record_id,eligible,exclusion_reason,title,year,doi,country,continent,income_group,iso3,lat,lon,region_city,sample_start,sample_end,property_type,price_type,document_type,estimators,spatial_method,time_fe,location_fe,se_type,n_obs_total,ai_methods,n_models,n_coefficients
008c3229443d60b36b8e1525b5af0589f63eb75d,True,,"Real Estate Prices in Beijing, 1644 to 1840",2012.0,10.1016/j.eeh.2012.10.003,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing,1644.0,1840.0,mixed,transaction,working_paper,OLS,none (location dummies),True,False,unknown,498.0,,4,40
009443a37464c7bfc0c1892b4c485e939d19af7c,False,"Aggregate unit of analysis: the regression (Tables 4-5, p. 9) is a monthly time-series model (2008 - October 2018) of the log of the AVERAGE housing price per square metre in Greater Santiago, with regressors that are monthly averages (average dwelling size, average building age, IDSE socioeconomic index of transaction areas, sales count) and macroeconomic series (mortgage rate, copper price, IPSA, money supply, construction cost index). The 456,133 individual transactions are not modelled at the property level, so no property-level characteristic coefficients exist. Kept qualitatively.",Testing Housing Price Drivers in Santiago de Chile: A Hedonic Price Approach,2023.0,10.13060/23362839.2023.10.2.558,Chile,South America,High income,CHL,-35.7,-71.5,Greater Santiago,2008.0,2018.0,mixed,transaction,journal,OLS,none,False,False,OLS,0.0,,0,0
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,True,,Analysis of Determinants of House Prices Using Hedonic Price Model: The Case of TR71 Region (Konut fiyatinin belirleyicilerinin hedonik fiyat modeliyle analizi: TR71 bolgesi ornegi),2021.0,10.25295/fsecon.895779,Turkey,Asia,Upper middle income,TUR,38.96,35.2,"TR71 region (Aksaray, Kirikkale, Kirsehir, Nevsehir, Nigde provinces)",2021.0,2021.0,mixed,listing,journal,OLS,none (province dummies),False,True,robust,1000.0,,1,13
00fe81644f944eeadcdbef9deb3f1be4026fb701,False,"Aggregate unit of analysis: dependent variable is the (log) mean price per square metre of flats in each of 80 Paris quartiers per year (balanced panel 80 x 14 = 1,120 per flat type), and regressors are quartier-level mean characteristics (shares of flats with one bathroom, maid's room, garage, floor level bands, size bands, construction period, street type, distance to quartier/arrondissement centre). Not property-level hedonic coefficients.",Maximum Likelihood Estimation and Lagrange Multiplier Tests for Panel Seemingly Unrelated Regressions with Spatial Lag and Spatial Errors: An Application to Hedonic Housing Prices in Paris,2010.0,10.1016/j.jue.2010.08.007,France,Europe,High income,FRA,46.2,2.2,Paris (80 quartiers),1990.0,2003.0,condo_apartment,transaction,working_paper,SAC,"SUR panel with spatial lag and spatial error (ML), distance and contiguity weight matrices",True,False,unknown,1120.0,,0,0
01e2f1bf2915117a013dff8a924c07e2ed16f152,False,"No hedonic coefficient table. The paper estimates a generalized propensity score (GPS) dose-response function of price per m2 with respect to four continuous 'treatments' (relative immigrant density/diversity, restaurant density/diversity); results are presented only as dose-response figures and the housing/location covariates (rooms, dwelling type, garden, distances) enter the first-step selection equation. Only Tables 1-3 (descriptives, dummies, correlations) are printed; no coefficients on housing characteristics are available.",Living apart together: The economic value of ethnic diversity in cities,2022.0,10.1177/23998083221082112,Netherlands,Europe,High income,NLD,52.1,5.3,Amsterdam,2006.0,2011.0,mixed,transaction,journal,other,none,True,False,unknown,40140.0,,0,0
036af7575382c2b07d715add3e591d6f0d1ad955,False,"Aggregate unit of analysis: cross-section of 985 Italian railway station areas; dependent variable is the average OMI (Osservatorio del Mercato Immobiliare) residential quotation in euro/m2 for the 1 km area around each station (mean ~1,280 euro/m2), regressed on station/municipal features and CFA latent constructs (Table 7, p. 11). No dwelling-level transactions and no property characteristic coefficients.",Modelling Real-Estate Values Around Railway Stations: Insights from an Italian Case,2026.0,10.3390/su18052304,Italy,Europe,High income,ITA,41.9,12.6,Nationwide (985 RFI railway stations),,,unknown,appraisal,journal,OLS,none,False,False,OLS,985.0,,0,0
03ae226b461f39ce77988b8e944f5ba8259156d3,True,,Modeling hedonic residential rents for land use and transport simulation while considering spatial effects,2010.0,10.5198/jtlu.v3i2.117,Switzerland,Europe,High income,CHE,46.8,8.2,Canton Zürich (171 municipalities),2004.0,2005.0,rental,rent,journal,OLS;spatial_error;spatial_lag;GWR,"SARerr and SARmix (k=9 nearest neighbours), GWR adaptive kernel",True,False,OLS,8592.0,,7,141
03bfeba917085bc65a0ab641e5a03916b687b20f,True,,Economic feasibility of wood-based structures—Improving urban carbon neutrality strategies,2021.0,10.1088/2634-4505/abfe05,Finland,Europe,High income,FIN,61.9,25.7,"Helsinki metropolitan area (Helsinki, Espoo, Vantaa)",1999.0,2018.0,condo_apartment,transaction,journal,OLS,none (postal-code dummies),False,True,clustered,27954.0,,9,9
03c7319d6d03a3326e49bd775951ee9918110cee,True,,Does my house have a premium or discount in relation to my neighbors? A regression-kriging approach,2020.0,10.1016/j.seps.2020.100914,Spain,Europe,High income,ESP,40.5,-3.7,Granada,2013.0,2013.0,condo_apartment,listing,journal,OLS;other,Regression-kriging (GLS + ordinary kriging of residuals),False,False,unknown,296.0,,2,16
05133875334147dc5ac7d37a0479720642327db6,True,,"Market Frictions, Arbitrage, and the Capitalization of Amenities",2019.0,10.3386/w25701,United States,North America,High income,USA,37.1,-95.7,Chicago-Naperville-Elgin IL-IN-WI metropolitan area (Census block groups),2005.0,2012.0,unknown,transaction,working_paper,OLS,,False,False,unknown,37564.0,,4,59
07441798ac5873fe53746864fd3cf3231a87b056,True,,Impact of infill development on prices of existing apartments in Finnish urban neighbourhoods,2018.0,10.3846/ijspm.2018.1540,Finland,Europe,High income,FIN,61.9,25.7,"Helsinki capital region (Helsinki, Espoo, Vantaa); seven case neighbourhoods with reference neighbourhoods",2000.0,2012.0,condo_apartment,transaction,journal,OLS,none,False,False,unknown,2762.0,,7,63
0795e1f2569ab3c9b87c0451960aa54739093319,True,,Performance of Multiple Linear Regression and Nonlinear Neural Networks and Fuzzy Logic Techniques in Modelling House Prices,2012.0,10.3844/jmssp.2012.419.434,Australia,Oceania,High income,AUS,-25.3,133.8,"Bathurst, New South Wales",1992.0,2004.0,single_family,transaction,journal,OLS;ML_marginal,"none (map coordinates X, Y as regressors)",False,False,unknown,4210.0,neural_network;ANFIS neuro-fuzzy,1,6
07b241fa57ce2f3e40926461143e077561f2a1cd,False,"Aggregate unit of analysis: regressions use Seoul's 25 autonomous districts (Gu) as observations, with district housing prices (multi-unit, single-unit, apartment) regressed on counts of heritage sites and protected areas; no dwelling-level characteristics or property-level price data.","Urban Heritage and its Socioeconomic Impacts in Seoul, South Korea: An Empirical Study Using Residential Environmental Satisfaction and Housing Price as Indicators",2022.0,10.11628/ksppe.2022.25.3.311,South Korea,Asia,High income,KOR,35.9,127.8,Seoul (25 Gu districts),0.0,0.0,mixed,unknown,journal,OLS;spatial_lag;spatial_error,SLM/SEM at district level,False,False,unknown,25.0,,0,0
0893ce95f4ec80e891e9cf83dfb029d633e4a22d,True,,Hedonic regression analysis in determining the effect of green on high rise residential,2022.0,10.21837/pm.v20i21.1114,Malaysia,Asia,Upper middle income,MYS,4.2,101.9,"Timur Laut District, Penang Island",2016.0,2020.0,condo_apartment,transaction,journal,OLS,none,True,True,OLS,934.0,,1,12
09caaf09cd085f29d8f22c8f28dd86b492ec121d,False,"Not a hedonic regression study: the paper proposes a theoretical 'dynamic impact function' of distance to MRT stations and validates it by correlating predicted and actual price per m2 for 138 units sold in May 2009 around four Taipei MRT stations (Tables 1-4 list raw observations and correlation coefficients r = 0.946/0.981/0.944/0.912). No regression coefficients, standard errors or characteristic implicit prices are estimated or reported.","Establishing dynamic impact function for house pricing based on surrending multi-attributes: evidence from Taipei City, Taiwan",2020.0,10.3846/ijspm.2020.11096,Taiwan,Asia,High income,TWN,23.7,121.0,Taipei City,2009.0,2009.0,condo_apartment,transaction,journal,other,distance decay function (non-regression),False,False,unknown,138.0,,0,0
0a4917c7f444817b4974629ac2f7d58ef2f99321,True,,"The Hedonic Method in Evaluating Apartment Price: A Case of Ho Chi Minh City, Vietnam",2020.0,10.13106/jafeb.2020.vol7.no6.517,Vietnam,Asia,Lower middle income,VNM,14.1,108.3,Ho Chi Minh City (24 districts),,,condo_apartment,transaction,journal,OLS,,False,False,unknown,339.0,,2,24
0a56ff9c5aeeb80c811f28d082785dd37d837fcc,True,,Determining the Property Value Impact of Landfills,1993.0,10.15760/etd.6640,United States,North America,High income,USA,37.1,-95.7,"Portland, Oregon (neighbourhood within ~0.5 mile of the Lavele limited-purpose landfill)",1971.0,1986.0,single_family,transaction,thesis,OLS,none,False,False,OLS,211.0,,3,29
0aed4606387835599541d79050eabb05449e0442,True,,The effect of Movida on residential property prices: up or down?,2023.0,10.1080/00036846.2022.2159008,Italy,Europe,High income,ITA,41.9,12.6,Turin,2017.0,2018.0,condo_apartment,transaction,journal,OLS;quantile,urban macro-area fixed effects; two-way cluster-robust SE,True,True,clustered,6861.0,,13,195
0b9eefecd90b818651be4c57fe476bab87958359,True,,Determining Factors on Housing Price in Beijing Using Regression Analysis,2025.0,10.54254/2754-1169/2024.ld19187,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing,,,condo_apartment,transaction,conference,OLS;IV,none,False,False,robust,3139.0,,2,14
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,True,,Willingness-to-pay for energy efficient homes: New insights from the 2022 energy crisis in the United Kingdom,2026.0,10.1016/j.erss.2026.104700,United Kingdom,Europe,High income,GBR,55.4,-3.4,Greater Manchester (England),2017.0,2024.0,single_family,listing,journal,other,two-level multilevel model with LSOA random intercepts,True,False,unknown,170137.0,,8,75
0d749c58da0b3282e774a34a3cbd378d57ba0801,True,,The capitalization of geomantic attributes: evidence from the housing market in Guangzhou,2023.0,10.48264/vvsiev-20233304,China,Asia,Upper middle income,CHN,35.9,104.2,Guangzhou (six districts),2013.0,2016.0,condo_apartment,transaction,journal,OLS,none (district fixed effects),True,True,robust,4859.0,,11,179
0d7a1f874f9358489f6f5882b5a4900f21774211,True,,Spatial Heterogeneity in Housing Market: Ankara Metropolitan Area,2022.0,10.18070/erciyesiibd.1122568,Turkey,Asia,Upper middle income,TUR,38.96,35.2,Ankara metropolitan area (8 districts),2021.0,2021.0,condo_apartment,listing,journal,OLS;GWR,"GWR (Gaussian adaptive kernel; bandwidth 45 by CV, 59 by AIC)",False,False,OLS,2784.0,,3,57
0e568775e77ac2d90b96f6f8ecad954135ed43b0,True,,Listing price estimation of apartments: A generalised linear model,2019.0,10.4102/jef.v12i1.204,South Africa,Africa,Upper middle income,ZAF,-30.6,22.9,"KwaZulu-Natal (Ballito, Durban Central, Umhlanga)",2016.0,2016.0,condo_apartment,listing,journal,other,suburb dummies; Mantel test for residual spatial autocorrelation,False,True,OLS,1314.0,,1,3
0e8221fad5dffd447b52c9be164621765eb67679,True,,From peaks to prices: the economic impact of natural amenities on alpine real estate values,2025.0,10.1108/jerer-02-2025-0033,Italy,Europe,High income,ITA,41.9,12.6,"Belluno Dolomites (Veneto), Italian Alps, 10 municipalities",2022.0,2023.0,mixed,transaction,journal,OLS;spatial_lag,"SAR (spatial lag, GeoDa, row-standardised W)",False,False,OLS,447.0,,2,32
0f2b62072edfd32a439d1606541bbbb8547810e4,True,,Willingness to pay for accessibility under the conditions of residential segregation,2014.0,10.3846/1648715x.2013.864342,France,Europe,High income,FRA,46.2,2.2,"Lyon metropolitan area (central part; suburbs Sainte-Foy-les-Lyon, Oullins, Venissieux, Vaulx-en-Velin)",1997.0,2008.0,condo_apartment,transaction,journal,OLS;spatial_error;GWR,Spatial Error model (threshold-distance weights) for submarkets; GWR on all sales,True,True,unknown,4362.0,,96,196
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,True,,End of the line: The impact of new suburban rail stations on housing prices,2023.0,10.5198/jtlu.2023.2199,United States,North America,High income,USA,37.1,-95.7,"Prince George's County, Maryland (Washington, DC suburb)",1998.0,2007.0,single_family,transaction,journal,OLS;FE_panel,none (ZIP FE / house FE),True,True,clustered,57912.0,,8,24
0fe82e8b18cc371498773e34654f4904c5d797a9,False,"Hedonic model (Table 5, p.11) reports only the appraisal-anchoring variables (ln capital value, days since appraisal, interaction); housing characteristic coefficients (bedrooms, bathrooms, floor area, view, region/time dummies) are included but not printed ('results of other fixed effects are not shown'). No usable characteristic coefficients.",Homebuyer Purchase Decisions: Are They Anchoring to Appraisal Values or Market Prices?,2022.0,10.3390/jrfm15040159,New Zealand,Oceania,High income,NZL,-40.9,174.9,New Zealand (14 regions),1990.0,2020.0,mixed,transaction,journal,OLS,none (regional dummies),True,True,unknown,1559117.0,,0,0
0ff4eb143517f757d1f3f4078cf390068474a83a,True,,"Big data, accessibility and urban house prices",2021.0,10.1177/0042098020982508,United States,North America,High income,USA,37.1,-95.7,"Miami-Dade County, Florida (Miami MSA)",2016.0,2016.0,single_family,transaction,journal,OLS;SAC,"Combined spatial autoregressive and spatial error model (Model 6), 5 nearest neighbours inverse-distance weights, lags of controls",True,False,unknown,13932.0,,6,130
1076844f99e9f35c7768a4e64f2c167ab26b5afd,True,,Predicting Housing Prices in Riyadh: A Comparative Analysis on Machine Learning and Hedonic Regression,2025.0,10.64389/isp.2025.01220,Saudi Arabia,Asia,High income,SAU,23.9,45.1,Riyadh,2024.0,2024.0,mixed,listing,journal,OLS,none (district dummies),False,True,OLS,2997.0,ANN;random_forest,1,11
11135c13b52c3fe849cfd9899af8e92968906ec5,True,,Assessing the Impact of Wildfires on the Swedish Housing Market: a Case Study of the 2014 Västmanland Wildfire,2026.0,10.1007/s41885-026-00200-3,Sweden,Europe,High income,SWE,60.1,18.6,"Västmanland County and surroundings (transactions within 100 km of the 2014 wildfire perimeter, Eastern Sweden)",2012.0,2016.0,mixed,transaction,journal,OLS;spatial_lag,spatially lagged selling price W(Price) over 200 nearest transactions (cols 3-5); postal-code FE in col 5,True,True,OLS,98269.0,,17,41
1196e55c7401009f4e60d7c8db96469c1e13b00e,True,,Capitalization of Open Spaces into Housing Values and the Residential Property Tax Revenue Impacts of Agricultural Easement Programs,2003.0,10.1017/s1068280500002483,United States,North America,High income,USA,37.1,-95.7,"Calvert, Carroll and Howard counties, Maryland",1993.0,1996.0,single_family,transaction,journal,OLS;spatial_error,"spatial error model (u = lambda*W*u + e), row-standardised inverse-distance weights, 1,000 m cut-off, ML",True,False,unknown,10135.0,,6,108
11ddac3108d5fcc806866635ea2276160f2ca53d,True,,Coastal armoring and sinking property values: the case of seawalls in California,2020.0,10.1007/s10018-020-00278-3,United States,North America,High income,USA,37.1,-95.7,"San Diego County and Santa Cruz County, California (homes within 1,000 ft of the shoreline)",1944.0,1999.0,single_family,transaction,journal,OLS;spatial_lag;spatial_error;SAC,"spatial lag, spatial error and SARAR(1,1) ML models with inverse-distance weights (Santa Cruz only)",False,False,robust,283.0,,18,210
122e07c191e40cdc3321c3817fb731f2d55466e1,True,,"Path selection of spatial econometric model for mass appraisal of real estate: evidence from Yinchuan, China",2023.0,10.3846/ijspm.2023.20376,China,Asia,Upper middle income,CHN,35.9,104.2,"Yinchuan, Xixia District (Ningxia)",2022.0,2022.0,condo_apartment,listing,journal,spatial_lag;other,"Spatial Durbin model, k=16 nearest-neighbour weight matrix (GeoDa)",False,False,unknown,429.0,,1,10
129023b53e859d480f057e1aa633ff7548d6c727,False,"Conference essay reviewing anchoring effects; the only estimates (Tables 1-3, p.4) are descriptive statistics, panel unit-root tests and a panel VAR of city-level log price on lagged log transaction volume (aggregate city panel). No residential hedonic regression with property characteristic coefficients; the 'improved hedonic model' is only discussed from secondary literature.",Anchoring Effect in China's Real Estate Market,2023.0,10.54254/2754-1169/14/20230815,China,Asia,Upper middle income,CHN,35.9,104.2,"China (national, east/mid/west panel); Hong Kong; Taipei (literature)",0.0,0.0,unknown,transaction,conference,other,,False,False,unknown,2652.0,,0,0
13561959c7aabb108ebf10b83cf499e51f169500,True,,Flood risk management and real-estate prices: between prevention and “crowding out” effect,2025.0,10.3389/frevc.2025.1603746,France,Europe,High income,FRA,46.2,2.2,Bordeaux metropolitan area and neighbouring estuarine municipalities (Gironde),2011.0,2016.0,single_family,transaction,journal,OLS;spatial_error,"spatial error model (SEM), ML, 1-nearest-neighbour weights (R spdep)",True,False,unknown,24871.0,,2,44
13a61953f01e5f8f119d4fa1872eb72503252526,True,,The Reflection of Income Segregation and Accessibility Cleavages in Sydney's House Prices,2022.0,10.3390/ijgi11070413,Australia,Oceania,High income,AUS,-25.3,133.8,Greater Sydney,2016.0,2016.0,single_family,transaction,journal,OLS;GWR,GWR with adaptive bi-square kernel (Table 5),False,False,OLS,32068.0,,2,36
14eecd7db66f7a02fa146490275ce97a19765a1a,True,,"The impact of a new light rail system on single-family property values in Charlotte, North Carolina",2012.0,10.5198/jtlu.v5i2.261,United States,North America,High income,USA,37.1,-95.7,"Charlotte (Mecklenburg County), North Carolina",1997.0,2008.0,single_family,transaction,journal,OLS,block-group fixed effects; Moran's I on residuals reported,False,True,unknown,6381.0,,4,36
