1{2 "record_id": "c7b242d28013321bceaeef0f994fd2d0dab032c0",3 "eligible": true,4 "exclusion_reason": null,5 "study": {6 "title": "Implicit Prices in Urban Real Estate Valuation",7 "year": 2013,8 "doi": "10.4067/s0718-915x2013000200009",9 "country": "Spain",10 "region_city": "Cordoba",11 "sample_start": 0,12 "sample_end": 0,13 "property_type": "condo_apartment",14 "price_type": "transaction",15 "data_source": "Random sample of 2,888 resale transactions of flats and apartments over a one-year period, obtained from real-estate brokerage companies in Cordoba",16 "document_type": "journal",17 "estimators": [18 "OLS"19 ],20 "spatial_method": "none",21 "time_fe": false,22 "location_fe": false,23 "se_type": "unknown",24 "n_obs_total": 2888,25 "ai_methods": [26 "ANN"27 ],28 "notes": "Revista de la Construccion 12(2) 116-126. Linear hedonic model in price levels (euros) with composite [0,1] indices (location, annexes) and one interaction term; compared with a 6:6-6-1:1 MLP neural network (R2 0.8605 vs 0.7738; no coefficients). Sample year not stated ('a year period'; paper 2013). Table 3 does not print N; study-level n assumed = 2,888 sample (ANN uses 80% training split)."29 },30 "models": [31 {32 "model_id": "T3-c1",33 "table": "3",34 "column": "1",35 "page": 7,36 "dep_var": "Sales price (euros)",37 "dep_transform": "level",38 "estimator": "OLS",39 "n_obs": 2888,40 "r2": 0.7738,41 "se_or_t_in_parentheses": "se",42 "sample_subset": "Full sample of 2,888 resale flats, Cordoba; parsimonious linear specification with Pav x Carp interaction; R2 0.7738 from text"43 }44 ],45 "coefficients": [46 {47 "model_id": "T3-c1",48 "var_name_printed": "Surface",49 "taxonomy_id": "living_area",50 "x_transform": "level",51 "x_unit": "m2",52 "beta": 1109.951,53 "se": 83.6205,54 "t": 13.27368,55 "p": 0.0,56 "p_stars": "",57 "ci_lo": null,58 "ci_hi": null,59 "page": 7,60 "confidence": "high",61 "notes": "size of the flat in m2 including common areas; Table 3 columns: Coefficients, Standard error, t-Student, Prob.; dependent variable = sales price in euros (level)"62 },63 {64 "model_id": "T3-c1",65 "var_name_printed": "Age",66 "taxonomy_id": "age",67 "x_transform": "level",68 "x_unit": "years",69 "beta": -1067.449,70 "se": 173.5725,71 "t": -6.149872,72 "p": 0.0,73 "p_stars": "",74 "ci_lo": null,75 "ci_hi": null,76 "page": 7,77 "confidence": "high",78 "notes": "age of the building in years; Table 3 columns: Coefficients, Standard error, t-Student, Prob.; dependent variable = sales price in euros (level)"79 },80 {81 "model_id": "T3-c1",82 "var_name_printed": "Location",83 "taxonomy_id": "other",84 "x_transform": "level",85 "x_unit": "index",86 "beta": 64297.29,87 "se": 5494.403,88 "t": 11.70232,89 "p": 0.0,90 "p_stars": "",91 "ci_lo": null,92 "ci_hi": null,93 "page": 7,94 "confidence": "medium",95 "notes": "location index scaled to [0,1]: position in the city, characteristics of the area and income level of the zone (33 income zones); Table 3 columns: Coefficients, Standard error, t-Student, Prob.; dependent variable = sales price in euros (level)"96 },97 {98 "model_id": "T3-c1",99 "var_name_printed": "Annexes",100 "taxonomy_id": "other",101 "x_transform": "level",102 "x_unit": "index",103 "beta": 18458.66,104 "se": 4572.246,105 "t": 4.037111,106 "p": 0.0001,107 "p_stars": "",108 "ci_lo": null,109 "ci_hi": null,110 "page": 7,111 "confidence": "medium",112 "notes": "annex index scaled to [0,1] combining garage and store room (closest leaf would be garage, but composite); Table 3 columns: Coefficients, Standard error, t-Student, Prob.; dependent variable = sales price in euros (level)"113 },114 {115 "model_id": "T3-c1",116 "var_name_printed": "Expenses",117 "taxonomy_id": "other",118 "x_transform": "level",119 "x_unit": "currency",120 "beta": 1296.708,121 "se": 105.9213,122 "t": 12.24218,123 "p": 0.0,124 "p_stars": "",125 "ci_lo": null,126 "ci_hi": null,127 "page": 7,128 "confidence": "medium",129 "notes": "community (common) expenses in euros (period not stated, presumably monthly); Table 3 columns: Coefficients, Standard error, t-Student, Prob.; dependent variable = sales price in euros (level)"130 },131 {132 "model_id": "T3-c1",133 "var_name_printed": "Pav xCarp",134 "taxonomy_id": "other",135 "x_transform": "other",136 "x_unit": "index",137 "beta": 5117.27,138 "se": 504.0529,139 "t": 10.15225,140 "p": 0.0,141 "p_stars": "",142 "ci_lo": null,143 "ci_hi": null,144 "page": 7,145 "confidence": "medium",146 "notes": "interaction between quality indices of pavement (flooring) condition and external carpentry (windows); Table 3 columns: Coefficients, Standard error, t-Student, Prob.; dependent variable = sales price in euros (level)"147 }148 ]149}