154f55871a6811fb1dd94f5c020e97dabe79c8c3,True,,Efficient property value estimation for single-family homes in central Florida,2024.0,10.1111/itor.13565,United States,North America,High income,USA,37.1,-95.7,"Florida, Orange and Seminole counties",,,single_family,appraisal,journal,OLS;other,none (county dummy),False,True,robust,30555.0,,2,14
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,True,,"Objective Housing Sales and Rent Prices in Representative Household Surveys: Implications for Wealth, Inequality, Housing Market, and Affordability Statistics",2024.0,10.1111/roiw.12692,Luxembourg,,,,,,Luxembourg (whole country; composite geography of municipalities and neighbourhoods),2018.0,2018.0,mixed,listing,journal,OLS;other,"locality dummies (Main, Alt.3); Markov random field linked-neighbour spline (Alt.2); distance to capital (Alt.1)",False,True,unknown,22619.0,,10,168
18a3ce8a193301208557e0d6f2d027166917cb25,True,,Impact of ground source heat pumps on house sales prices in Finland,2023.0,10.1007/s12053-023-10084-x,Finland,Europe,High income,FIN,61.9,25.7,"Eight cities: Helsinki, Espoo, Vantaa, Turku, Tampere, Lahti, Kuopio, Oulu",1999.0,2018.0,single_family,transaction,journal,OLS,none (postcode fixed effects),True,True,unknown,19008.0,,14,42
1908d2ee0b0995f38129f51d7446a3626531b8d6,True,,Mind the Anticipation Gap: A Difference-in-Differences Analysis of the Elizabeth Line's Impact on London Housing Prices,2026.0,10.67913/vner/2026.1.1.1,United Kingdom,Europe,High income,GBR,55.4,-3.4,Greater London and outer boroughs with Elizabeth Line stations,2000.0,2024.0,mixed,transaction,journal,FE_panel,none (property fixed effects; distance bands to stations),True,True,clustered,1602487.0,,6,16
1956ccee53765fb417ccdc3f95db189441def931,True,,Analyzing the Impact of Accessibility on Residential Property Price: A Case study of Hanoi's Central Districts,2025.0,10.64711/dq21w997,Vietnam,Asia,Lower middle income,VNM,14.1,108.3,Hanoi (12 central districts),2024.0,2025.0,mixed,listing,journal,OLS;GWR,"GWR (ArcGIS, AIC bandwidth) in addition to global OLS",False,False,robust,1545.0,,1,7
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,True,,Property Tax Capitalization within a National Historic District versus Property Tax Capitalization outside that National Historic District: Another Application of the Tiebout Hypothesis,2011.0,10.5539/ijef.v3n4p14,United States,North America,High income,USA,37.1,-95.7,"Savannah, Georgia (Savannah Historic Landmark District and rest of metro area)",2000.0,2005.0,single_family,transaction,journal,OLS,none,False,False,robust,2501.0,,4,60
1ad007ac2e8575311162da739431607dfdaeeb1b,True,,The Research on Factors Influencing Housing Prices-Take Chicago as an Example,2025.0,10.54254/2753-8818/2025.23756,United States,North America,High income,USA,37.1,-95.7,Chicago (as stated by the authors; see notes),0.0,0.0,unknown,unknown,conference,OLS,none,False,False,OLS,100.0,,1,11
1b06d5abfe32d650517ed54e21f8d196f135c666,True,,"Impact of light rail line on residential property values - a case of Sydney, Australia",2021.0,10.1108/ijhma-03-2021-0033,Australia,Oceania,High income,AUS,-25.3,133.8,"Sydney - Kensington/Randwick (around UNSW, CBD and South East Light Rail stops)",2012.0,2020.0,mixed,transaction,journal,OLS,,False,False,unknown,702.0,,2,18
1b4b730b1b7e5c68c755a7ae46919b1120fc8c06,True,,Housing Markets in Uruguay: Determinants of Housing Demand and Its Interaction with Public Policies,2011.0,10.18235/0011348,Uruguay,South America,High income,URY,-32.5,-55.8,Montevideo (20 neighbourhood groups) and upcountry (14 regional groups),2006.0,2006.0,mixed,rent,working_paper,other;OLS,none (separate regressions by market),False,False,unknown,21310.0,,34,379
1cd473df8f393883694de4530b0d1c667382890c,True,,"Exploring a multilevel approach with spatial effects to model housing price in San Jose, Costa Rica",2021.0,10.1177/23998083211041122,Costa Rica,,,,,,San Jose Metropolitan Region,,,single_family,listing,journal,other,Bayesian multilevel random intercepts (166 districts) with intrinsic CAR spatial prior (CARM); MCMC in WinBUGS,False,True,unknown,1264.0,,3,24
1ce55be799df6cb17762fb0541fe95340687f3de,True,,The willingness to pay for access to piped water: a hedonic analysis of house prices in Southwest Sri Lanka,2012.0,10.1007/s12076-012-0079-y,Sri Lanka,Asia,Lower middle income,LKA,7.9,80.8,"Southwest Sri Lanka (Negombo, Kalutara, Galle districts)",2003.0,2004.0,single_family,appraisal,journal,OLS,none (district dummies),False,True,unknown,1523.0,,2,18
1d57857811e3f735e7c7dfe3dfb0c766f1aba868,True,,Adaptive Reuse of Religious Heritage and Its Impact on House Prices,2020.0,10.1007/s11146-020-09798-x,Netherlands,Europe,High income,NLD,52.1,5.3,Netherlands (areas within 2 km of 42 reused religious heritage sites),1995.0,2017.0,mixed,transaction,journal,OLS;other,difference-in-differences with neighbourhood fixed effects (1 km treatment ring vs 1-2 km control ring); non-parametric DiD (Diamond & McQuade 2019),True,True,robust,342439.0,,6,6
1daf1d20ba429ff68e39043313dece9a679c8c5d,True,,A spatial semiparametric M-quantile regression for hedonic price modelling,2023.0,10.1007/s10182-023-00476-w,Italy,Europe,High income,ITA,41.9,12.6,Milan,2004.0,2010.0,condo_apartment,transaction,journal,quantile,bivariate thin-plate spline on coordinates (spatial trend) inside M-quantile model,False,False,unknown,3946.0,,5,70
2075796388c43cd5aedc64728dd832af194aa20d,False,"Aggregate unit of analysis: panel of 30 Chinese cities x 10 years (2006-2015) regressing log average city residential house price (yuan/m2, China Real Estate Statistical Yearbook) on city-level PM10 with city fixed effects and RD/IV designs. No property-level hedonic regression and no dwelling characteristic coefficients (only city covariates such as GDP, wage, population density). Keep qualitatively for air-pollution capitalisation (approx. -1% per ug/m3 PM10, Tables 4-7).",Effects of air quality on house prices: evidence from China's Huai River Policy,2021.0,10.1080/00779954.2020.1827014,China,Asia,Upper middle income,CHN,35.9,104.2,30 provincial capital cities north and south of the Huai River,2006.0,2015.0,unknown,transaction,journal,FE_panel;IV;other,regression discontinuity in latitude distance from Huai River,False,True,unknown,300.0,,0,0
21199d311319fd0034523954fb23eaaf34739428,False,"Regression tables (Tables 4 and 6, p. 14) regress price per m2 on three expert-weighted composite indicators (location Cl, position Cp, technical Ct) built by multi-attribute aggregation; no coefficient is attached to an identifiable property, neighbourhood, environmental or location characteristic, so nothing maps to the taxonomy.",Assessing the Impact of Urban Improvement on Housing Values: A Hedonic Pricing and Multi-Attribute Analysis Model for the Historic Centre of Venice,2017.0,10.3390/buildings7040112,Italy,Europe,High income,ITA,41.9,12.6,Venice (historic centre),,,condo_apartment,transaction,journal,OLS,none,False,False,robust,197.0,,0,0
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,True,,The Amenity Value of English Nature: A Hedonic Price Approach,2014.0,10.1007/s10640-013-9664-9,United Kingdom,Europe,High income,GBR,55.4,-3.4,England (Model 5: Great Britain),1996.0,2008.0,mixed,transaction,working_paper,OLS,Travel-to-Work-Area fixed effects (Models 3-5),True,True,clustered,1013125.0,,5,125
2344ebd24eeebb31c33011f3e72a12383c3c1e88,True,,"Hedonic Price Modeling of New Residential Property Values in Xi'an City, China",2017.0,10.11114/ijsss.v5i9.2510,China,Asia,Upper middle income,CHN,35.9,104.2,Xi'an,2014.0,2014.0,condo_apartment,listing,journal,OLS,none (residual mapping only),False,False,OLS,378.0,,1,6
23a821c97160e852a6c2dd5c6097aa79bfac7ed3,False,"Aggregate unit of analysis: 1498 residential price samples averaged into 653 sample-area means (Shunde District, Foshan, China, 1999/2001-2010, Yuan/m2, calibrated to 2010 level) and modelled with a flexible spatiotemporal mixed model (FSTM) built for spatial prediction. The only coefficient table (Table 1, p.15: level Yuan/m2 on distance to centre, road/market/bus/telecom/supermarket/post/bank densities, public area, shared area, 2003 population density; SE and p-values printed, units of regressors undefined) contains no dwelling characteristic coefficients and the regressors are area-level densities with unstated units. Not usable for coefficient synthesis; keep as qualitative (ML/spatiotemporal prediction) evidence.",Prediction and analysis of residential house price using a flexible spatiotemporal model,2022.0,10.1080/15140326.2022.2045466,China,Asia,Upper middle income,CHN,35.9,104.2,"Shunde District, Foshan, Guangdong",2001.0,2010.0,unknown,transaction,journal,other,"flexible spatiotemporal mixed-effects model (FSTM, random coefficients, Gaussian Markov random fields, ML)",True,False,unknown,653.0,,0,0
25220943ab063e0fe03168460d2005c02cf25de0,True,,Mass Appraisal of Property Tax Base based on Multivariate Linear Regression - Empirical Study on Four Districts of Jinan,2013.0,10.2991/icetis-13.2013.254,China,Asia,Upper middle income,CHN,35.9,104.2,"Jinan, Shandong (Tianqiao, Huaiyin, Shizhong, Lixia districts)",2012.0,2012.0,condo_apartment,transaction,conference,OLS,none (district code as a numeric regressor),False,False,OLS,226.0,,1,6
2565afc9ee2e15c0daf31480b06229279a91d815,False,"Aggregate unit of analysis: the regression explains the MEDIAN house value of census blocks (California housing block dataset: housing median age, total rooms, total bedrooms, population, households, median income per block, longitude/latitude), not individual dwelling prices; no property-level characteristic coefficients. Student conference paper (ICFTBA 2024), sample period not stated.","Study of the Factors Influencing House Prices in California, USA",2025.0,10.54254/2754-1169/2024.19450,United States,North America,High income,USA,37.1,-95.7,California (census blocks),0.0,0.0,unknown,other,conference,OLS,none (longitude/latitude as regressors),False,False,OLS,0.0,,0,0
2580ac3af513b0ee5f2e19ed10bd991f2a8c8015,True,,Extracting real estate values of rental apartment floor plans using graph convolutional networks,,,Japan,Asia,High income,JPN,36.2,138.3,Osaka Prefecture,2015.0,2015.0,rental,rent,working_paper,OLS,,False,False,unknown,15323.0,graph convolutional network (ResGatedGraphConv) on floor-plan access graphs producing a floor-plan value (FPV);semantic segmentation of floor-plan images;integrated gradients,2,25
2799534456858542797f23b6cf17bd1f12439819,True,,Towards a Hedonic Pricing Method for the Bucharest Private Housing Market,2019.0,10.47743/saeb-2019-0031,Romania,Europe,High income,ROU,45.9,25.0,Bucharest,2014.0,2018.0,condo_apartment,transaction,journal,OLS;quantile,none,False,False,unknown,765.0,,98,727
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,True,,Impact of Air Pollution on Property Values: A Hedonic Price Study,2013.0,10.23917/jep.v14i1.150,Indonesia,Asia,Upper middle income,IDN,-0.8,113.9,Yogyakarta Special Region (city of Yogyakarta and Sleman regency),,,single_family,transaction,journal,OLS,none,False,False,unknown,250.0,,2,18
28afe169f4e2851e590b8152147dbd5bb4ee90f0,True,,Quality of Life in Chinese Cities,2021.0,10.2139/ssrn.3764334,China,Asia,Upper middle income,CHN,35.9,104.2,287 prefecture-level cities (national),2005.0,2005.0,mixed,transaction,working_paper,OLS,none,False,False,clustered,421660.0,,2,30
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,True,,Exploring the quantitative impact of medical marijuana dispensaries on residential sale prices in Oklahoma,2026.0,10.1007/s00181-026-02894-6,United States,North America,High income,USA,37.1,-95.7,"Oklahoma (Comanche, Oklahoma, Payne, Tulsa, Wagoner, Washington counties)",2020.0,2023.0,single_family,transaction,journal,OLS,none (county dummies),True,True,unknown,28022.0,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,14,108
290a4bf33ce230c96c2113bb929c287ce4514c65,True,,Borrowed sizes: A hedonic price approach to the value of network structure in public transport systems,2021.0,10.5198/jtlu.2021.1664,Sweden,Europe,High income,SWE,60.1,18.6,Scania (Skane) region,2016.0,2016.0,single_family,transaction,journal,spatial_error,"spatial error model (GMM, Kelejian-Prucha 2010 SEs), Euclidean-distance weights with GeoDaSpace default bandwidth",False,False,robust,18273.0,,6,67
291ca9688b933cfaf7d01e6f6552e428bb2432b5,True,,Occupant Well-Being and House Values,2020.0,10.36934/wecon2019-023,Netherlands,Europe,High income,NLD,52.1,5.3,"North of the Netherlands (Groningen, Friesland, Drenthe)",2000.0,2012.0,mixed,transaction,working_paper,OLS;IV;other;SAC,GNS (general nesting spatial model) and SAC (spatial lag + spatial error) with inverse-distance weights (1 km),True,False,unknown,14857.0,,7,137
29ce2045a8b41ca2314a2b80fea6fdc3b22ab75f,False,"Not an empirical housing-market study: the author states 'the dataset used was simulated' (p. 6); 1,000 synthetic observations, variables only labelled X1-X7 in Table 2 (p. 5) with no units, location, period or price definition. No real residential price data.",Research on the Factors Influencing Housing Prices,2025.0,10.54254/2753-8818/2025.gl24068,Unknown,,,,,,unknown (simulated data),,,unknown,unknown,conference,OLS,none,False,False,OLS,1000.0,,0,0
2b0979784a826ff5181dbb43492b0239ca3062e8,True,,The Value of a Sea View: Hedonic Estimates Using 3D Simulation and Natural Language Processing,2023.0,10.3368/le.100.2.071522-0056r,Ireland,Europe,High income,IRL,53.1,-8.2,"Republic of Ireland, listings within 5 km of the coastline",2014.0,2019.0,mixed,listing,journal,OLS,"spatial fixed effects at various levels (local market, micro-market, electoral division, small area, ED x year, small area + micro-market x year)",True,True,clustered,100030.0,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),16,64
2bbd25e60ca8ea2625da98d69a5096e00200229f,True,,Does energy efficiency matter for prices of tenant-owned apartments?,2022.0,10.1007/s11356-022-20482-w,Sweden,Europe,High income,SWE,60.1,18.6,"Malmö, Göteborg, Linköping, Stockholm, Luleå, Umeå (six municipalities)",2019.0,2019.0,condo_apartment,transaction,journal,OLS;other,none (postcode fixed effects),True,True,robust,21696.0,,27,138
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,True,,Valuing Historical and Open Space Amenities with Hedonic Property Valuation Models,2016.0,10.1017/age.2016.14,United States,North America,High income,USA,37.1,-95.7,"York County, James City County and City of Williamsburg, Virginia",1998.0,2004.0,single_family,transaction,journal,spatial_error,"Spatial error model (lambda) with contiguity-based (strict, 200 m, 400 m, 600 m) and distance-based (1/d, 1/d^2 within 600 m) row-standardised weight matrices; OLS rejected",True,True,unknown,12337.0,,12,192
2cdb6f374417590715ab5db24f593d17616b9ea2,False,"No regression coefficients are printed: the paper compares predictive performance of linear regression, random forest, XGBoost and gradient boosting (Table 2: R2, MSE, MAE, MedAE) and interprets the gradient-boost model with SHAP importance plots, partial dependence and interaction figures; the linear-regression coefficients for the structural, walkability, streetscape and locational variables are not reported (only definitions and descriptives in Table 1). SHAP values are not marginal effects usable in the coefficient synthesis.",Effects of neighborhood streetscape on the single-family housing price: Focusing on nonlinear and interaction effects using interpretable machine learning,2025.0,10.1371/journal.pone.0323495,South Korea,Asia,High income,KOR,35.9,127.8,Seoul,2017.0,2019.0,single_family,transaction,journal,OLS;ML_marginal,none (latitude/longitude as features),False,False,unknown,13776.0,computer_vision_streetscape;gradient_boosting;XGBoost;random_forest;SHAP,0,0
2ce98014780d8a025c9acf3e943a33fd71e8d5b6,False,"No hedonic regression coefficients on property characteristics are printed. The paper reports only average treatment effects (ATT, in $000s per home) of Mountain Pine Beetle tree damage from a GenMatch matching estimator with Bayesian regression adjustment (Table 4, p. 8/53); the auxiliary weighted-OLS regression coefficients for age, square footage, lot size, bedrooms, bathrooms, wildfire and quarter indicators are not reported. Flag for human review: the ATTs (full sample -10.471 (2.926); Golden -23.097 (5.871); Boulder -124.338 (81.445), posterior mean (std), benchmark PI-visual) could serve a qualitative environmental synthesis but are not hedonic coefficients.",Forest pests and home values: The importance of accuracy in damage assessment and geocoding of properties,2017.0,10.1016/j.jfe.2017.02.002,United States,North America,High income,USA,37.1,-95.7,"Colorado front range (Golden, Boulder), wildland-urban interface",,,single_family,transaction,journal,other,matching (GenMatch) with Bayesian regression adjustment; sub-regional fixed effects in full-sample regression,False,True,unknown,908.0,,0,0
2d5062b633e25ceaf8877d3b26abf6c4fd403dba,True,,"Impacts of commuter rail transit on property values: the case of the Montreal North Shore, Canada, 1992-2009",2012.0,10.15396/eres2012_294,Canada,North America,High income,CAN,56.1,-106.3,"Montreal North Shore (Rosemere, Sainte-Therese, Blainville, Saint-Jerome stations), Quebec",1992.0,2009.0,single_family,transaction,conference,other,spatio-temporal accessibility indices; DID repeat-sales differencing used to control spatial autocorrelation,True,False,unknown,26366.0,,4,19
2e573f3384314fd1e0b0dd7c24f567743146abb7,False,"Repeat-sales house price index methodology paper (characteristics repeat sales, Florida 2002-2020). Tables report only summary statistics (Table 1) and model fit statistics (Table 2: R2, AIC, BIC, GCV); no implicit-price coefficients of housing characteristics on price level are printed (characteristics enter as time-varying spline effects on price change, shown only as index figures).",Selection Bias in Housing Price Indexes: The Characteristics Repeat Sales Approach,2022.0,10.1111/obes.12534,United States,North America,High income,USA,37.1,-95.7,Florida,2002.0,2020.0,mixed,transaction,journal,other,county effects,True,True,unknown,1049478.0,,0,0
2f1c2029c5f2034d797bc4a5ae390cff3782ab60,False,"Aggregate unit of analysis and no characteristic coefficients printed. All variables are measured at the level of 1,270 newly built residential blocks (block centroid; first-time transactions 2006-2016), i.e. block-level mean prices, not individual dwellings. Printed tables (2-5) report only the green-space area coefficient (per m2 of green space within 1 km, in log price), spline parameters and DID interaction terms; the housing/location controls (Table A1) are 'Yes' but never printed, and the appendix is not in the PDF.",Area-Based Hedonic Pricing of Urban Green Amenities in Beijing: A Spatial Piecewise Approach,2024.0,10.1007/s10640-024-00861-2,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing,2006.0,2016.0,condo_apartment,transaction,journal,OLS;IV;other,district and ring-road dummies; regression spline on distance; matching; spatial DID,True,True,unknown,1270.0,cross-validated model selection (regression spline knots),0,0
309364b6d8361dba9a9e751b55ade4c452cd784b,True,,The research of influence factors that possibly lead to the change in house prices,2023.0,10.54254/2753-8818/14/20240926,India,Asia,Lower middle income,IND,20.6,79.0,India (city not stated),0.0,0.0,unknown,listing,conference,OLS,none,False,False,OLS,910.0,,1,10
323b30d53cb25830c8397eeb95e569a5dc5a3044,False,"Aggregate unit of analysis: observations are OMI-zone rental quotation ranges (min-max EUR/m2 per zone x dwelling type x conservation status; 54,214 cells, 8,046 municipalities), not individual dwellings; purpose is a Country-Product-Dummy spatial rent index. Only coefficients are region dummies, dwelling type (economic apartment, detached vs well-finished apartment), conservation status (excellent vs normal) and district class (semi-central, outskirts, suburban, rural vs central) with SEs (Tables 3A-3B, pp.13-16; log rent per m2 midpoint/min/max; N=54,214 and 16,040). Flag for human review: if zone-level quotation cells are accepted, type/condition/district coefficients could be extracted.",Sub-National Spatial Price Indexes for Housing: Methodological Issues and Computation for Italy,2022.0,10.2478/jos-2022-0004,Italy,Europe,High income,ITA,41.9,12.6,"Italy, 20 regions (all municipalities)",2017.0,2017.0,mixed,rent,journal,OLS;other,none (district and homogeneous-zone dummies),False,True,OLS,54214.0,,0,0
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,True,,Impacts of Ground Water Contamination on Property Values: Agricultural Run-off and Private Wells,2016.0,10.1017/age.2016.16,United States,North America,High income,USA,37.1,-95.7,"Lake County, Florida",1990.0,2013.0,single_family,transaction,journal,OLS;FE_panel;spatial_error,"spatial error model (inverse-distance SWM, 3,200 m radius, 12-month time constraint) and census block-group fixed effects",True,True,robust,1730.0,,8,28
327115a5186cc436d1749ca2acaa98314f882fee,True,,"Bus stop, property price and land value tax: A multilevel hedonic analysis with quantile calibration",2015.0,10.1016/j.landusepol.2014.07.017,United Kingdom,Europe,High income,GBR,55.4,-3.4,"Cardiff, Wales",2000.0,2008.0,mixed,transaction,journal,OLS;other;quantile,ward dummies (OLS) / ward and year random effects (multilevel),True,True,OLS,9669.0,,66,150
3372ad7c12532642d33524d3fe7c38467c784796,True,,Estimation of Hedonic Models Using a Multilevel Approach: An Application for the Swiss Rental Market,2008.0,10.1007/bf03399271,Switzerland,Europe,High income,CHE,46.8,8.2,Nationwide (municipalities as level-2 clusters),2006.0,2007.0,rental,rent,journal,OLS;other,multilevel (random intercept and random slope at municipality level); OLS variants with cantonal dummies,True,True,OLS,11913.0,,3,33
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,True,,"Predicting the rental value of houses in household surveys in Tanzania, Uganda and Malawi: Evaluations of hedonic pricing and machine learning approaches",2021.0,10.1371/journal.pone.0244953,Uganda,,,,,,National (LSMS-ISA household surveys),2010.0,2016.0,rental,rent,journal,OLS;other,"SAR and SEM estimated but coefficients not reported (only prediction performance, Tables 9-10)",False,True,unknown,4882.0,Ridge;LASSO;regression tree;bagging;random forest;boosting,18,227
33bb6f1b232198d68a02a325e907247d5c15da07,False,"No hedonic coefficient table is reported: the paper builds a rental dataset from online ads and estimates hedonic rent and price models by department/year only to derive municipal hedonic indices and rent-price ratios (Tables 5-8 are descriptive, index statistics, or ads-vs-survey comparison regressions). No printed characteristic coefficients for prices or rents in the main text (reproduction programs on OSF).",Can big data increase our knowledge of local rental markets? A dataset on the rental sector in France,2022.0,10.1371/journal.pone.0260405,France,Europe,High income,FRA,46.2,2.2,France (all municipalities),2016.0,2017.0,mixed,rent,journal,OLS,municipality / neighbourhood fixed effects,True,True,clustered,,,0,0
35b0e34c43595f2139ae225aceb59ae4af4bb8da,True,,Incentivizing the Public to Support Invasive Species Management: Eurasian Milfoil Reduces Lakefront Property Values,2014.0,10.1371/journal.pone.0110458,United States,North America,High income,USA,37.1,-95.7,"King County, Washington (41 lakes near Seattle)",1995.0,2006.0,single_family,transaction,journal,IV,none,False,False,unknown,1258.0,,3,16
35e9cf817db8c35d9d40580566f6516793f3cc92,True,,"Sea Level Rise, Homeownership, and Residential Real Estate Markets in South Florida",2020.0,10.1080/00330124.2020.1818586,United States,North America,High income,USA,37.1,-95.7,"Florida: Pinellas County and Miami-Dade County (5,000-ft coastal bands)",2004.0,2019.0,single_family,transaction,journal,spatial_lag,"spatial autoregressive (SAR) lag model, distance-band (5,000 ft) weight matrix, estimated in GeoDa",True,True,unknown,135718.0,,4,58
36eac2e74fd054fe7faa7ad4134c3aa524d5616d,True,,Mass appraisal for property tax purposes: approach using global and local spatial regression,2023.0,10.29327/2290393.2.2-2,Brazil,South America,Upper middle income,BRA,-14.2,-51.9,"Florianopolis, Santa Catarina (Centro, Agronomica, Trindade neighbourhoods)",2020.0,2020.0,condo_apartment,listing,journal,spatial_error;GWR,"spatial error model (distance band 525 m) and GWR (fixed Gaussian, 278 m)",False,False,unknown,190.0,,2,14
3777ce734c4a5c9380dfa227ede8503f4f25b44e,True,,"The impact of urban light rail transit on double-story terraced property values in the Greater Kuala Lumpur, Malaysia",2021.0,10.22146/ijg.46302,Malaysia,Asia,Upper middle income,MYS,4.2,101.9,"Greater Kuala Lumpur (Kuala Lumpur, Shah Alam, Gombak)",2009.0,2010.0,single_family,transaction,journal,OLS,none (sub-region dummies CENTRAL/SOUTH),False,True,OLS,1419.0,,1,14
37a309783a11809263623703621db3a26e46597f,True,,The Effect of Central Business District on House Prices in Chengdu Metropolitan Area: A Hedonic Approach,2015.0,10.2991/cas-15.2015.83,China,Asia,Upper middle income,CHN,35.9,104.2,"Chengdu (within the Around-the-city Expressway), Sichuan",2014.0,2014.0,condo_apartment,listing,conference,OLS,none,False,False,unknown,180.0,,2,20
37e8b014df3e5f26ac93ad70c5f3f3c607c04c26,True,,"Estimation of the anticipation effects of the metro project on real estate dynamics in Bogota, Colombia",2025.0,10.5198/jtlu.2025.2593,Colombia,South America,Upper middle income,COL,4.6,-74.3,Bogota,2007.0,2023.0,condo_apartment,listing,journal,OLS,none in reported tables (quasi-experimental DiD with isochrone treatment zones; spatial regressions mentioned but not tabulated in extracted pages),True,False,robust,278393.0,,8,180
387fe0804339369bfc565f8780311edbb5b8a55f,False,"Unit of analysis is the mixed-use project (n = 76 projects from the Sina Commercial Real Estate database), with project-level average residential unit price and office rent regressed on project attributes (hotel presence, city tier, etc.) and a matched-pairs hotel-performance analysis (ADR, RevPAR, occupancy; Table 3). Aggregate project means, commercial/hospitality focus, no dwelling-level hedonic characteristic coefficients.",Do Hotels and Mixed-Use Projects Benefit Each Other? Evidence from China,2017.0,10.61701/789881.21,China,Asia,Upper middle income,CHN,35.9,104.2,multiple Chinese cities (first-tier and others),0.0,0.0,mixed,listing,journal,OLS,none,False,False,unknown,76.0,,0,0
38bde6e6f3fb947d8b6029d64eef6268c93759cc,True,,Marginal prices of improvements made to blocks of flats: empirical evidence from Romania,2016.0,10.3846/1648715X.2015.1121415,Romania,Europe,High income,ROU,45.9,25.0,"Cluj-Napoca, Iasi, Timisoara, Arad",2011.0,2012.0,condo_apartment,transaction,journal,OLS;other,"none (city dummies, intra-city location ring dummies)",False,True,unknown,483.0,,10,92
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,True,,Spatial Discontinuities in Water Rights: Estimating Household Willingness-to-Pay for Unmetered Irrigation Water,2024.0,10.52324/001c.127962,United States,North America,High income,USA,37.1,-95.7,"Weber County, Utah (Ogden)",1999.0,2020.0,single_family,transaction,journal,OLS,boundary (spatial) regression discontinuity design with boundary-segment fixed effects and distance buffers,True,True,clustered,74375.0,,20,152
38d51e7656f94829f9f43fba3ef936f46b613e29,True,,A Hedonic Analysis of the Impact of Marine Aquaculture on Coastal Housing Prices in Maine,2017.0,10.1017/age.2017.19,United States,North America,High income,USA,37.1,-95.7,"Maine coast: Casco Bay, Damariscotta River and Penobscot Bay regions",2012.0,2014.0,single_family,transaction,journal,other,none (municipality fixed effects; 2-mile buffer indices),True,True,robust,8580.0,,6,108
3b145fc34a20579d69b10544f4da1eace43b32a3,True,,Three-dimensional land-use configuration and property prices: A spatially filtered multi-level modelling perspective,2023.0,10.1177/23998083231180213,China,Asia,Upper middle income,CHN,35.9,104.2,"Beijing metropolitan area (old city centre, main urban, inner and outer suburban zones)",2015.0,2015.0,condo_apartment,transaction,journal,other,"random-effects eigenvector spatial filtering (RE-ESF, single level) and spatially filtered multi-level model (SFML, property within street/township)",True,False,unknown,86031.0,,6,204
3b4b454985f862f1a1d6165d8c81255275be3ddb,True,,The effects of park and sea landscape on property value in a tourist city,2022.0,10.3389/fenvs.2022.967094,China,Asia,Upper middle income,CHN,35.9,104.2,"Zhuhai (Xiangshan Park area, Guangdong)",2015.0,2015.0,mixed,listing,journal,OLS,none,False,False,OLS,688.0,,5,75
3b820e938ca4b455736f08f285e1b5bb43f7674a,True,,Determinants of Residential Real Estate Property Prices in Ethiopia: The Case of Bahir Dar City,2024.0,10.11648/j.ijber.20241303.11,Ethiopia,Africa,Low income,ETH,9.1,40.5,Bahir Dar City (Dagmawi Minilik site),2024.0,2024.0,single_family,transaction,journal,OLS,none,False,False,OLS,103.0,,1,12
3bbf88ea5271189e3329337f57932674d7aa341e,True,,The Spatial Dimension of House Prices,2017.0,10.59490/abe.2017.4.1747,Netherlands,Europe,High income,NLD,52.1,5.3,Small city 'A' in the north-eastern Netherlands (Chapter 6),1998.0,2007.0,single_family,transaction,thesis,OLS;GWR,postcode dummies (OLSD) and mixed GWR with property-specific land prices (MGWR),False,True,OLS,5983.0,,3,25
3e2f420e36b96c93f3636cc35296dc7c69414687,True,,Effect of Air Quality Improvements on Apartment Prices in Seoul: Application of Spatial Hedonic Price Model and Interpolation Method,2013.0,10.2457/srs.43.163,South Korea,Asia,High income,KOR,35.9,127.8,Seoul,2008.0,2008.0,condo_apartment,listing,journal,OLS;spatial_error;spatial_lag;IV,"spatial error (ML, GM) and spatial lag (ML, 2SLS) models with distance-band weight matrices 1.7/5/10/20 km",False,False,OLS,500.0,,11,176
3fff47f2ad1427c42ba357bc9b2363011924b07a,True,,Short-term rentals and the housing market: evidence from Portuguese metropolitan areas,2026.0,10.1007/s10258-026-00295-2,Portugal,Europe,High income,PRT,39.4,-8.2,Lisbon and Porto metropolitan areas,2010.0,2017.0,mixed,transaction,journal,FE_panel,"none (postcode / civil-parish fixed effects, clustered SE)",True,True,clustered,185654.0,,30,30
416244dcac790a50e1100858c6071c54dd1650ba,True,,"Analysing location attributes with a hedonic model for apartment prices in Donetsk, Ukraine",2007.0,10.1080/1648715x.2007.9637567,Ukraine,Europe,Lower middle income,UKR,48.4,31.2,Donetsk,2005.0,2005.0,condo_apartment,listing,journal,OLS;spatial_lag;spatial_error,SAR and SEM in Appendix (inverse-square-distance weights); Moran's I reported for OLS,False,False,robust,325.0,,12,238
41a24683a4b966679145f8c822178e61a9a339a4,True,,"A Comparative Hedonic Analysis of Condominium Asking Rents in Bangkok, Phuket, and Pattaya",2026.0,10.56261/built.v24.266592,Thailand,Asia,Upper middle income,THA,15.9,100.9,"Bangkok, Phuket, Pattaya",2026.0,2026.0,condo_apartment,rent,journal,OLS,none (city dummies),False,True,robust,14849.0,,5,22
41c05e4c190bfd812f576bb4bc53a0c147331a7d,True,,Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach,2022.0,10.1007/s11146-022-09915-y,Germany,Europe,High income,DEU,51.2,10.5,Frankfurt am Main,2019.0,2020.0,rental,rent,journal,OLS,none in OLS appendix (coordinates as controls in Panel A); spatial lag/error and ML models used for prediction only,False,False,unknown,9256.0,random_forest;gradient_boosting,2,32
4326e33d5aa8be80e2f1d1ae91adb42331da513d,False,"Aggregate unit of analysis: dependent variable is ln(ZHVI), the Zillow average home value at the ZIP Code x year-month level (and FHFA HPI at ZIP level), in a difference-in-differences design (Amazon Fresh x Post). No property-level hedonic regression and no coefficients on dwelling characteristics; controls are ZIP-level socio-economics (not reported). Tables 2-9 and appendix tables are all ZIP-level DiD or consumption regressions.",E-Grocery and Housing Markets: Evidence from the Amenity Effect of Amazon Fresh as a Digital Amenity,2026.0,10.1007/s11146-026-10055-w,United States,North America,High income,USA,37.1,-95.7,Multiple MSAs with Amazon Fresh service (ZIP Code panel),,,mixed,other,journal,FE_panel,none,True,True,clustered,118517.0,,0,0
43d34a3cb07ebe23b958a009b21ab082b8ff0225,True,,Canals vs. Streams: To What Extent Do Water Quality and Proximity Affect Real Estate Values? A Hedonic Approach Analysis,2016.0,10.3390/w8120577,Italy,Europe,High income,ITA,41.9,12.6,Province of Milan (city of Milan + province),2011.0,2015.0,mixed,listing,journal,OLS;spatial_lag,spatial lag (SL) model,True,True,unknown,10530.0,,5,91
4412b66b7af7dc2e4784f04e96dda07a5d24ef90,True,,Buyers' property asset purchase decisions: an empirical study on the high-end residential property market in Hong Kong,2016.0,10.3846/1648715x.2015.1105322,Hong Kong,Asia,High income,HKG,22.3,114.2,"Hong Kong Island, Southern District (South Horizons, Chi Fu Fa Yuen and related estates)",1992.0,2011.0,condo_apartment,transaction,journal,OLS,none,False,False,unknown,1398.0,,2,19
461f8c8aa68c6a2b5157bc03f6d689991ee3ac64,True,,"Estimating the Effects of Light Rail Transit (LRT) System on the Property Values in the Klang Valley, Malaysia: A Hedonic House Price Approach",2013.0,10.11113/jt.v61.1620,Malaysia,Asia,Upper middle income,MYS,4.2,101.9,"Klang Valley (Kuala Lumpur), within 2 km of Kelana Jaya Line LRT stations",2004.0,2005.0,mixed,transaction,journal,OLS,none,False,False,unknown,1580.0,,2,34
467b5db9559e6802d7f96e2e470749e1440b69fd,True,,Valuing open space in a marshland environment: development alternatives for coastal Georgia,2016.0,10.1017/aae.2016.25,United States,North America,High income,USA,37.1,-95.7,"Chatham County (Savannah), Georgia",2005.0,2011.0,single_family,transaction,journal,SAC,"SARAR (spatial lag + spatial autoregressive error), inverse-distance weights truncated at 200 m, generalized spatial 2SLS (Arraiz et al. 2010)",True,False,robust,11011.0,,3,59
4921c6722d9f1b3252972eb36e559f7e030e6f8a,False,"No hedonic price regression: only zone-level mean price-per-m2 comparisons (t-tests, effect sizes) and surveys; no coefficients on property characteristics.",Revisiting the Proximity Principle with Stakeholder Input: Investigating Property Values and Distance to Urban Green Space in Potchefstroom,2020.0,10.3390/land9070235,South Africa,Africa,Upper middle income,ZAF,-30.6,22.9,Potchefstroom,2015.0,2019.0,single_family,appraisal,journal,,,False,False,,188.0,,0,0
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,True,,Do Foreigners Pay Higher Rents for the Same Quality of Housing in Geneva and Zurich?,2008.0,10.1007/bf03399272,Switzerland,Europe,High income,CHE,46.8,8.2,Geneva and Zurich (cantons),2000.0,2000.0,rental,rent,journal,OLS,none (district fixed effects in -fix models),False,True,unknown,68651.0,,10,152
4a6c4412ae803b09046980401041b08141e48e51,True,,'No Drugs in My Back Yard:' the Ambivalent Reception of Cannabis Retailers,2022.0,10.2139/ssrn.3461820,Netherlands,Europe,High income,NLD,52.1,5.3,"Dutch towns with cannabis retailers (coffeeshops), 201 towns",1999.0,2016.0,mixed,transaction,journal,OLS;FE_panel;IV,none (town / six-digit postcode fixed effects),True,True,clustered,422630.0,,14,40
4c31e259cf5625db8bd0cbbcae78c68fed2c8164,True,,Text-augmented house valuation: using embedding vectors and SHAP values,2026.0,10.36253/aestim-19824,South Korea,Asia,High income,KOR,35.9,127.8,Seongdong-gu (Seoul) and Gangjin-gun (Jeonnam Province),2024.0,2024.0,single_family,appraisal,journal,OLS,none,False,False,unknown,1670.0,"sentence embeddings (paraphrase-mpnet-base-v2, SBERT);PCA of embeddings;XGBoost;SHAP",4,78
4d2cf36586abe5a8dcb4cd171a95a31095559520,True,,The influence of urban green and recreational areas on the price of housing in Zagreb,2024.0,10.15201/hungeobull.73.3.3,Croatia,Europe,High income,HRV,45.1,15.2,Zagreb,2023.0,2023.0,condo_apartment,listing,journal,GWR,"GWR (Gaussian kernel, 120 nearest neighbours)",False,False,unknown,2314.0,,1,20
4d32787a617d281fb36974fdcd341ff661cf2fe5,True,,Housing market differentiation: the cases of Yenimahalle and Cankaya in Ankara,2015.0,10.3846/1648715X.2014.1000429,Turkey,Asia,Upper middle income,TUR,38.96,35.2,Ankara (Cankaya and Yenimahalle districts),2011.0,2011.0,condo_apartment,listing,journal,OLS,submarket (cluster) dummies in overall model; separate regressions per cluster,False,True,OLS,1733.0,,9,25
4e466a17fb2cf5a4adc290cec91b0f1aaedbabd1,True,,Research on the Influencing Factors of Rental House Prices,2024.0,10.62051/cs0pd728,China,Asia,Upper middle income,CHN,35.9,104.2,"Guangzhou, Guangdong",2020.0,2020.0,rental,rent,conference,OLS,none,False,False,OLS,11128.0,,2,8
4e94c698b9b6217c36e2e8842148142f5bccfb36,True,,A re-assessment of house price indices: evidence from the Spanish market,2019.0,10.3846/ijspm.2019.6366,Spain,Europe,High income,ESP,40.5,-3.7,Alicante province (Valencian Community),2010.0,2010.0,unknown,listing,journal,OLS,none (urban-dependence level only; no geo-references),False,False,unknown,596170.0,,1,33
4ecf623f40ce01fde8d4ac0ee88291986f7a72fa,False,"No hedonic regression: the study compares mean municipal valuations and estimated market values per m2 (South African Rand/m2) across three distance zones around five urban green spaces in Potchefstroom (n=188) using dependent t-tests, ANOVA and Kruskal-Wallis tests (Tables 3-5). No regression coefficients on property characteristics or on distance to green space are estimated.",Economic Assessment of South African Urban Green Spaces Using the Proximity Principle: Municipal Valuation vs. Market Value,2021.0,10.17645/up.v6i4.4407,South Africa,Africa,Upper middle income,ZAF,-30.6,22.9,"Potchefstroom, North West Province",2019.0,2020.0,single_family,appraisal,journal,other,zone comparison (distance zones 1-3),False,False,unknown,188.0,,0,0
4f4475636117754066fcc0578aecfcf69e646566,True,,Modelling the impact of wind farms on house prices in the UK,2008.0,10.3846/1648-715x.2008.12.251-269,United Kingdom,Europe,High income,GBR,55.4,-3.4,"Cornwall (St Breock / Bears Down area, houses within half a mile of a 16-turbine wind farm)",2000.0,2007.0,single_family,transaction,journal,OLS,none (postcode location dummies),True,True,OLS,199.0,,2,32
5170d50eab56ddf40c03eaf3e11552023cf9142d,False,"Hedonic (restricted/unrestricted) and hybrid models are estimated on Sydney house sales 1971-2011 but no characteristic coefficients are printed anywhere in the paper; footnote 7 states 'All model estimates are available upon request from the authors'. Only summary statistics, goodness-of-fit and index growth-rate tables are reported.",House Price Models for Banking and Insurance Applications: The Impact of Property Characteristics,2017.0,10.1515/apjri-2017-0003,Australia,Oceania,High income,AUS,-25.3,133.8,Sydney Statistical Division,1971.0,2011.0,single_family,transaction,journal,OLS;other,postcode dummies,True,True,unknown,757150.0,,0,0
51b11fac87d973139852a88a8c12a9cdbf87b57a,True,,Hedonic Analysis of Forest Pest Invasion: the Case of Emerald Ash Borer,2019.0,10.3390/f10090820,United States,North America,High income,USA,37.1,-95.7,"Milwaukee, Wisconsin (northern 10 zip codes)",2008.0,2015.0,single_family,transaction,journal,OLS,none (zip-code spatial fixed effects),True,True,unknown,4502.0,,16,116
5242a8699dbfd95d3c698daaa18f7bab00d59c97,True,,The impact of luxury housing on neighborhood housing prices: an application of the spatial difference-in-differences method,2020.0,10.3846/ijspm.2020.13649,Taiwan,Asia,High income,TWN,23.7,121.0,Taipei City,2008.0,2014.0,condo_apartment,transaction,journal,OLS;spatial_lag;spatial_error,spatial lag and spatial error models (ML) with location fixed effects,False,True,unknown,12771.0,,6,84
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,True,,Geospatial Heterogeneity in Monetary Value of Proximity to Waterfront Ecosystem Services in the Gulf of Mexico,2021.0,10.3390/w13172401,United States,North America,High income,USA,37.1,-95.7,Coastal counties of Mississippi and Alabama (Gulf of Mexico),2010.0,2010.0,mixed,appraisal,journal,OLS;GWR,geographically weighted regression (adaptive bandwidth 533 m),False,False,robust,620.0,,2,42
52cbefc12720084fe56091430bf37e9fbeba96b9,True,,Do 5G cell phone towers decrease house prices? Evidence from Warsaw,2024.0,10.1007/s10901-024-10144-3,Poland,Europe,High income,POL,51.9,19.1,Warsaw (Miasteczko Wilanow estate),2016.0,2021.0,condo_apartment,transaction,journal,OLS;other,none (single estate; CEM matching in Mod. 4-6),True,False,unknown,1825.0,,9,84
53a228745dc9a32b1002f59f1be59cdca85e461e,False,"Data are not an empirical sample: the paper states (Section 2.1, p. 3) that 'the report obtained 3,000 simulated valid data points by adding random noise'; the provenance of any underlying real listings is not documented. Conference proceeding (student paper). Flag for human review: Tables 4-5 (pp. 7-8) do print OLS coefficients with SE and p-values on log price per m2 (10,000 yuan/m2) for school district (0.273, SE 0.011), sea view (0.452, 0.032), subway (-0.014, 0.018), elevator (0.052, 0.029), renovation (0.033, 0.022), age-band dummies, south orientation (0.009, 0.010) and area in m2 (0.001, SE printed as 0), plus district dummies, but they are estimated on simulated data.",Variance analysis and linear regression: Exploring the impact of location factors on the average logarithmic price of pre-owned housing in Shenzhen,2024.0,10.54254/2753-8818/39/20240598,China,Asia,Upper middle income,CHN,35.9,104.2,Shenzhen (10 central administrative districts),,,condo_apartment,listing,conference,OLS,none (district dummies),False,True,OLS,3000.0,,0,0
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,True,,Comparing automated valuation models for real estate assessment in the Santiago Metropolitan Region: A study on machine learning algorithms and hedonic pricing with spatial adjustments,2025.0,10.1371/journal.pone.0318701,Chile,South America,High income,CHL,-35.7,-71.5,Santiago Metropolitan Region,2020.0,2020.0,mixed,listing,journal,OLS;spatial_lag,SAR / spatial lag with k-nearest-neighbour weights (rho = 0.4271),False,False,unknown,52039.0,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2,64
53f863bd54970307af93c0ba10a947b3b65b890a,True,,The impact of Energy Performance Certificate level on house listing prices. First evidence from Italian real estate,2014.0,10.13128/aestimum-15459,Italy,Europe,High income,ITA,41.9,12.6,Turin,2012.0,2012.0,condo_apartment,listing,journal,OLS,microzone dummies (40 zones),False,True,OLS,577.0,,4,34
549587ac03dcb9d550c7fe68da027277dd876b12,True,,A divide-and-conquer approach for spatio-temporal analysis of large house price data from Greater London,2024.0,10.1007/s10479-025-06889-x,United Kingdom,Europe,High income,GBR,55.4,-3.4,Greater London (983 MSOAs),2011.0,2019.0,mixed,transaction,journal,other,Bayesian spatio-temporal Gaussian process (separable Matern/exponential space-time random effect) estimated by divide-and-conquer with Wasserstein barycenter (D&C-STBD),False,False,unknown,651202.0,,1,13
54da27518406c538ad01d44349b80f8a974bfe46,True,,"Economic effects of air quality on housing prices: evidence from Beijing, China",2024.0,10.1007/s10901-023-10108-z,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing,2013.0,2019.0,condo_apartment,transaction,journal,OLS;FE_panel;IV;quantile,none (community fixed effects),True,True,clustered,333269.0,,21,145
58a9ab2513035056fdc6d56cafc04ae9d61a0955,True,,Willing to pay more for high-quality schools? A hedonic pricing and propensity score matching approach,2018.0,10.14246/irspsd.6.1_45,China,Asia,Upper middle income,CHN,35.9,104.2,"Xiamen Island (Siming and Huli districts), Fujian",2014.0,2014.0,condo_apartment,listing,journal,OLS;other,none,False,False,unknown,1250.0,,6,72
59a1872eca8f8697a739527375ba1a22843bf5bd,False,"No dwelling-level hedonic coefficients are printed. A hedonic (semi-log) model is only used internally to construct quarterly standard-house price indices (Chang et al. 2008 method) by housing tier and city; the reported regressions (Tables 14, 16, 18) are time-series regressions of the quarterly price index (32 observations) on macroeconomic variables (CPI, construction cost index, M2, national income, mortgage rate, TAIEX). Aggregate unit of analysis (index), no characteristic implicit prices.",The housing price dynamics and macroeconomic factors: Evidence of Taiwan housing market,2025.0,10.3846/ijspm.2025.24610,Taiwan,Asia,High income,TWN,23.7,121.0,"Taipei, Taichung, Kaohsiung",2014.0,2022.0,condo_apartment,transaction,journal,OLS,none,False,False,unknown,32.0,,0,0
5bcd886348a12f52aa055354a9647ba5c4fa64c4,True,,Giving Eyes to Automated Valuation Models: Computer Vision Assessment of Interior Home Condition,2026.0,10.1007/s11146-026-10071-w,Norway,Europe,High income,NOR,60.5,8.5,Oslo,2022.0,2023.0,condo_apartment,transaction,journal,OLS,none (district or postal-code fixed effects),True,True,unknown,15702.0,CNN image classification (room type and 1-5 condition per room);XGBoost AVM with SHAP (not extracted),14,180
5bed224cb10ce261eda55857ae903598b9f96697,True,,"Investigation of the impact of railways on housing values; the case of Istanbul, Turkey",2019.0,10.2495/tdi-v3-n4-295-305,Turkey,Asia,Upper middle income,TUR,38.96,35.2,"Istanbul (Esenler-Kirazli metro line, 5 stations, European side)",2017.0,2017.0,condo_apartment,listing,journal,OLS,none,False,False,OLS,665.0,,1,11
5bf64585206ad7e7f4dd7182eea5bcbb352319dd,False,"No hedonic characteristic coefficients are printed in the article: the SW2SLS spatial hedonic estimates (33 house characteristics, by year 2007-2012 and by area) are relegated to Table IV of an online Supplementary Appendix 3 that is not part of the PDF. The printed Tables 2-3 are aggregate relative-price (ripple-effect) regressions between quality-adjusted area price series (log p_Orihuela on log p_coast / log p_inland) and Table 1 reports Moran's I; these are not property-level characteristic coefficients.","Ripple effect on housing prices. Evidence from tourist markets in Alicante, Spain",2017.0,10.3846/1648715x.2016.1241192,Spain,Europe,High income,ESP,40.5,-3.7,"Vega Baja county, Alicante (Orihuela city, coastal and inland areas)",2007.0,2012.0,mixed,listing,journal,spatial_lag;spatial_error;IV,"SAR/SEM via spatially weighted 2SLS, contiguity and distance weight matrices",False,False,unknown,,,0,0
5cf2ca5773ec64d2d8be794899e97064def914d5,True,,"The effects of jobs, amenities, and locations on housing submarkets in Xiamen City, China",2022.0,10.1007/s10901-022-09984-8,China,Asia,Upper middle income,CHN,35.9,104.2,Xiamen,2016.0,2017.0,condo_apartment,listing,journal,OLS;spatial_error;spatial_lag,"SEM (3 submarkets) and SLM (outer-district rental), 4-nearest-neighbour weights",True,False,unknown,4113.0,,8,197
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,True,,The value capture potential of the Lisbon Subway,2012.0,10.5198/jtlu.v5i1.251,Portugal,Europe,High income,PRT,39.4,-8.2,Lisbon (municipality / metropolitan area),2007.0,2007.0,mixed,listing,journal,spatial_lag,spatial lag of log price (500 m influence area),False,False,unknown,8742.0,,1,16
602e1fb4b1e820fd13056357b14a38759c9354ab,True,,"Metro station inauguration, housing prices, and transportation accessibility: Tehran case study",2021.0,10.5198/jtlu.2021.1622,Iran,Asia,Lower middle income,IRN,32.4,53.7,Tehran,2010.0,2018.0,mixed,transaction,journal,OLS,none (postal-code region fixed effects; difference-in-differences),True,True,unknown,833282.0,,33,144
61571b403ee0b92394b214f7249ffc6c6a95a4dc,False,"Prediction-only paper: describes the Norwegian tax-valuation hedonic model (log price per m2 on size, age, housing type, year dummies and geographic calculation groups) but the PDF reports only prediction-performance tables (Tables 1-3: absolute errors, R2) and tax-revenue/distributional tables (Tables 4-5); no hedonic coefficient estimates are printed (coefficient appendix tables, if any, are in an online appendix not included).",Improving housing valuation for taxation: the Norwegian case,2025.0,10.1007/s10797-025-09928-2,Norway,Europe,High income,NOR,60.5,8.5,Norway (national),2011.0,2020.0,mixed,transaction,journal,OLS,geographic calculation groups (k-means-type clustering of basic statistical units),True,True,unknown,0.0,clustering (machine learning grouping of geographical units),0,0
617738a89ff272112e6f8804b981aa1981f5a232,True,,Semi-Parametric Interpolations of Residential Location Values: Using Housing Price Data to Generate Balanced Panels,2014.0,10.20955/wp.2014.050,United States,North America,High income,USA,37.1,-95.7,"Denver metropolitan area, Colorado (Adams, Denver, Douglas, Arapahoe, Jefferson counties)",2003.0,2010.0,single_family,transaction,working_paper,OLS;other,OLS with quadratic latitude/longitude polynomial and county dummies; Robinson's semi-parametric method (local polynomial regression on location),True,True,unknown,326744.0,,2,20
620cbd7217ca28bcea726920009e42496a17ea8b,True,,"The Impact of Brownfields on Residential Property Values in Cincinnati, Ohio: A Spatial Hedonic Approach",2012.0,10.68479/001c.7941,United States,North America,High income,USA,37.1,-95.7,"Cincinnati, Ohio (Hamilton County; properties within 1,000 ft of a brownfield, mostly Mill Creek corridor)",2009.0,2009.0,single_family,appraisal,journal,OLS;spatial_lag;spatial_error,SAR and SEM by maximum likelihood (row-standardised W),False,False,unknown,1607.0,,3,45
63065c2cad027c9578aace5fb84b3bd4ba000e2b,True,,Hurricane-Induced Discharges from Superfund Sites: A Hedonic Price Analysis of Real Estate Market Responses,2024.0,10.3368/le.101.1.030423-0019r1,United States,North America,High income,USA,37.1,-95.7,"Harris County (Houston), Texas",2013.0,2019.0,single_family,transaction,journal,OLS,"census-tract (3/4-digit) spatial fixed effects; distance-decay (negative exponential, Gaussian) transformations of distance to site",True,True,clustered,5162.0,,16,54
63d3e41634a76fe68a3edb5f056b73b7098ad523,True,,The Impact of Water Body Restoration on the Sales and Rental Markets in Beijing,2023.0,10.3368/le.99.4.041322-0030r1,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing,2015.0,2018.0,condo_apartment,transaction,journal,OLS,"none (BOWB, ring-road and district-by-year fixed effects)",True,True,clustered,84547.0,,32,64
63f327f2d844daf6ba970bc6d5f6ab1fc9861dfd,True,,"External Factors, Housing Values, and Rents: Evidence from Survey Data",2000.0,10.1080/2167034x.2003.12461361,Turkey,Asia,Upper middle income,TUR,38.96,35.2,Istanbul,1992.0,1992.0,mixed,appraisal,conference,OLS,none (district dummies),False,True,unknown,795.0,,2,43
6663c2076db87ffe9baf2162abc65f7ffa450ab0,False,"Controlled interrupted time series on log closing price (Table 2, p.15) prints only the ITS terms (time, group, level, trend, SCS level/trend) as exponentiated ratios with 95% CI; housing and neighbourhood attribute coefficients (bathrooms, bedrooms, floor size, distance to SCS, proximity scores) are included as controls but never printed. No characteristic coefficients available.","Evaluating the effects of supervised consumption sites on housing prices in Montreal, Canada using interrupted time series and hedonic price models",2024.0,10.1016/j.dadr.2024.100242,Canada,North America,High income,CAN,56.1,-106.3,"Montreal, Quebec",2014.0,2022.0,condo_apartment,transaction,working_paper,OLS,spatio-temporal price lag (Dube & Legros 2013),False,False,unknown,6903.0,,0,0
66b74975968370c75371207845d963de2413a23e,True,,Does urban centrality influence residential prices? An analysis for the Barcelona Metropolitan Area,2017.0,10.7764/rdlc.16.1.57,Spain,Europe,High income,ESP,40.5,-3.7,Barcelona Metropolitan Region (137 municipalities),2014.0,2014.0,condo_apartment,listing,journal,OLS,none,False,False,OLS,3479.0,,1,14
670518142f78514470ad2ea85cc37f0ccb4483aa,True,,"Low-emission zones, modes of transport and house prices: evidence from Berlin's commuter belt",2022.0,10.1007/s11116-022-10295-8,Germany,Europe,High income,DEU,51.2,10.5,Brandenburg counties bordering Berlin (Berlin commuter belt),2008.0,2011.0,single_family,listing,journal,OLS,none (municipality fixed effects; spatial DiD by walking-distance bands),True,True,clustered,129521.0,,10,45
670783d3e4613f6e96cb818330755422772653ef,True,,The impact of energy certification on the real estate market: an analysis using Big Data and hedonic pricing,2026.0,10.36253/aestim-19711,Italy,Europe,High income,ITA,41.9,12.6,Padua (Padova),2022.0,2023.0,condo_apartment,listing,journal,OLS,"urban zone dummies (10 zones, reference Torre/Mortise/Ponte di Brenta)",False,True,unknown,1738.0,,7,58
67d132eca470e26b7a8c41462ca1252d056a93bb,True,,"Spatial and Social Media Data Analytics of Housing Prices in Shenzhen, China",2016.0,10.1371/journal.pone.0164553,China,Asia,Upper middle income,CHN,35.9,104.2,Shenzhen,2015.0,2015.0,condo_apartment,transaction,journal,OLS;GWR,GWR (bandwidth 0.337) in addition to global OLS,False,False,unknown,25323.0,social media check-in hot-spot analysis (Getis-Ord Gi*),2,30
69288e963b8055b19e0fd077000b14eb34270ae1,True,,The effects of transaction hotspots and flipping hotspots on housing prices,2024.0,10.3846/ijspm.2024.20899,Taiwan,Asia,High income,TWN,23.7,121.0,Taipei City,2012.0,2021.0,unknown,transaction,journal,OLS;spatial_lag;spatial_error;quantile,spatial lag / spatial error / spatial quantile regression with spatial lag term; administrative district dummies,True,True,unknown,62140.0,,8,80
6a582c18a0b55c4939a0e4812ae293fd34b678de,True,,Capitalization of Public School Quality into Housing Prices: An Empirical Analysis Based on School District Housing for Public Primary Schools in Shanghai,2018.0,10.4236/chnstd.2018.74025,China,Asia,Upper middle income,CHN,35.9,104.2,Shanghai,0.0,0.0,condo_apartment,listing,journal,IV,none,False,False,OLS,344.0,,3,27
6c0fa6707be0f8c5edd0d4088f7dfb356412099f,True,,"The demand for air quality: evidence from the housing market in Bogota, Colombia",2018.0,10.1017/s1355770x18000050,Colombia,South America,Upper middle income,COL,4.6,-74.3,Bogota D.C.,2011.0,2011.0,mixed,rent,journal,other,"locality (spatial) fixed effects; frontier model with heteroskedastic error (sigma2_mu function of PM10, strata, strata*PM10, spatial FE)",False,True,unknown,6061.0,,4,4
6c554bbc30f053c6546ae8df71b70b126d3f4178,True,,"Evaluating the Impact of Urban Blue Space Accessibility on Housing Price: A Spatial Quantile Regression Approach Applied in Changsha, China",2021.0,10.3389/fenvs.2021.696626,China,Asia,Upper middle income,CHN,35.9,104.2,Changsha (Hunan),2019.0,2019.0,condo_apartment,transaction,journal,OLS;quantile;IV;spatial_lag,"spatial lag (inverse-distance weights, 3.71 km bandwidth) instrumented via 2SLS; spatial quantile regression (McMillen 2012)",False,False,unknown,,,20,340
6e4be5daf59355440452370cc31893fbd8320793,False,"Repeat-sales difference-in-differences model (Tables 3-6): dependent variable is the change in log price between two sales of the same property; regressors are a time-bracket indicator (B) and its interactions with property type, rural/coastal location, flood-defence construction (B*D) and defence design variables. Property characteristics are differenced out and enter only as interactions; no hedonic price-level regression with characteristic coefficients. Flagged for human review: the flood-defence treatment effect (urban +12.6% to +16.7%, rural -0.8% to -5.0%) is an environmental (flood_risk) effect but not a hedonic coefficient.",Assessing the Economic Benefits of Flood Defenses: A Repeat-Sales Approach,2018.0,10.1111/risa.13136,United Kingdom,Europe,High income,GBR,55.4,-3.4,England,1995.0,2014.0,mixed,transaction,journal,other,repeat-sales DiD with county fixed effects,True,True,robust,7217966.0,,0,0
6e83e47fe67686f424f9c68dca8dac1370a653d3,True,,"An Empirical Analysis of the Relationship Between Shopping Malls and Surrounding Property Prices: Evidence from Xi'an, China",2024.0,10.54254/2754-1169/94/2024ox0141,China,Asia,Upper middle income,CHN,35.9,104.2,"Weiyang District, Xi'an, Shaanxi",2017.0,2021.0,condo_apartment,transaction,conference,OLS,none,False,False,unknown,10175.0,,3,35
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,True,,The Impact of the Youth Housing Loan Subsidy Policy on Housing Prices: Evidence from New Taipei City,2026.0,10.5296/ber.v16i4.24024,Taiwan,Asia,High income,TWN,23.7,121.0,New Taipei City,2021.0,2024.0,mixed,transaction,journal,OLS,none (price-tier area dummies),True,True,robust,108671.0,,4,24
7059eb726206d6598f1ef88ae9a43a35a98c6937,True,,The relationship of single-family detached house prices with neighborhood walkability and disaster risk,2023.0,10.1371/journal.pone.0292657,Japan,Asia,High income,JPN,36.2,138.3,Tokyo Metropolitan Area (central cities and other cities),2015.0,2020.0,single_family,transaction,journal,quantile,none,True,False,unknown,71289.0,,5,115
71977f92d0454f114374d8e7935fc5debd79713d,False,"Aggregate unit of analysis: regression of median house value of California census block groups (1990 California Housing dataset, n=20,433 blocks) on block-level medians/totals (longitude, latitude, housing median age, total rooms, total bedrooms, population, households, median income). No individual dwelling prices or characteristic coefficients.",Predicting Housing Price Using Regression Analysis: A Study Based on California Housing Price,2025.0,10.54254/2753-8818/2025.23005,United States,North America,High income,USA,37.1,-95.7,California,1990.0,1990.0,unknown,other (block-group median house value),conference,OLS,none,False,False,unknown,20433.0,,0,0
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,True,,The Effect of War on Spatial Differentiation of Real Estate Values and Urban Disorder in the Damascus Metropolitan Area,2024.0,10.3390/urbansci8040183,Syria,,,,,,Damascus metropolitan area (Damascus and Rural Damascus Governorates),2010.0,2022.0,mixed,transaction,journal,OLS,"none (governorate split samples, war-damage dummies)",True,True,unknown,2411.0,,4,52
721bde276de0a5af885925a9444c628cfce6d18a,True,,The impacts of light rail on residential property values in a non-zoning city: A new test on the Houston METRORail transit line,2019.0,10.5198/jtlu.2019.1310,United States,North America,High income,USA,37.1,-95.7,"Houston (Harris County), Texas",1982.0,2010.0,single_family,transaction,journal,OLS;other;spatial_lag;spatial_error,multilevel regression (TAZ level 2) and spatial lag / spatial error models on a 5% random sample,False,False,unknown,384368.0,,6,120
74099967a079fff42f0df3135c0f69cc4e059615,True,,A Quantitative Examination of Housing Price Determinants in Yogyakarta,2025.0,10.23917/determinasi.v3i4.502,Indonesia,Asia,Upper middle income,IDN,-0.8,113.9,Yogyakarta,,,single_family,listing,journal,OLS,none,False,False,OLS,1713.0,,1,5
755578f10943061d8e5adfd02909b14166725d76,True,,Influence of the Urban Green Spaces of Seville (Spain) on Housing Prices through the Hedonic Assessment Methodology and Geospatial Analysis,2022.0,10.3390/su142416613,Spain,Europe,High income,ESP,40.5,-3.7,Seville,2022.0,2022.0,unknown,listing,journal,OLS,none (ordinary kriging used separately for price surface),False,False,unknown,1000.0,,2,8
757bd683e867096bd3de6214d8e05c02d711dbcc,False,"Aggregate unit of analysis: regressions use Seoul dong (sub-district) level average transaction prices by housing type (multi-unit, single-unit, apartment) as the dependent variable, with facility counts per 10,000 population and park-area share at the dong level as the only regressors (Tables 6-8, pp.9-11). No dwelling-level observations and no structural characteristics; no standard errors or t-statistics printed (stars only). Not a property-level hedonic regression.",Effects of Educational and Cultural Facilities on Housing Prices in Seoul from an Accessibility Perspective,2021.0,10.11628/ksppe.2021.24.5.529,South Korea,Asia,High income,KOR,35.9,127.8,Seoul,,,mixed,transaction,journal,OLS;spatial_lag;spatial_error,SLM and SEM at dong level,False,False,unknown,,,0,0
75ba68147bf6e34f9b631b70a8cea636eda11e65,True,,Use of Geographically Weighted Regression (GWR) Method to Estimate the Effects of Location Attributes on the Residential Property Values,2017.0,10.22146/ijg.27036,Malaysia,Asia,Upper middle income,MYS,4.2,101.9,Kuala Lumpur,2010.0,2010.0,single_family,transaction,journal,OLS;GWR,GWR,False,False,unknown,4393.0,,2,30
75d0711aebd70fde400d1a6a49265e443bbe1884,True,,"The value of environmental (dis)amenities in the urban housing market: Evidence from Khulna, Bangladesh",2020.0,10.1016/j.jum.2020.02.001,Bangladesh,Asia,Lower middle income,BGD,23.7,90.4,Khulna city (3 planned + 5 unplanned residential blocks),,,rental,rent,journal,OLS,,False,False,unknown,201.0,,3,42
7670a6d2dc2183fc23719395205238727f178317,True,,Spatial Estimation of the Impact of Airport Noise on Residential Housing Prices,2008.0,10.1007/bf03399267,Switzerland,Europe,High income,CHE,46.8,8.2,Canton of Zurich (Zurich Airport area),1995.0,2005.0,single_family,transaction,journal,spatial_error;OLS,"ML spatial autoregressive error model (SAR error); W: Euclidean cut-off 300 m (Models 1,2,6), 600 m (Model 4), 4 nearest neighbours (Model 5)",True,False,unknown,3737.0,,6,217
78349a30196c9ee010a5b6087b25ddd2eb8a9b3d,True,,Economic Evaluation of the Indoor Environmental Quality of Buildings: The Noise Pollution Effects on Housing Prices in the City of Bari (Italy),2021.0,10.3390/buildings11050213,Italy,Europe,High income,ITA,41.9,12.6,"Bari (Apulia), four OMI municipal areas",2017.0,2019.0,condo_apartment,transaction,journal,ML_marginal,separate models per OMI area,False,False,unknown,800.0,genetic algorithm (EPR-MOGA evolutionary polynomial regression),4,38
784bd147866d1ec15bbfa3c42d3c2fc6a9ac3192,True,,The economic value of sustainability. Real estate market and energy performance of homes,2023.0,10.48264/vvsiev-20233402,Italy,Europe,High income,ITA,41.9,12.6,"Padua, Mestre (Venice), Bergamo",2022.0,2023.0,mixed,listing,journal,OLS,none (ordinal OMI zone variable),False,False,unknown,901.0,,6,32
78763be000cac6c28c0629b4c2e5fffb2f7f7fde,True,,Factors Affecting Spatial Autocorrelation in Residential Property Prices,2022.0,10.3390/land11060931,Hong Kong,Asia,High income,HKG,22.3,114.2,Hong Kong Island,1998.0,2009.0,condo_apartment,transaction,journal,OLS;spatial_lag,"lagged-price spatial autoregressive terms (vertical within-building and horizontal inverse-distance weights), estimated by OLS",True,True,unknown,167418.0,,5,45
79a14cd6c47cfe07a6fd907132f2ed86427b4831,True,,"Are Homeowners Willing to Pay More for Access to Parks? Evidence from a Spatial Hedonic Study of the Cincinnati, Ohio, USA Park System",2018.0,10.68479/001c.3851,United States,North America,High income,USA,37.1,-95.7,"City of Cincinnati, Ohio",,,single_family,appraisal,journal,spatial_error;other,"Bayesian spatial Durbin error model (SDEM, contiguity W, lambda = 0.388) and spatial lag of X (SLX) model; quadratic lat/long controls",False,False,unknown,36167.0,,18,86
79ef2b5c97af212a2651b0df761a0e38797c7254,False,"Aggregate unit of analysis: the dependent variable is the suburb median house price (Kaggle dataset of 421 Sydney suburbs, 2020-2021; 300 suburbs retained) and all regressors are suburb-level ratings (median weekly rent, traffic, public transport, nature, noise, family/pet friendliness, safety) -- no dwelling-level prices or property characteristics. Table 2 (p.4) reports B, SE, Beta, t, p for X1-X9.",Investigation Upon Factors Contributing to Housing Price Variations-Specifically Sydney for Reference,2024.0,10.62051/4r609702,Australia,Oceania,High income,AUS,-25.3,133.8,Sydney urban suburbs,2020.0,2021.0,unknown,listing,conference,OLS,none,False,False,OLS,300.0,,0,0
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,True,,Hedonic Modeling for a Growing Housing Market: Valuation of Apartments in Complexes,2014.0,10.5539/ijef.v6n3p188,Turkey,Asia,Upper middle income,TUR,38.96,35.2,"Metropolitan Izmit (Kocaeli): Izmit, Kartepe, Basiskele",,,condo_apartment,transaction,journal,OLS,none (municipality and complex dummies),False,False,robust,405.0,,4,48
7b29c36e620db272e042f7b9f343c676a2038678,True,,Interpretable Machine Learning for Real Estate Market Analysis,2022.0,10.2139/ssrn.3835931,Germany,Europe,High income,DEU,51.2,10.5,Frankfurt am Main,2013.0,2019.0,rental,rent,journal,OLS;spatial_lag;other,SAR (spatial lag); coordinates as controls in all models,True,False,OLS,52966.0,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,3,60
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,True,,Approach to hedonic model and analyzing factors affecting real estate prices in Hanoi,2022.0,10.22271/maths.2022.v7.i4b.849,Vietnam,Asia,Lower middle income,VNM,14.1,108.3,"Hanoi (6 main streets: Nguyen Chi Thanh, Tran Duy Hung, Nguyen Trai, Tay Son, Huynh Thuc Khang, Truong Chinh)",2021.0,2021.0,unknown,transaction,journal,OLS,none,False,False,robust,240.0,,6,45
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,True,,Net benefits of urban slums redevelopment policies on the value of adjacent residential property,2021.0,10.3846/ijspm.2021.14570,Pakistan,Asia,Lower middle income,PAK,30.4,69.3,Islamabad,,,single_family,rent,journal,OLS,none,False,False,unknown,504.0,,6,84
7e996f814b72e80b4de3f1e836fe30324b1e2912,False,"Repeat-sales model (GLS on log price change between successive sales of the same home, Larimer and Boulder counties CO, 1998-2011): structural characteristics are differenced out; the only reported coefficients are year-specific host-tree-proximity (within 0.1 km) effects, a differenced wildfire-within-5km/5yr indicator, year dummies and an age-depreciation term (Tables 6, 7, 8, 12, 13). No cross-sectional hedonic regression with property-characteristic coefficients. Flag for human review if repeat-sales environmental effects are to be included.",Hedonic Valuation with Translating Amenities: Mountain Pine Beetles and Host Trees in the Colorado Front Range,2014.0,10.1007/s10640-014-9856-y,United States,North America,High income,USA,37.1,-95.7,"Larimer and Boulder counties, Colorado Front Range (control: Spokane WA)",1998.0,2011.0,single_family,transaction,journal,other,none (area-specific intercepts and trends),True,True,unknown,0.0,,0,0
7f206890031d1d54ba82515e526e51ef8c34c412,False,"No printed characteristic coefficients: the paper fits a structured additive distributional regression (GAMLSS-type, batchwise backfitting with regional clustering) to >1 million German apartment asking prices per m2, but reports covariate effects only graphically (effect plots, county maps) and in Table 1 (out-of-sample prediction accuracy); Tables 2-3 are descriptive statistics only. Methodological/predictive study; keep qualitatively (AI/ML section).",A Parsimonious Hedonic Distributional Regression Model for Large Data with Heterogeneous Covariate Effects,2025.0,10.17713/ajs.v54i2.1904,Germany,Europe,High income,DEU,51.2,10.5,"Germany (national, county-level clusters)",2016.0,2022.0,condo_apartment,listing,journal,ML_marginal;other,model-based regional clustering of county effects; structured additive distributional regression (location and scale),False,True,unknown,0.0,structured additive distributional regression (GAMLSS);batchwise backfitting;boosting-type variable selection;model-based clustering,0,0
7f45f70c2c2271b7539c0915321311343666b384,True,,The Grass Isn't Always Greener: How Crime Influences Property Values Near Urban Greenlines,2026.0,10.1007/s11146-025-10026-7,United States,North America,High income,USA,37.1,-95.7,"Memphis / Shelby County, Tennessee",2006.0,2022.0,mixed,transaction,journal,OLS,census-tract fixed effects (no spatial econometrics),True,True,unknown,18411.0,,22,180
80c7a3882a0d8e30de9d0f2d3d4f1558e6df1c50,False,"Unit of analysis is the housing block (residential project/community): the dependent variable is the natural log of the block-level average transaction price per m2 in 2005 and 2012 (Tables 5-6, stepwise OLS with SE, t and p). Aggregate project means rather than individual dwelling prices; excluded from the coefficient synthesis per protocol (note: coefficients are printed with SEs and could be recovered if block-level studies are later admitted).",The Transitional Spatial Pattern of Housing Prices in Beijing: Factors and Implications,2014.0,10.14246/irspsd.2.3_46,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing,2005.0,2012.0,condo_apartment,transaction,journal,OLS,none in regression (Moran's I / LISA exploratory),False,False,OLS,,,0,0
819ec939f0241cca8513d3a72e45a56254da737d,True,,House Prices and Flood Risk Exposure: An Integration of Hedonic Property Model and Spatial Econometric Analysis,2022.0,10.1007/s11146-022-09930-z,Vietnam,Asia,Lower middle income,VNM,14.1,108.3,Ho Chi Minh City (District 7),2017.0,2018.0,mixed,listing,journal,OLS;spatial_error;spatial_lag;SAC;other,"SEM, SAR, SLX, SDM, SDEM, SAC (same inverse-distance W for lag and error); SAC preferred by AIC/BIC",False,False,unknown,2367.0,,14,231
828367334a6cb48f8254ab88d9172664e3afd7a2,True,,World heritage designation and property: the impact of preservation on the price of historic assets,2022.0,10.3846/ijspm.2022.18156,Israel,Asia,High income,ISR,31.0,34.9,"Tel Aviv, White City UNESCO World Heritage site",1998.0,2009.0,mixed,transaction,journal,OLS,none,True,False,unknown,300.0,,9,68
844f3013b415b6de89430c28be2c24c13f35196d,False,"Aggregate unit of analysis: 106 ""ordinary commodity housing"" projects (housing estates) in Xiamen, with the project average (listed) price as dependent variable and project-level attributes (property management fee, households, green ratio, FAR); data from SouFun website and newspaper advertisements. Not individual dwelling prices.",Using GIS and Hedonic in the modelling of spatial variation of housing price in Xiamen city,2013.0,10.14246/irspsd.1.4_29,China,Asia,Upper middle income,CHN,35.9,104.2,"Xiamen, Fujian",,,condo_apartment,listing,journal,OLS,none (kriging and Moran I descriptive),False,False,unknown,106.0,,0,0
84a6e8ef31bf481e52cb738679f636c9a2fcc69f,True,,Loss of Value in House Properties due to Air Pollution in Map Ta Phut Industrial Area of Thailand,2016.0,10.35762/aer.2016.38.3.1,Thailand,Asia,Upper middle income,THA,15.9,100.9,"Map Ta Phut, Rayong province (3 communities around 2 air monitoring stations)",2016.0,2016.0,mixed,appraisal,journal,other,none,False,False,unknown,192.0,,4,36
84fe25f12d7833b71a83f2c2ae3a06dfc013ffcf,False,"Unit of analysis is the residential estate/plot (FANG.com plot-level average selling price per residential unit, with 'average usable area in the apartment' and 'number of households' as regressors), i.e. project-level means rather than individual dwellings; sample size not printed. Flag for human review: double-log OLS for Beijing and Shanghai (Table 2, p. 13) with street-view CNN (PSPNet) green/sky/building view indices is relevant to RQ6 (AI-derived characteristics) and could be extracted if estate-level means are admitted.",Do street-level scene perceptions affect housing prices in Chinese megacities? An analysis using open access datasets and deep learning,2019.0,10.1371/journal.pone.0217505,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing and Shanghai,2015.0,2015.0,condo_apartment,listing,journal,OLS,none,False,False,robust,,computer_vision;semantic_segmentation_PSPNet;street_view_indices,0,0
8506f16b0710a57ed835f9583338b207fd204258,True,,Analysis of Tianjin real estate market: multiple linear regression prediction method,2024.0,10.62051/a4tma782,China,Asia,Upper middle income,CHN,35.9,104.2,Tianjin,2018.0,2022.0,unknown,transaction,conference,OLS,none,False,False,OLS,,,1,4
85ea3296a5d9175ea12142cf209523d5db6d0b42,True,,Hedonic Analysis of the Impact of Flood Events on Residential Property Values in Malaysia: A Study of Willingness to Pay,2019.0,10.22452/mjes.vol56no1.4,Malaysia,Asia,Upper middle income,MYS,4.2,101.9,"Peninsular Malaysia, 20 flood-prone districts (urban and rural)",2013.0,2014.0,single_family,appraisal,journal,OLS,none,False,False,unknown,1360.0,,2,22
85ec88163a881d2f9a23ced6110d5e4e05b48d09,True,,Urban Traffic Arterials and the Sale Price of Single Family Houses in Portland: A Hedonic Analysis of Impacts,1997.0,10.15760/etd.8061,United States,North America,High income,USA,37.1,-95.7,"Portland, Oregon",1994.0,1994.0,single_family,transaction,thesis,OLS,none,False,False,robust,1437.0,,5,99
8674ce1937729ab9e1f1084511ae7a29ecdbc635,True,,The Role of Subjective Perceptions and Objective Measurements of the Urban Environment in Explaining House Prices in Greater London: A Multi-Scale Urban Morphology Analysis,2023.0,10.3390/ijgi12060249,United Kingdom,Europe,High income,GBR,55.4,-3.4,Greater London,2017.0,2021.0,mixed,transaction,journal,OLS,none (postcode district code / space-syntax centralities as regressors),False,False,unknown,49603.0,backpropagation neural network (SVI semantic segmentation view indices -> perceived streetscape scores);street view image semantic segmentation,5,124
877cbdabc2aba0920a744f15d91bf843fa770f5c,True,,The Road to Higher Prices: Will Improved Road Standards Lead to Higher Housing Prices?,2020.0,10.1007/s11146-020-09751-y,Norway,Europe,High income,NOR,60.5,8.5,"Southern Norway (Agder): Kristiansand core town, treatment towns Lillesand, Grimstad, Arendal and control communities west of Kristiansand",2003.0,2013.0,mixed,transaction,journal,OLS,none (zip-code fixed effects),True,True,robust,37216.0,,16,102
87f031f0ad9dc17cd7151e97fc7ad56a0e7b728f,True,,Spatial Variability of the 'Airbnb Effect': A Spatially Explicit Analysis of Airbnb's Impact on Housing Prices in Sydney,2022.0,10.3390/ijgi11010065,Australia,Oceania,High income,AUS,-25.3,133.8,"Sydney, New South Wales",2019.0,2019.0,mixed,transaction,journal,OLS;IV;GWR,"GWR (adaptive gaussian kernel, 190 nearest neighbours) as spatial model; postcode controls in OLS/IV",True,True,robust,36264.0,,4,63
8885ddb1a206684210159fea8394d2ea9c611111,True,,Natural Environmental Amenities and House Prices - A Hedonic Analysis for Integrated Planning,2018.0,10.15641/jarer.v0i0.482,Nigeria,Africa,Lower middle income,NGA,9.1,8.7,"Yaba LCDA, Lagos",2016.0,2016.0,single_family,rent,journal,OLS,none,False,False,OLS,111.0,,1,20
8965e19cc07a82548ccce5e2fba1b9f697ca577c,True,,Craft breweries and residential property values,2024.0,10.1111/grow.12710,United States,North America,High income,USA,37.1,-95.7,"Denver, Colorado",1990.0,2016.0,mixed,transaction,journal,OLS,census tract and ZIP code fixed effects; hedonic difference-in-differences with distance/walk-time bins,True,True,clustered,257565.0,,24,516
89e86c34d31d60b83fe1893b6d6fc9985407503c,True,,From industry to center for arts and culture: the impact of industrial heritage transformation on neighborhood house prices,2025.0,10.3389/frsc.2025.1522520,Denmark,Europe,High income,DNK,56.3,9.5,Aarhus,2006.0,2018.0,condo_apartment,transaction,journal,OLS,postal-code fixed effects + spatio-temporal information lag term (median price of 5 matched nearby sales within 1 km / 365 days),True,True,robust,9742.0,,2,2
8a99113b012c7dc5288863734eba9456a85fd906,True,,"Investigating the impact of property characteristics, cost of living, and environmental factors on rental prices in Baidoa's climate-affected real estate market: a hybrid approach using hedonic regression and neural networks",2025.0,10.3389/frsc.2025.1511761,Somalia,,,,,,Baidoa,0.0,0.0,rental,rent,journal,OLS,none,False,False,unknown,90.0,ANN,1,5
8acb5243fed06bb1f23f1332908a7f46169463e4,True,,Willingness to Pay for Access to Piped Water using Hedonic Pricing Model,2022.0,10.15408/etk.v21i1.16984,Pakistan,Asia,Lower middle income,PAK,30.4,69.3,"Pakistan (urban and rural, four provinces)",2013.0,2014.0,mixed,rent,journal,OLS,none (province and region dummies),False,True,unknown,15884.0,,4,6
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,True,,Indirect Construction of Hedonic Price Indexes for Private Properties,2008.0,10.1007/bf03399268,Switzerland,Europe,High income,CHE,46.8,8.2,"Switzerland (nationwide, 40 regions)",1985.0,2004.0,mixed,transaction,journal,other,"village price-level index (macro-location, GAM with driving-time coordinates) + region fixed effects",True,True,unknown,,,2,34
8c46154fbaf164447e17b77d9874009c161a116a,True,,The effect of light rail transit service on nearby property values: Quasi-experimental evidence from Seattle,2018.0,10.5198/jtlu.2018.1096,United States,North America,High income,USA,37.1,-95.7,"Seattle (Rainier Valley / South King County), Washington",1992.0,2016.0,single_family,transaction,journal,OLS,"none (separate regressions per station neighbourhood, DiD)",False,False,clustered,29654.0,,14,180
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,True,,Information value of property description: A machine learning approach,2021.0,10.1016/j.jue.2020.103299,United States,North America,High income,USA,37.1,-95.7,"Atlanta, GA metropolitan area (MLS-defined)",2010.0,2016.0,single_family,transaction,working_paper,OLS;FE_panel,MLS area x year fixed effects,True,True,clustered,40851.0,NLP text analysis of listing descriptions (uniqueness score),16,56
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,True,,Spatial Heterogeneity in Hedonic Price Effects for Lake Water Quality,2023.0,10.3368/le.100.1.102122-0086r,United States,North America,High income,USA,37.1,-95.7,"Contiguous United States (national model; properties within 1,000 m of lakes > 4 ha)",,,single_family,transaction,journal,OLS,census tract x year fixed effects; state and ecoregion interactions with water quality,True,True,clustered,485860.0,,1,13
90decb41b454a38dee63486b408022b766c2dc06,True,,Effects of New Grocery Store Development on Inner-City Neighborhood Residential Prices,2017.0,10.1017/age.2016.29,United States,North America,High income,USA,37.1,-95.7,"Worcester, Massachusetts",1988.0,2011.0,single_family,transaction,journal,OLS,difference-in-differences with distance buffers around grocery stores,True,False,clustered,33849.0,,6,36
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,True,,Estimation of Housing Price Variations Using Spatio-Temporal Data,2019.0,10.3390/su11061551,Spain,Europe,High income,ESP,40.5,-3.7,Granada,1988.0,2005.0,condo_apartment,listing,journal,other;OLS,regression-cokriging (GLS with spatio-temporal cross-variograms) vs OLS,False,False,unknown,1007.0,,8,48
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,True,,Stratification and Public Utility Services in Colombia: Subsidies to Households or Distortion of Housing Prices?,2006.0,10.32468/be.422,Colombia,South America,Upper middle income,COL,4.6,-74.3,Bogota,2000.0,2003.0,mixed,appraisal,working_paper,OLS;IV,"boundary (stratum border) fixed effects, RD design",False,True,robust,5292.0,,6,80
933204aac69df35d44733b61b90a1210852e7b68,True,,A new Mass Rapid Transit (MRT) line construction and housing wealth: Evidence from the Circle Line,2017.0,10.24294/jipd.v1i1.22,Singapore,Asia,High income,SGP,1.35,103.8,Singapore (Circle Line MRT corridor),2009.0,2013.0,condo_apartment,transaction,journal,OLS,planning-sector fixed effects (first 2 digits of postal code),True,True,unknown,81316.0,,14,168
942f0ff361a49b68c1333c31381f78c02a3d0937,True,,How different are dwellings whose energy efficiency impacts price formation?,2019.0,10.1088/1757-899x/603/4/042015,Spain,Europe,High income,ESP,40.5,-3.7,Barcelona Metropolitan Area (164 municipalities),2014.0,2016.0,condo_apartment,listing,conference,spatial_error,"spatial error model, ML, rook contiguity weights (GeoDa)",True,False,unknown,6492.0,,1,28
96e0ec640b350c1ec477b4a65c34f99c77d53503,True,,Identifying Determinants of Residential Property Values in South London,2011.0,10.2478/v10135-011-0004-0,United Kingdom,Europe,High income,GBR,55.4,-3.4,"Welling (DA16), Bexley, South London",2000.0,2009.0,mixed,transaction,journal,OLS,none,False,False,OLS,1251.0,,1,12
977446bbb49b4d764e634547886ae927f75e8e35,False,"No printed hedonic coefficient table. The main text (37-page author manuscript, Land Economics 2024) reports results only as Figure 5 (percentage price impacts of CAFO exposure ventile bins, 3 km and 5 km); the full regression tables for the log-price and price specifications are in an online Appendix C that is not included in the PDF. Only Table 2 (summary statistics) is printed. Structural controls (square footage, year built, bathrooms, bedrooms, acreage, basement sqft) are described in endnote 7 but their coefficients are never printed.",Costs of Exposure to Industrial Livestock Operations,2024.0,10.3368/le.101.1.011224-0003,United States,North America,High income,USA,37.1,-95.7,Eastern North Carolina (43 counties),2010.0,2014.0,single_family,transaction,journal,OLS,census tract fixed effects,True,True,unknown,46481.0,,0,0
98438191d74bdd40ba8f1ee8325b8fb8b7420348,True,,Influence of Objective Factors on House Prices,2023.0,10.54254/2754-1169/4/20221059,Unknown,,,,,,unknown (variables Carpet_area/Builtup_area/City_type suggest an Indian listing dataset),0.0,0.0,unknown,listing,conference,OLS,none,False,False,unknown,932.0,,1,3
9848e68efcee710bc05a55f8576e298c00f7e04b,True,,"The effect of remediating PCB-contaminated sediments on home prices in Milwaukee, Wisconsin, USA",2022.0,10.1017/age.2022.26,United States,North America,High income,USA,37.1,-95.7,"Milwaukee, Wisconsin",2010.0,2016.0,mixed,transaction,journal,OLS,census-tract fixed effects (213 tracts); DiD around remediation,True,True,unknown,3925.0,,6,76
98c105ab42ddbb39da40f571a9e40579ebb0b16f,True,,The impact of the Coronavirus pandemic on New York City real estate: First evidence,2021.0,10.1111/jors.12591,United States,North America,High income,USA,37.1,-95.7,New York City,2003.0,2020.0,single_family,transaction,journal,OLS;other,none (MODZCTA fixed effects in level models),True,True,clustered,133072.0,,26,86
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,True,,The Impact of Housing Market Segmentation between Tourists and Residents on the Hedonic Price for Landscape Quality,2008.0,10.1007/bf03399270,Switzerland,Europe,High income,CHE,46.8,8.2,"Six alpine resorts in Valais (Verbier, Anzere, Ovronnaz, Champery, Grimentz, Haute-Nendaz)",2003.0,2003.0,rental,rent,journal,OLS,"none (resort-specific interactions with log rooms in Models 2, 4, 6)",False,False,robust,506.0,,6,56
9dd3ef8baea1541e7438928532ebd498c89ffa88,True,,Hedonic Valuation of Real Estate Properties in Nigeria,2018.0,10.15641/jarer.v1i1.452,Nigeria,Africa,Lower middle income,NGA,9.1,8.7,"Lagos metropolis (Island submarket: Ikoyi, Victoria Island, Lekki)",2010.0,2016.0,mixed,transaction,journal,OLS,none,False,False,OLS,256.0,,1,10
a072fb43e67fcc553e457777f0c68324ace19eb7,True,,Factors influencing housing prices: A comparative study using multiple linear regression and random forest,2024.0,10.54254/2753-8818/51/2024ch0174,United States,North America,High income,USA,37.1,-95.7,unknown,,,unknown,listing,conference,OLS,none,False,False,OLS,544.0,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",1,13
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,True,,Nonlinear Effects of School Quality on House Prices,2003.0,10.20955/r.92.185-204,United States,North America,High income,USA,37.1,-95.7,"St. Louis, Missouri metropolitan area (St. Louis County for boundary sample)",1998.0,2001.0,single_family,transaction,working_paper,OLS,attendance-zone boundary fixed effects (Black 1999 design) in Table 5,False,True,clustered,38656.0,,9,123
a34939ebd1d20ba654297f426501ad47056b65a4,True,,Adjusting to the New Normal: River Flood Risk and the Real Estate Market,2025.0,10.1007/s10640-025-00995-x,Germany,Europe,High income,DEU,51.2,10.5,Germany (national; houses in and near official river flood-risk zones),2014.0,2022.0,single_family,listing,journal,FE_panel,zip-code / county / 1 km2 grid fixed effects; difference-in-differences,True,True,clustered,1466509.0,,39,75
a5c3a8b4f02ea9b02009cba2eba334012eb7b212,True,,Economic Impact of a Heritage Policy on Residential Property Values in a Historic District Context: The Case of the Old City of Quebec,2018.0,10.52324/001c.7989,Canada,North America,High income,CAN,56.1,-106.3,"Quebec City (Old City historic district), Quebec",1997.0,2011.0,condo_apartment,transaction,journal,OLS,"repeat-sales first-difference DiD (distance buffers, network and Euclidean)",True,False,unknown,744.0,,3,11
a7a83b631f85316bae926a6c965b325fb26c01c4,True,,A gamma generalised linear model as an alternative to log linear real estate price functions,2019.0,10.4102/jef.v12i1.476,South Africa,Africa,Upper middle income,ZAF,-30.6,22.9,South Africa (national; >2000 suburb/area factor levels),2013.0,2017.0,mixed,listing,journal,other,"none (area factor dummies, >2000 levels)",False,True,unknown,415200.0,autoencoder (H2O) used only for anomaly detection in data cleaning,5,40
a7fe404df2e413395450e192cebe2f68aa921579,True,,Impact of access to sunlight on residential property values: an empirical analysis of the housing market in Shanghai,2022.0,10.3846/ijspm.2022.18004,China,Asia,Upper middle income,CHN,35.9,104.2,Shanghai,2019.0,2021.0,condo_apartment,transaction,journal,OLS,none (Moran's I test on district prices not significant),True,True,clustered,40448.0,,11,111
a842ed7c689fc0985af5ca73c3f97f4279427db3,True,,Influence of a special tax-cooling measure on housing prices in Taiwan: a hedonic pricing model with consideration of the spillover effect,2025.0,10.1007/s42973-025-00217-5,Taiwan,Asia,High income,TWN,23.7,121.0,Taiwan (all counties/cities; municipality vs non-municipality),2012.0,2015.0,mixed,transaction,journal,OLS;FE_panel,none (county fixed effects or county-by-year fixed effects),True,True,unknown,416263.0,,24,124
a855c4aba93669899f6285712fd4b23cfb3500bb,True,,Estimation of a Hedonic House Price Model with Bargaining: Evidence from the Italian Housing Market,2013.0,10.13128/aestimum-13123,Italy,Europe,High income,ITA,41.9,12.6,"Taranto (OMI zones B1, C1, D1, E2); also Alessandria, Cosenza, Crotone, Genova, Venezia Mestre, Vercelli (no coefficients printed)",2009.0,2010.0,unknown,transaction,conference,OLS,none (separate regressions per OMI zone),False,False,unknown,883.0,,8,16
a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,True,,Examining the vintage effect in hedonic pricing using spatially varying coefficients models: a case study of single-family houses in the Canton of Zurich,2022.0,10.1186/s41937-021-00080-2,Switzerland,Europe,High income,CHE,46.8,8.2,Canton of Zurich,2018.0,2019.0,single_family,transaction,journal,other,"GP-based spatially varying coefficients (SVC) model, maximum likelihood (R package varycoef); SVCs on intercept, Z.age, Z.age2",True,False,unknown,1578.0,Gaussian process SVC,1,10
a9aa8ff2e63af06927e90407046655fab060c351,False,"No printed coefficients for property/neighbourhood characteristics. The hedonic control vector (distance to CBD, plot area, year built, dwelling type, SEIFA, distances to transport/schools/parks, flood/heritage overlays) is explicitly 'not shown' (p. 17); Table 5 reports only the adjusted interrupted-time-series treatment effects of infill development within 100 m distance rings (exponentiated coefficients, SEs omitted), which are not hedonic characteristic coefficients. Supplementary tables are not in the PDF.",The Size and Spatial Extent of Neighborhood Price Impacts of Infill Development: Scale Matters?,2022.0,10.1007/s11146-022-09916-x,Australia,Oceania,High income,AUS,-25.3,133.8,Melbourne,2006.0,2015.0,mixed,transaction,journal,other,postcode and LGA fixed effects,True,True,robust,418273.0,,0,0
aa81dc840f8ab6c12b272e830117706e34b5a89a,True,,Fresh air in the city: the impact of air pollution on the pricing of real estate,2024.0,10.1007/s11356-023-31668-1,Poland,Europe,High income,POL,51.9,19.1,Warsaw,2021.0,2022.0,condo_apartment,listing,journal,spatial_error,"spatial error model (SEM), k-nearest-neighbour weights",False,True,unknown,14938.0,,2,34
aa82db73a0ef7b24a4266aa846327f66030956a0,True,,A spatial analysis of EPCs in The Belfast Metropolitan Area housing market,2019.0,10.1080/09599916.2019.1697345,United Kingdom,Europe,High income,GBR,55.4,-3.4,"Belfast Metropolitan Area, Northern Ireland",2013.0,2014.0,mixed,transaction,journal,OLS;spatial_lag;GWR,"OLS with spatial/temporal dummies; GWR (Table 9-10, only quantiles of local coefficients, not extracted); spatial lag models with inverse exponential distance weights (Table 11, n=961)",True,True,OLS,1478.0,,13,91
afc63bb9b7bf51c6364ea26f57de3de63b12d8bb,True,,Irish Property Price Estimation Using A Flexible Geo-spatial Smoothing Approach: What is the Impact of an Address?,2022.0,10.1007/s11146-022-09888-y,Ireland,Europe,High income,IRL,53.1,-8.2,Dublin (city and county),2018.0,2018.0,mixed,transaction,journal,other,"Geo-additive GAM with Gaussian-process spatial smooth (Kammann-Wand kernel, 100 knots); also linear model, nearest neighbours, decision tree and random forest for accuracy comparison",False,True,unknown,5208.0,random forest;decision tree;text-extracted attributes from listing descriptions,1,29
b0f7dc6f984405958850264589ee0ef2b7e42b69,True,,"Neighborhood Historic Preservation Status and Housing Values in Oklahoma County, Oklahoma",2009.0,10.68479/001c.9769,United States,North America,High income,USA,37.1,-95.7,"Oklahoma County (Oklahoma City), Oklahoma",2000.0,2003.0,single_family,appraisal,journal,OLS,none (fine neighbourhood fixed effects from parcel-ID ranges),False,True,robust,368433.0,,2,58
b150aa7a491222e57926fd7829879b82c8d7c8d6,True,,The Impacts of Environmental Amenities on Rental Value of Houses and a Pathway Towards Sustainable Urban Development Align with SDG 11,2025.0,10.47172/2965-730x.sdgsreview.v5.n02.pe02806,Bangladesh,Asia,Lower middle income,BGD,23.7,90.4,Rajshahi City Corporation,,,rental,rent,journal,OLS,none,False,False,robust,210.0,,3,33
b34f2af5cff586af9757e0b66b7191bb692373e4,False,"Aggregate unit of analysis: the regression (Table 3, p. 9) is estimated on 28 condominium PROJECTS, with the dependent variable defined as the average selling price of each project (baht per unit, project-level average, p. 6), not individual dwelling prices. Only 3 project-level regressors retained (number of floors in the building, distance to MRT station, distance to department store). Kept qualitatively (transit proximity, Bangkok).","Determinants of New Condominium Prices near MRT Orange Line Stations: Case study of Estimating Housing Affordability in Bangkok, Thailand",2025.0,10.55463/hkjss.issn.1021-3619.64.29,Thailand,Asia,Upper middle income,THA,15.9,100.9,Bangkok (MRT Orange Line corridor),2024.0,2024.0,condo_apartment,listing,journal,OLS,none,False,False,OLS,28.0,,0,0
b3911e100e43278a0d85948b17dd0e029042bb65,False,"No usable multivariate hedonic regression table: the paper reports only ten bivariate OLS trend lines (rent on land value, population density, security score, slope, distance to towns, floor size, distances to four road classes; pp. 8-12) without standard errors, t-statistics, p-values or sample sizes, plus an ad hoc 'combined spatial hedonic' formula (p.12) whose additional coefficients (noise, scenic beauty, tiles, fence, garage, pollution, night guard, parking, house age) have no reported estimation output. Variance information absent, so no coefficient can enter the synthesis.","Analysis of Spatial Factors Affecting Rental House Prices: A Case Study of Nyeri Town Constituency, Kenya",2021.0,10.12691/jgg-9-3-2,Kenya,Africa,Lower middle income,KEN,-0.02,37.9,"Nyeri Town Constituency, Nyeri County",2019.0,2020.0,rental,rent,journal,OLS,GIS-based bivariate regressions and AHP weighting,False,False,unknown,0.0,,0,0
b4d90ac556c12775841d148b92b32c2089b062dd,True,,The Effects of Landfills on Rural Residential Property Values: Some Empirical Evidence,2000.0,10.68479/001c.9345,United States,North America,High income,USA,37.1,-95.7,"Massachusetts, six rural towns (Pepperell, Hudson, Belchertown, Clinton, Leicester, Ware)",1992.0,1995.0,single_family,transaction,journal,OLS,none (separate regressions by town),True,False,robust,379.0,,6,72
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,True,,Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria,2014.0,10.1177/0042098013492234,Austria,Europe,High income,AUT,47.5,14.6,"Austria (national, 9 federal states)",1998.0,2009.0,single_family,transaction,working_paper,OLS;spatial_lag;IV;GWR,"SAR (ML) and S2SLS with k=5 nearest-neighbour weights; GWR and mixed GWR (Gaussian kernel, adaptive bandwidth)",False,True,robust,3887.0,,4,63
b633c49b2f5879640f919bdc54ae4390ee31d91d,True,,Time-Geographically Weighted Regressions and Residential Property Value Assessment,2019.0,10.1007/s11146-019-09718-8,United States,North America,High income,USA,37.1,-95.7,"50 municipalities in Connecticut; 145 towns in the Greater Boston Area, Massachusetts",1987.0,2013.0,single_family,transaction,working_paper,FE_panel,"town fixed effects (Table 2); GWR and TGWR local regressions (summaries only, not extracted)",True,True,clustered,867596.0,,2,40
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,True,,Sorting in an urban housing market-is there a response to demographic change?,2021.0,10.1007/s10037-021-00158-7,Germany,Europe,High income,DEU,51.2,10.5,Dortmund,2007.0,2016.0,mixed,listing,journal,SAC,GS2SLS spatial autoregressive model with spatial lag (lambda) and spatial error (rho),True,True,robust,57137.0,,24,95
b827a50a5b3fe735ba3475c0514ffecf35e91d7e,True,,"If you build it, they will change: Evaluating the impact of commuter rail stations on real estate values and neighborhood composition in the Rotterdam-The Hague metropolitan area, the Netherlands",2021.0,10.5198/jtlu.2021.1795,Netherlands,Europe,High income,NLD,52.1,5.3,"Rotterdam-The Hague metropolitan area (Berkel Westpolder, Pijnacker Zuid, Nootdorp RandstadRail stations)",1985.0,2018.0,mixed,transaction,journal,OLS,none (catchment-zone DID),False,False,unknown,31072.0,,6,108
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,True,,Measures of labour market accessibility. What can we learn from observed commuting patterns?,2020.0,10.18335/region.v7i1.261,Norway,Europe,High income,NOR,60.5,8.5,Stavanger region (Western Norway),2003.0,2007.0,single_family,transaction,journal,OLS;spatial_error;other,"spatial error model and spatial Durbin model, k=3 nearest-neighbour row-standardised weights",True,False,OLS,4392.0,,16,176
b922ab81201881b47779769df9e76de174e13df7,True,,"Comparing traditional and machine learning techniques in apartments mass appraisal in Fortaleza, Brazil",2025.0,10.36253/aestim-15344,Brazil,South America,Upper middle income,BRA,-14.2,-51.9,Fortaleza (Ceará),2017.0,2021.0,condo_apartment,transaction_and_listing,journal,OLS;spatial_error,"spatial error model (GMM, Arraiz et al. 2010), queen contiguity weights",True,False,unknown,32688.0,MARS;M5P;random_forest;quantile_random_forest;GBM;LightGBM;CatBoost;XGBoost;deep_learning,2,48
ba26780937630bfce76ea1bcc89a7777faa87ed0,False,"Unit of analysis is aggregate: the hedonic model (eq. 4-6, p. 7) is estimated on district x property-type x quarter MEANS of log price (balanced panel obtained by averaging over individual transactions), not on individual properties. In addition, Tables 3-4 print point estimates only with no standard errors, t-statistics or p-values (only symbols for |t|<=1.96 and 1.96<|t|<=4), so no usable precision information. Kept qualitatively (earthquake-risk capitalization, Japan).",Earthquake Risk Embedded in Property Prices: Evidence From Five Japanese Cities,2021.0,10.1080/01621459.2021.1928512,Japan,Asia,High income,JPN,36.2,138.3,"Tokyo, Osaka, Nagoya, Fukuoka, Sapporo",2006.0,2015.0,mixed,transaction,journal,other,none (city dummies + district random error component),False,True,unknown,331343.0,,0,0
ba6d3043dcfb0e7c6ad45ae35c0629afbc728c5f,True,,An ANN Model for the Influence of Siding Materials on Single-Family Home Values,2003.0,10.18260/1-2--12549,United States,North America,High income,USA,37.1,-95.7,"College Station, Texas",1997.0,2000.0,single_family,transaction,conference,OLS,none,False,False,unknown,145.0,"ANN (Jordan-Elman recurrent network) for price prediction, compared with hedonic OLS",1,5
baaee624057dd67c85185a4177e6d00e5b13c4a2,True,,The Hedonic Pricing Model Applied to the Housing Market,2020.0,10.35808/ijeba/526,Vietnam,Asia,Lower middle income,VNM,14.1,108.3,Ho Chi Minh City and Ha Noi,2019.0,2019.0,single_family,transaction,journal,OLS,none,False,False,robust,205.0,,1,8
bbc85c0376ef4c6974813a189124a40708684478,True,,Price changes of repeat-sales houses in Kaohsiung City: analyses based on hierarchical linear growth models,2023.0,10.3846/ijspm.2023.19935,Taiwan,Asia,High income,TWN,23.7,121.0,Kaohsiung City,2012.0,2020.0,condo_apartment,transaction,journal,other,none (CBD/suburb dummy),False,False,robust,7076.0,,1,6
bc3577b4d2c3cc062519a4199d4f0a8834e89c89,True,,Points of Interest and Housing Prices,2023.0,10.2478/remav-2023-0007,Poland,Europe,High income,POL,51.9,19.1,Olsztyn,2021.0,2021.0,condo_apartment,transaction,journal,spatial_error;OLS,"spatial error model (SAR error), k=5 nearest neighbours weight matrix",False,False,unknown,2182.0,,4,54
bc5c2c3c86f1f45909dcce75c8f09acff914dd28,True,,Toward transparent and accurate housing price appraisal: Hedonic price models versus machine learning algorithms,2025.0,10.1186/s40854-025-00874-w,South Korea,Asia,High income,KOR,35.9,127.8,Busan,2015.0,2015.0,condo_apartment,transaction,journal,OLS;spatial_lag,"Spatial lag regression (inverse-distance band W, row-standardised)",False,False,unknown,61152.0,random forest;deep neural network;SHAP;Gini importance;permutation importance,2,34
bcc88aa6a74894b8030f7071e7fd929a9fa08668,False,"Aggregate unit of analysis: the regressions (Tables 5-6, pp.13-14) use 168 apartment complexes (129 urban + 39 rural; the rural complexes aggregate 832 sales) with the log of the complex-level average price per m2 as dependent variable; regressors are factor scores of network distances to amenities, ln(complex age), ln(max floor), dummy for total units, bus-stop and CBD distance, urban and Geum River dummies. Complex (project) means rather than dwelling-level transactions; Living SOC variables are factor-analysis scores, not interpretable distances. Only z/t-values printed (no SEs). Borderline: flag for human review if complex-level Korean apartment studies are to be admitted.","Urban versus rural disparities in amenity proximity and housing price: the case of integrated urban-rural city, Sejong, South Korea",2024.0,10.1007/s10901-023-10098-y,South Korea,Asia,High income,KOR,35.9,127.8,Sejong,,,condo_apartment,transaction,journal,spatial_lag;OLS,SLM (spatial lag) with spatial weight matrix,False,False,unknown,168.0,,0,0
bcf745178dcc691b18c9d83f1fe5e6d55eff9a85,False,"Not a hedonic price study. LSU dissertation (Shuang Zhu, 2011) with three essays: (1) appraisal bias/accuracy regressions on differences between appraisals of New Orleans foreclosure properties (Tables 1.2-1.3, appraiser characteristics as regressors); (2) Cox hazard models of mortgage default with foreclosure delay (Tables 2.3-2.x); (3) Cox hazard models of default with housing-expectation proxies from Case-Shiller futures (Tables 3.4-3.6). No residential price or rent regression with property-characteristic coefficients; the word 'hedonic' does not appear in the PDF. The metadata abstract (spatial-temporal hedonic prediction) belongs to a different document.",Three essays on real estate finance,2011.0,10.31390/gradschool_dissertations.1653,United States,North America,High income,USA,37.1,-95.7,New Orleans (essay 1); national loan-level (essays 2-3),,,unknown,appraisal,thesis,OLS;other,none,False,False,unknown,1532.0,,0,0
bd42cea5779904b39c488f5e59235573696a2827,True,,The impact of urban renewal on neighboring housing prices: an application of hierarchical linear modeling,2022.0,10.3846/ijspm.2022.15971,Taiwan,Asia,High income,TWN,23.7,121.0,Taipei City,2008.0,2016.0,mixed,transaction,journal,other,"none (two-level hierarchical linear model, houses nested in urban renewal projects)",False,False,unknown,19157.0,,1,16
c0719dfc2e99247adf55e3df25480bbce55099dd,True,,Modelling coastal externalities effects on residential housing values,2022.0,10.1108/ijhma-05-2022-0071,Nigeria,Africa,Lower middle income,NGA,9.1,8.7,"Victoria Island, Lagos",,,rental,rent,journal,OLS,none,False,False,unknown,318.0,,6,72
c0c750e0ff9e1fcc59888eee28b0b7208f559964,True,,"Essays on housing markets and economic growth (Chapter 2: residential property values and proximity to coal mines, Monongalia County, WV)",2010.0,10.33915/etd.4652,United States,North America,High income,USA,37.1,-95.7,"Monongalia County, West Virginia",2004.0,2005.0,single_family,transaction,thesis,spatial_lag,"Bayesian heteroskedastic spatial autoregressive (SAR) model, row-standardised 2-nearest-neighbour weight matrix (selected by Bayesian model comparison over SAR/SEM/SDM); direct, indirect and total effects per LeSage and Pace (2009)",False,False,robust,683.0,,2,54
c15ba8a0a6017224eaf4694459bf962179074662,True,,A Study of the Metro and Housing Value Interaction with Hedonic Price Model: Comparison of Ankara Batikent and Koru Metro Stations,2023.0,10.30785/mbud.1284843,Turkey,Asia,Upper middle income,TUR,38.96,35.2,Ankara (Batikent / Kent-Koop and Koru neighbourhoods),2022.0,2022.0,condo_apartment,listing,journal,OLS,none,False,False,OLS,42.0,,2,15
c30509d1b7dff13ef9c6d68570be3618b239e0cd,False,"Price functions are EPR-MOGA (evolutionary polynomial regression) equations: each term is a multiplicative combination of several variables raised to fractional powers (e.g. Sb^0.5*B^0.5*Vm^0.5), so no interpretable per-characteristic coefficient exists; no standard errors, t or p values are reported; only CoD and cross-validation errors (Tables 2-4, 6-7) and narrative average percentage variations from a simplified exogenous simulation (text pp. 14-16, Figures S1-S12). Not usable for coefficient synthesis; keep qualitatively (COVID-19, six Italian cities, 165 sales per city per phase, 2019H2 vs 2021H1).",An Assessment Methodology for the Evaluation of the Impacts of the COVID-19 Pandemic on the Italian Housing Market Demand,2021.0,10.3390/buildings11120592,Italy,Europe,High income,ITA,41.9,12.6,"Turin, Milan, Florence, Rome, Naples, Catania",2019.0,2021.0,condo_apartment,transaction,journal,other,none (OMI trade-area dummies),False,True,unknown,1980.0,genetic algorithm (EPR-MOGA),0,0
c457882224ad7235eecc5a3f2b95232d76a155e7,True,,Unleashing the hidden green value: assessing the impact of energy certification and environmental amenities on real estate through hedonic modelling,2025.0,10.36253/aestim-17418,Italy,Europe,High income,ITA,41.9,12.6,"Padua (Padova), Veneto",2022.0,2023.0,condo_apartment,transaction,journal,OLS,none,False,False,unknown,222.0,,1,14
c5910ffe5f4e46ed4d95f8ada01d97feb8173ca6,True,,Research on the Influencing Factors of House Prices in Chicago,2024.0,10.62051/1jq1vs36,United States,North America,High income,USA,37.1,-95.7,"Chicago suburbs, Illinois",,,single_family,transaction,conference,OLS,none,False,False,OLS,,,1,8
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,True,,"Spatial heterogeneity in implicit housing prices: evidence from Hangzhou, China",2017.0,10.3846/1648715x.2016.1247021,China,Asia,Upper middle income,CHN,35.9,104.2,Hangzhou (six urban districts),2014.0,2014.0,condo_apartment,unknown,journal,OLS;GWR,"spatial expansion (coordinate interactions), GWR, mixed GWR (adaptive Gaussian kernel)",False,False,OLS,603.0,,6,60
c6b33e6b839caa1157a283c6f9a1e3350edd0558,True,,Modeling unobserved heterogeneity in hedonic price models,2021.0,10.1111/1540-6229.12320,United States,North America,High income,USA,37.1,-95.7,"Los Angeles (multifamily); Heemstede, Netherlands (single-family)",2001.0,2017.0,mixed,transaction,journal,other,"Bayesian hedonic models: standard (location FE), hybrid repeat-sales, property random effects (RE), Besag spatial random effects, spatial random walk (SRW) along TSP route",True,True,unknown,4731.0,,14,105
c7b242d28013321bceaeef0f994fd2d0dab032c0,True,,Implicit Prices in Urban Real Estate Valuation,2013.0,10.4067/s0718-915x2013000200009,Spain,Europe,High income,ESP,40.5,-3.7,Cordoba,0.0,0.0,condo_apartment,transaction,journal,OLS,none,False,False,unknown,2888.0,ANN,1,6
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,True,,Do people value farmers markets: A spatial hedonic pricing model approach,2024.0,10.1017/age.2024.1,Canada,North America,High income,CAN,56.1,-106.3,"Edmonton, Alberta",2015.0,2017.0,single_family,transaction,journal,OLS;spatial_lag,"SAR with five weight matrices (800-m, 1000-m, nearest 10/20/30)",True,False,unknown,8241.0,,6,168
c98a43acf9eb55645cbcf1d65650ddce2b8ab2c6,False,"Aggregate unit of analysis: dependent variable is the zip-code-level Zillow median housing price per square foot (monthly panel 2010-2016), not individual dwelling prices; the only regressors of interest are an Uber-entry indicator and zip-code-level census interactions (college share, poverty, public transport use, commute time, vehicles per capita, traffic delay, air quality above median). No dwelling-characteristic implicit prices are estimated.",The social value of a ridesharing platform: a hedonic pricing approach,2022.0,10.1007/s00181-022-02310-9,United States,North America,High income,USA,37.1,-95.7,"US metropolitan areas (zip codes), Uber entry 2010-2016",2010.0,2016.0,mixed,other,journal,FE_panel,none (zip code / metro fixed effects),True,True,clustered,398209.0,,0,0
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,True,,Property price and anti-social behaviour: An empirical study of Northern Ireland,2025.0,10.3846/ijspm.2025.23983,United Kingdom,Europe,High income,GBR,55.4,-3.4,Northern Ireland (all local government districts; Belfast vs non-Belfast),2018.0,2022.0,mixed,transaction,journal,OLS;spatial_lag;IV,OLS with LGD dummies; spatial lag term (inverse-distance weighted ln price of neighbours sold within two months) in Models 18-20; 2SLS in Model 20,True,True,unknown,14521.0,,20,173
cfc27a33426e6615c17a451873b0b54c65612252,False,"Unit of analysis is the housing estate (project): the dependent variable is the log of the average per-square-metre price of each housing estate (HEPrice, 47,316 estates in 10 Chinese cities), not individual dwelling transactions; only building year and proximity variables are included as estate-level characteristics (no structural attributes of dwellings). Aggregate (project-mean) hedonic, excluded from coefficient synthesis per protocol.",Multilevel effects of urban form and urban functional zones on housing prices: evidence from open-source big data,2024.0,10.1007/s10901-023-10109-y,China,Asia,Upper middle income,CHN,35.9,104.2,"10 extra-large cities (Shanghai, Beijing, Shenzhen, Guangzhou, Chengdu, Hangzhou, Wuhan, Nanjing, Changsha, Xi'an)",2021.0,2021.0,condo_apartment,listing,journal,other;OLS,hierarchical linear model (two-level: estate within city),False,True,robust,47316.0,NLP (natural language processing of POI data for urban functional zones),0,0
d37971d97af2ef251a0da6b9c73ae5f307074e7d,True,,"Hedonic Analysis of Housing Prices Near the Portland Urban Growth Boundary, 1978-1990",1996.0,10.15760/etd.1344,United States,North America,High income,USA,37.1,-95.7,"Washington County (Portland metropolitan area), Oregon",1978.0,1990.0,single_family,transaction,thesis,OLS,none,False,False,unknown,2269.0,,15,225
d3812508998e06d0728e9af8b9c2c72e4dad465a,True,,Crime Measures and Housing Prices: an Analysis Using Quantile Regression and Spatial Autocorrelation,2025.0,10.1007/s11146-024-09997-w,United States,North America,High income,USA,37.1,-95.7,"Seattle, Washington",2008.0,2020.0,single_family,transaction,journal,IV;quantile,"spatial lag of neighbouring sale prices (log WY, sales within 2,000 ft in past 24 months) included as regressor in Tables 7-9 Panel B / 11 Panel B; no area FE except zip code FE in Table 11",True,False,clustered,61902.0,,72,1164
d3cc2b5ffbf39645fc47562257a85c240474e3d7,True,,Investment incentives of rent controls and gentrification: Evidence from German micro data,2024.0,10.1111/1540-6229.12478,Germany,Europe,High income,DEU,51.2,10.5,"Germany (national, municipality/district level)",2010.0,2019.0,condo_apartment,listing,journal,OLS,none (district fixed effects),True,True,clustered,3064152.0,,4,60
d3e27cac15a096168d22a145ab49342c924dc96e,True,,Bridging the information gap: what are the impacts of EPCs on Prague's residential market selling prices?,2025.0,10.2478/fiqf-2025-0026,Czech Republic,Europe,High income,CZE,49.8,15.5,Prague,2023.0,2023.0,condo_apartment,listing,journal,OLS,none (separate regressions by location class; ordinal location variable in the pooled model),False,False,OLS,4189.0,,14,65
d458e3973f160efbbd5c7fd28ec076d63dc933e1,True,,An Estimation of the Coastal Premium for Residential Housing Prices in San Diego County,2011.0,10.1007/s11146-009-9195-x,United States,North America,High income,USA,37.1,-95.7,"San Diego County, California",2006.0,2006.0,single_family,transaction,journal,OLS,none (106 neighbourhood/ZIP fixed effects),False,True,unknown,9755.0,,3,45
d5fa1a30f0b446809e7d5129c56b30f298ed13b5,False,"Aggregate unit of analysis: first-difference regressions of census block-group median rent / median home value (2000-2010) on change in conserved acres, weighted by households; no property-level transactions and no dwelling characteristic coefficients reported (housing controls included but not printed).",Land conservation policy and rental markets: evaluating unintended housing price effects,2026.0,10.1007/s00168-026-01528-0,United States,North America,High income,USA,37.1,-95.7,national (census block groups),2000.0,2010.0,mixed,other (census median values and rents),journal,FE_panel,county-trend FE; propensity score matching,True,True,clustered,58932.0,,0,0
d66dcd3e24d3aa705a9e17810be910446c18dce3,True,,What is the effect of location on rental housing prices in Athens?,2021.0,10.7819/rbgn.v23i3.4114,Greece,Europe,High income,GRC,39.1,21.8,Athens,2014.0,2014.0,condo_apartment,rent,journal,OLS;other,"regression-kriging (GLS with exponential variogram, range 878.6 m)",False,False,unknown,757.0,,2,26
d8941587e0ea17530b8486a47a4da824ad437bf0,True,,Rail Accessibility and Residential Unit Prices: Evidence from Melbourne's Cranbourne Line,2025.0,10.54254/2754-1169/2025.cau28492,Australia,Oceania,High income,AUS,-25.3,133.8,"Melbourne (Cranbourne Line corridor, south-east suburbs)",,,mixed,transaction,conference,OLS;GWR,GWR for spatially varying covariates (Table 6); OLS global model,False,False,OLS,374.0,,2,19
d956659c01d343fed17ef54a0b1e248a34a32995,True,,The effect of urban green spaces on house prices in Warsaw,2018.0,10.3846/ijspm.2018.5220,Poland,Europe,High income,POL,51.9,19.1,Warsaw,2010.0,2015.0,condo_apartment,transaction,journal,OLS;WLS;quantile,none (district dummies),True,True,unknown,43075.0,,6,153
db3684d67741de25ae92064ef093bf9c1d604ef8,True,,Analyzing Key Determinants of Property Valuation in Boston Neighborhoods,2025.0,10.54254/2754-1169/2025.bj25752,United States,North America,High income,USA,37.1,-95.7,"Boston, MA",2024.0,2024.0,mixed,appraisal,conference,OLS,none (ZIP-code dummies),False,True,unknown,,"K-means clustering (descriptive segmentation, not used for coefficients)",1,9
dbfc419fae85b2cf607f68db238ec77b3593a5e0,True,,Dynamic effect of sports parks on housing prices: Evidence from Hangzhou Asian Games Park,2025.0,10.3846/ijspm.2025.24813,China,Asia,Upper middle income,CHN,35.9,104.2,Hangzhou (Zhejiang),2018.0,2023.0,condo_apartment,transaction,journal,OLS,none (region fixed effects; distance rings),True,True,unknown,31329.0,,16,124
ddac707c3201e8fd8ee39f4a8176310e5a638976,True,,Potential impact of property management on the market value of dwellings in multi-owned housing,2023.0,10.1007/s10901-023-10032-2,Poland,Europe,High income,POL,51.9,19.1,Olsztyn,2018.0,2019.0,condo_apartment,transaction,journal,OLS,none,False,False,OLS,146.0,,4,20
dde22a8458111f4d97568d09ce7efc13ea6e96aa,True,,Public transport accessibility and the prices of nearby properties: the case of the first metro line in Warsaw,2020.0,10.18757/ejtir.2020.20.2.3979,Poland,Europe,High income,POL,51.9,19.1,Warsaw,2006.0,2013.0,condo_apartment,transaction,journal,OLS;spatial_error;spatial_lag,SEM and SAR with spatial weight matrix,True,False,clustered,5576.0,,6,123
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,True,,Urban location and housing prices within a hedonic model,2008.0,10.68479/001c.9464,United States,North America,High income,USA,37.1,-95.7,"Indianapolis (Marion County), Indiana",1999.0,1999.0,single_family,transaction,journal,OLS,none,False,False,unknown,8772.0,,20,91
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,True,,Energy Retrofitting for the Modern Heritage Enhancement in Weak Real Estate Markets: The Olivetti Housing Stock in Ivrea,2022.0,10.3390/su14063507,Italy,Europe,High income,ITA,41.9,12.6,"Ivrea and Eporediese area (31 surrounding municipalities), Piedmont",2019.0,2020.0,mixed,listing,journal,spatial_error,"Spatial Error Model (GeoDa), lambda 0.321 (DS) / 0.246 (SS)",False,False,unknown,1154.0,,2,23
de48aa9a311d709ef0a33453d7042001c2e721a6,True,,"Public transport, noise complaints, and housing: Evidence from sentiment analysis in Singapore",2021.0,10.1111/jors.12524,Singapore,Asia,High income,SGP,1.35,103.8,a public-housing (HDB) town in Singapore along new bus route no. 972,2010.0,2018.0,condo_apartment,transaction,journal,OLS,building-block fixed effects,True,True,clustered,1450.0,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),4,35
dfd836c56fd33dc021acfdf9971e3bbd78377b82,True,,Costos de contaminación ambiental en la valoración de inmuebles en la ciudad de Cuenca: estudio de la depreciación en sectores de alta contaminación,2025.0,10.26871/killkanasocial.v9i1.1581,Ecuador,South America,Upper middle income,ECU,-1.8,-78.2,Cuenca,2018.0,2018.0,mixed,appraisal,journal,OLS,none,False,False,robust,101598.0,,3,138
e06a4d3e776b1e6666c940f56997612ef11873e4,True,,The effect of BEAM Plus certification on property price in Hong Kong,2017.0,10.3846/1648715X.2017.1409290,Hong Kong,Asia,High income,HKG,22.3,114.2,"Hong Kong, Sham Shui Po - Cheung Sha Wan district (16 residential developments)",2012.0,2014.0,condo_apartment,transaction,journal,OLS,sub-district dummy (NSSP),False,True,unknown,646.0,,2,23
e075c6fe2099973f79200c3fb2110ef7bfef767a,True,,"Application of the hedonic pricing model to real estate valuation in Hanoi, Vietnam",2024.0,10.30574/wjarr.2024.24.2.3458,Vietnam,Asia,Lower middle income,VNM,14.1,108.3,Hanoi,2023.0,2024.0,unknown,listing,journal,OLS,none,False,False,unknown,195.0,,1,7
e1b44941a0d59a0ba33dc85660a7305568feae7f,True,,"Assessing the economic premium of additional elevator: PSM hedonic analysis in Beijing, China",2024.0,10.3846/ijspm.2024.22606,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing,2017.0,2021.0,condo_apartment,transaction,journal,OLS;quantile,none (district fixed effects),True,True,unknown,17952.0,,66,90
e2459715fae0e20316482cb1778f7b7fac58b6af,True,,Understanding Spatial Variations in the Impact of Accessibility on Land Value Using Geographically Weighted Regression,2012.0,10.5198/jtlu.v5i2.225,United Kingdom,Europe,High income,GBR,55.4,-3.4,"Tyne and Wear (Newcastle, Gateshead, North and South Tyneside)",2005.0,2005.0,mixed,listing,journal,OLS;GWR,"GWR local model (results mapped only, not tabulated); global OLS in Table 2",False,False,unknown,1690.0,,1,10
e2aec14baa7ef3008564e4685e54665957939139,True,,"Determinants of Luxurious Condominium Prices in Bangkok CBD: A Case study of Encouraging Housing Affordability in Bangkok, Thailand",2022.0,10.14246/irspsd.10.1_167,Thailand,Asia,Upper middle income,THA,15.9,100.9,Bangkok CBD,2014.0,2018.0,condo_apartment,listing,journal,OLS,none,False,False,unknown,55.0,,3,48
e2cefa2df09279ce534acb1e9e0f5991e38a2e5f,False,"Not a housing price study: all regressions (Tables 2-6) are Rosen-Roback hedonic WAGE regressions (dependent variable log hourly wage, CPS workers across 219 MSAs). Housing cost enters only as an MSA-level index (intercept of an unreported hedonic housing regression) used as a regressor; no residential price/rent equation with characteristic coefficients is printed.",Heterogeneous Individual Valuations of a Mild Climate,2026.0,10.1007/s10640-026-01110-4,United States,North America,High income,USA,37.1,-95.7,219 MSAs,,,unknown,other,journal,WLS,,True,False,clustered,257478.0,,0,0
e4f33aca0968c7c930129cd6f3fbf32507e5ac89,True,,The effects of a shopping mall on housing prices: a case study in Hangzhou,2019.0,10.3846/ijspm.2019.6360,China,Asia,Upper middle income,CHN,35.9,104.2,Hangzhou (study area around West Intime shopping mall),2011.0,2015.0,condo_apartment,transaction,journal,OLS;spatial_lag;spatial_error,OLS main models; SAR/SEM robustness (Table A2) with GIS-randomised unit coordinates,True,True,unknown,9254.0,,13,215
e6c58cb070edd6cfaff8b1bababd256016f5ed90,True,,Hedonic real estate price estimation with the spatiotemporal geostatistical model,2023.0,10.1007/s43071-023-00039-w,Japan,Asia,High income,JPN,36.2,138.3,"Yokosuka City, Kanagawa Prefecture",2016.0,2019.0,single_family,transaction,journal,OLS;other;spatial_lag;spatial_error,"Bayesian spatiotemporal geostatistical model (MCMC, Metropolis-Hastings); SLX; SDEM",True,True,OLS,1136.0,,18,330
e7545aa69fd7e3b0b4fddbe8806b08519280a674,True,,Analysis of House Prices to Assess Economic Impacts of New Public Transport Infrastructure: Madrid Metro Line 12,2011.0,10.3141/2245-16,Spain,Europe,High income,ESP,40.5,-3.7,"South Madrid metropolitan area (Alcorcon, Getafe, Leganes, Mostoles, Fuenlabrada)",,,condo_apartment,listing,journal,OLS;spatial_error;spatial_lag,"SEM and SLM (ML, GeoDa)",False,False,unknown,1714.0,,3,39
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,True,,Valuing Neighbourhood Soundscapes in Urban Housing Markets: Evidence from Karachi,2026.0,10.30541/v64i3pp.241-261,Pakistan,Asia,Lower middle income,PAK,30.4,69.3,Karachi,,,unknown,appraisal,journal,OLS,none,False,False,unknown,484.0,,2,64
eb83365b4894fa9c413cfdff9bdf069881dad3ad,True,,Examining the spatial relationship between environmental health factors and house prices: NO2 problem?,2018.0,10.1108/jerer-01-2018-0008,United Kingdom,Europe,High income,GBR,55.4,-3.4,"Belfast, Northern Ireland",2013.0,2013.0,mixed,transaction,journal,OLS;GWR;spatial_lag,GWR (adaptive bandwidth 40 NN) and spatial lag model (inverse-distance W),False,True,unknown,2501.0,,11,228
ebd764414d12429dec7ee666a2f902c6faad3bb7,True,,Measuring the Value of U.S. National Parks Using Hedonic Property Value Models,2023.0,10.3368/le.100.1.102122-0088r1,United States,North America,High income,USA,37.1,-95.7,"Counties around 18 National Park Service units (Birmingham AL, Cuyahoga OH, Paterson NJ, River Raisin MI, Tule Springs NV, Boston MA, Tucson AZ, Great Smoky Mountains TN/NC, and others reported in figures/appendix)",1987.0,2021.0,single_family,transaction,journal,FE_panel,none (block group fixed effects),True,True,unknown,,,13,45
ebefda640bee5302366b339dc1624f32b129581a,True,,Property price gradients: the vertical dimension,2011.0,10.1007/s10901-010-9203-8,Hong Kong,Asia,High income,HKG,22.3,114.2,"Hong Kong, Telford Gardens housing estate (Kowloon Bay)",2000.0,2006.0,condo_apartment,transaction,journal,OLS,single estate (none),False,False,robust,807.0,,4,54
ecb8bacfa12ff5fad71503a1b459329f9f420bc4,False,"Two-stage mass-appraisal model: k-means clustering into submarkets (on area, age, bedrooms, bathrooms, type) followed by ordinary kriging of prices within each submarket. No hedonic regression is estimated; the paper reports only cluster descriptive statistics (Table 2), variogram models and LOOCV fit statistics (R-squared, RMSE, MAPE; Tables 3-8) and kriging maps. No coefficient on any property characteristic, no SE. Prediction-only study; keep qualitatively (AI/geostatistical AVM evidence, Medellin, Colombia, 263 appraisals).",A House Price Modeling Based on Clustering and Kriging: The Medellín Case,2022.0,10.52324/001c.66198,Colombia,South America,Upper middle income,COL,4.6,-74.3,Medellín,0.0,0.0,mixed,appraisal,journal,other,"ordinary kriging (Matern, spherical, circular, Gaussian, exponential variograms) within k-means submarkets",False,False,unknown,263.0,k-means clustering;kriging,0,0
ede799d5a89d38a16239a4734a2cb00510a8c501,True,,"The COVID-19 Pandemic, Airbnb and Housing Market Dynamics in Warsaw",2021.0,10.13060/23362839.2021.8.1.524,Poland,Europe,High income,POL,51.9,19.1,"Warsaw (7 districts with Airbnb activity, incl. Srodmiescie and Wola)",2017.0,2020.0,condo_apartment,rent,journal,quantile;OLS,none (district dummies); MGWR used only for mapping rent changes,True,True,unknown,41246.0,,12,96
ee4a73efc5ad67b4400db23b09eeacbeb4812f86,False,"No hedonic coefficients printed: the paper reports only mean absolute SHAP values and permutation feature importances (Tables 3-4, temporal figures) and predictive-performance metrics (Appendix Table A1) for a log-linear regression and a random forest; the linear regression coefficients themselves are not reported (Appendix A2 gives VIFs only). Feature importances are not marginal effects and cannot enter the coefficient synthesis (keep qualitatively for the AI/AVM section).",Explainable AI-based mass appraisal: Insights from machine learning applications in Korea's residential property market,2025.0,10.3846/ijspm.2025.25137,South Korea,Asia,High income,KOR,35.9,127.8,"Seoul, Gangnam District",2006.0,2017.0,condo_apartment,transaction,journal,OLS;ML_marginal,none (Dong dummies),True,True,unknown,,random_forest;SHAP;permutation_feature_importance,0,0
eeedb48b06f3660101615bf3de6b27e1951880ee,True,,"Impact of public water supply unreliability on residential property prices in Marion County, West Virginia",2021.0,10.1017/age.2021.24,United States,North America,High income,USA,37.1,-95.7,"Marion County, West Virginia",2012.0,2017.0,single_family,transaction,journal,quantile,"spatial quantile lag model, two-stage quantile regression (Kim & Muller 2004), qregspiv (McSpatial R)",True,False,bootstrap,1985.0,,18,342
f2f2e8d4e0c68be7054271b21b3018d65c7e131c,True,,The calculation of regional index of dwelling prices in Croatia,2020.0,10.20472/efc.2020.014.013,Croatia,Europe,High income,HRV,45.1,15.2,"Croatia: Zagreb, Middle and South Adriatic, Istria and North Adriatic, Other regions",2010.0,2019.0,condo_apartment,listing,conference,OLS,none (district/county dummies),True,True,robust,4670.0,,10,30
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,True,,Impacts of Sea Level Rise on Real Estate Prices in Coastal Georgia,2020.0,10.52324/001c.11643,United States,North America,High income,USA,37.1,-95.7,"Savannah, Georgia",2007.0,2016.0,mixed,transaction,journal,OLS,none (167 six-digit ZIP code fixed effects),True,True,robust,34807.0,,2,66
f34b3a1e2f48af6ea9bd6c13d722fba48077ca05,True,,"Public Transportation Accessibility, Proximity to New York City, and Residential Property Values in New Jersey",2020.0,10.15760/hgjpa.2020.4.1.6,United States,North America,High income,USA,37.1,-95.7,New Jersey (statewide),2018.0,2018.0,mixed,transaction,journal,OLS,none,False,False,unknown,1780.0,,6,96
f8260edb97a0dbb7c5a255fca59c10da9cde8ca8,True,,Real estate listings and their usefulness for hedonic regressions,2021.0,10.1007/s00181-020-01992-3,Germany,Europe,High income,DEU,51.2,10.5,Berlin,2007.0,2015.0,single_family,transaction,journal,other,district dummies or thin-plate spline of latitude/longitude (geoadditive model),True,True,robust,80588.0,,5,38
f870a2d97f24564c545a70499dbb596627b9f607,False,"Aggregate unit of analysis: regressions use 36 neighbourhood-level observations (average price per m2 of residential compounds around shopping malls in six Beijing districts), not individual dwellings; only three regressors (log distance to mall, age, school-district rank) with the distance variable's definition and units unclear; student conference proceedings paper (ICEMGD 2025) with Table 1 lacking variable labels.","The Impact of Shopping Malls on Surrounding Housing Prices: Evidence from Beijing, China",2025.0,10.54254/2754-1169/2025.cau27161,China,Asia,Upper middle income,CHN,35.9,104.2,Beijing (six urban districts),0.0,0.0,condo_apartment,listing,conference,OLS,none,False,False,OLS,36.0,,0,0
f90cf5207d8f2a48c20e426cb00e7a3d92fecdbe,False,"Aggregate unit of analysis: individual transactions are averaged to residential-community (xiaoqu) mean prices per year (513 communities in 2012, 679 in 2016, 1,013 in 2020; p.6) and the OLS/GWR hedonic models (Table 4, p.9) are estimated on community means, not on dwelling-level prices. Table 4 reports OLS estimates with t-values and GWR mean coefficients for log community price on green ratio, plot ratio, property-management level, building age, subway dummy, quality school dummies and distances (km) to CBD, wetland park, Xiang River and green space -- extractable if community-level means are later admitted.",The Capitalization Effect of Natural Amenities on Housing Price in Urban China: New Evidence From Changsha,2022.0,10.3389/fenvs.2022.833831,China,Asia,Upper middle income,CHN,35.9,104.2,"Changsha, Hunan",2012.0,2020.0,condo_apartment,transaction,journal,OLS;GWR,"Geographically weighted regression (Gaussian adaptive kernel, AICc bandwidth) compared with global OLS",False,False,unknown,2205.0,,0,0
fb704039a7cb48f523fc8649b0477ed96bedc7f7,True,,Improved Methods for Predicting Property Prices in Hazard Prone Dynamic Markets,2016.0,10.1007/s10640-016-0076-5,United States,North America,High income,USA,37.1,-95.7,"Pitt County, North Carolina",1992.0,2002.0,single_family,transaction,journal,OLS;other,kriging of residuals (M4); log distances to amenities (M1-M2),True,False,unknown,4779.0,,3,3
fb8eee688ea40496609ebe82ad7180db4acffe2c,True,,The impact of short-term rental activity on house prices: evidence from coastal Virginia,2024.0,10.1007/s00168-024-01328-4,United States,North America,High income,USA,37.1,-95.7,"Hampton Roads, Virginia",2015.0,2019.0,mixed,transaction,journal,OLS;quantile,none (zip-code and school-district fixed effects),True,True,robust,102142.0,,36,48
fb9d007b500b1eff5cd9c2ed633d123752bd4215,True,,EPC Labels and Building Features: Spatial Implications over Housing Prices,2021.0,10.3390/su13052838,Italy,Europe,High income,ITA,41.9,12.6,Turin,2015.0,2018.0,mixed,listing,journal,OLS;spatial_error,"spatial error model (SEM), row-standardized weights",False,False,unknown,2092.0,,5,85
fc9d39b019f0526d9688d6cea3c777de313aea1d,True,,"Factors influencing the value of houses: Estimates for the city of Cagliari, Italy",2015.0,10.1016/j.landusepol.2014.08.012,Italy,Europe,High income,ITA,41.9,12.6,Cagliari (Sardinia),2013.0,2013.0,condo_apartment,appraisal,journal,spatial_lag;OLS,"spatially lagged dependent variable (500 m neighbours) included as regressor, estimated by OLS",False,False,OLS,304.0,,5,75
fdf3432efb95e96e6e45a3ba105603f17a38d366,True,,Hedonic valuation of marginal willingness to pay for air quality improvement,2012.0,10.20885/ejem.v4i2.3318,Indonesia,Asia,Upper middle income,IDN,-0.8,113.9,Yogyakarta Special Territory (Yogyakarta City and Gunungkidul high-PM10 sub-districts),2010.0,2010.0,single_family,transaction,journal,OLS,none,False,False,unknown,250.0,,2,20
fe9b5a96e7007d52e9bebe9eaea418541aa3b090,False,"Evolutionary Polynomial Regression (EPR) automated valuation models of log rent for five Italian cities (Milan, Turin, Rome, Naples, Catania; second half of 2019). The fitted equations are sums of multiplicative monomials of several variables raised to exponents (0, 0.5, 1, 2); no separable per-characteristic coefficients, no standard errors, t-statistics or p-values are reported (only CoD/RMSE/MAPE). No extractable hedonic coefficients.",An Automatic Tool for the Determination of Housing Rental Prices: An Analysis of the Italian Context,2021.0,10.3390/su14010309,Italy,Europe,High income,ITA,41.9,12.6,"Milan, Turin, Rome, Naples, Catania",2019.0,2019.0,rental,rent,journal,ML_marginal,none,False,False,unknown,,evolutionary polynomial regression (EPR),0,0