1{2 "record_id": "549587ac03dcb9d550c7fe68da027277dd876b12",3 "eligible": true,4 "exclusion_reason": null,5 "study": {6 "title": "A divide-and-conquer approach for spatio-temporal analysis of large house price data from Greater London",7 "year": 2024,8 "doi": "10.1007/s10479-025-06889-x",9 "country": "United Kingdom",10 "region_city": "Greater London (983 MSOAs)",11 "sample_start": 2011,12 "sample_end": 2019,13 "property_type": "mixed",14 "price_type": "transaction",15 "data_source": "England house price transactions (Land Registry-type records) merged with EPC attributes; 651,202 transactions, 106 monthly periods Jan 2011-Oct 2019",16 "document_type": "journal",17 "estimators": [18 "other"19 ],20 "spatial_method": "Bayesian spatio-temporal Gaussian process (separable Matern/exponential space-time error process), divide-and-conquer with Wasserstein barycenter combination (D&C-STBD)",21 "time_fe": false,22 "location_fe": false,23 "se_type": "unknown",24 "n_obs_total": 651202,25 "ai_methods": [],26 "notes": "arXiv 2407.15905 / Annals of Operations Research. Dependent variable = log(house price per square metre); covariates include linear and quadratic time trends and trend x CO2 interaction (not extracted). Only the proposed D&C-STBD model has a coefficient table (Table 2, p.17, posterior means with 95% credible intervals). Benchmark models (simple hedonic OLS, spatial hedonic with region FE, temporal, SBD, D&C-SBD) are reported only through fit statistics in Table 3 (p.19): R2 0.166 / 0.605 / 0.173 / 0.744 / 0.739 / 0.796; their coefficients are not printed. Newly built properties (<1%) excluded."27 },28 "models": [29 {30 "model_id": "T2-c1",31 "table": "2",32 "column": "Estimate",33 "page": 17,34 "dep_var": "log(house price per square meter)",35 "dep_transform": "per_m2",36 "estimator": "other",37 "n_obs": 651202,38 "r2": 0.796,39 "se_or_t_in_parentheses": "none",40 "sample_subset": "full data, 983 MSOAs x 106 months",41 "notes": "Bayesian spatio-temporal Gaussian process model (D&C-STBD), Gibbs sampling, 20 subsets combined by Wasserstein barycenter. Table reports posterior mean and 95% credible interval (no SE/t). Dependent variable is log-transformed price per m2. R2 = 0.796 from Table 3 p.19 (in-sample fit)."42 }43 ],44 "coefficients": [45 {46 "model_id": "T2-c1",47 "var_name_printed": "log (1 + Area)",48 "taxonomy_id": "living_area",49 "x_transform": "log",50 "x_unit": "m2",51 "beta": -0.319,52 "se": null,53 "t": null,54 "p": null,55 "p_stars": "",56 "ci_lo": -0.321,57 "ci_hi": -0.316,58 "page": 17,59 "confidence": "high",60 "notes": "Bayesian posterior mean; 95% credible interval. total floor area in m2, entered as log(1+Area); dependent is log price per m2"61 },62 {63 "model_id": "T2-c1",64 "var_name_printed": "Rooms (3 Rooms)",65 "taxonomy_id": "bedrooms",66 "x_transform": "dummy",67 "x_unit": "count",68 "beta": 0.066,69 "se": null,70 "t": null,71 "p": null,72 "p_stars": "",73 "ci_lo": 0.065,74 "ci_hi": 0.068,75 "page": 17,76 "confidence": "high",77 "notes": "Bayesian posterior mean; 95% credible interval. number of rooms category; reference = <=2 rooms (cat1)"78 },79 {80 "model_id": "T2-c1",81 "var_name_printed": "Rooms (4 Rooms)",82 "taxonomy_id": "bedrooms",83 "x_transform": "dummy",84 "x_unit": "count",85 "beta": 0.059,86 "se": null,87 "t": null,88 "p": null,89 "p_stars": "",90 "ci_lo": 0.057,91 "ci_hi": 0.062,92 "page": 17,93 "confidence": "high",94 "notes": "Bayesian posterior mean; 95% credible interval. number of rooms category; reference = <=2 rooms (cat1)"95 },96 {97 "model_id": "T2-c1",98 "var_name_printed": "Rooms (5 Rooms)",99 "taxonomy_id": "bedrooms",100 "x_transform": "dummy",101 "x_unit": "count",102 "beta": 0.064,103 "se": null,104 "t": null,105 "p": null,106 "p_stars": "",107 "ci_lo": 0.061,108 "ci_hi": 0.067,109 "page": 17,110 "confidence": "high",111 "notes": "Bayesian posterior mean; 95% credible interval. number of rooms category; reference = <=2 rooms (cat1)"112 },113 {114 "model_id": "T2-c1",115 "var_name_printed": "Rooms (> 5 Rooms)",116 "taxonomy_id": "bedrooms",117 "x_transform": "dummy",118 "x_unit": "count",119 "beta": 0.109,120 "se": null,121 "t": null,122 "p": null,123 "p_stars": "",124 "ci_lo": 0.106,125 "ci_hi": 0.113,126 "page": 17,127 "confidence": "high",128 "notes": "Bayesian posterior mean; 95% credible interval. number of rooms category; reference = <=2 rooms (cat1)"129 },130 {131 "model_id": "T2-c1",132 "var_name_printed": "Property type (Terraced)",133 "taxonomy_id": "dwelling_type",134 "x_transform": "dummy",135 "x_unit": "binary",136 "beta": -0.052,137 "se": null,138 "t": null,139 "p": null,140 "p_stars": "",141 "ci_lo": -0.054,142 "ci_hi": -0.05,143 "page": 17,144 "confidence": "high",145 "notes": "Bayesian posterior mean; 95% credible interval. reference = Semi-detached"146 },147 {148 "model_id": "T2-c1",149 "var_name_printed": "Property type (Detached)",150 "taxonomy_id": "dwelling_type",151 "x_transform": "dummy",152 "x_unit": "binary",153 "beta": 0.141,154 "se": null,155 "t": null,156 "p": null,157 "p_stars": "",158 "ci_lo": 0.138,159 "ci_hi": 0.144,160 "page": 17,161 "confidence": "high",162 "notes": "Bayesian posterior mean; 95% credible interval. reference = Semi-detached"163 },164 {165 "model_id": "T2-c1",166 "var_name_printed": "Property type (Flats)",167 "taxonomy_id": "dwelling_type",168 "x_transform": "dummy",169 "x_unit": "binary",170 "beta": -0.25,171 "se": null,172 "t": null,173 "p": null,174 "p_stars": "",175 "ci_lo": -0.252,176 "ci_hi": -0.247,177 "page": 17,178 "confidence": "high",179 "notes": "Bayesian posterior mean; 95% credible interval. reference = Semi-detached"180 },181 {182 "model_id": "T2-c1",183 "var_name_printed": "Fireplace",184 "taxonomy_id": "fireplace",185 "x_transform": "binary",186 "x_unit": "binary",187 "beta": 0.064,188 "se": null,189 "t": null,190 "p": null,191 "p_stars": "",192 "ci_lo": 0.062,193 "ci_hi": 0.065,194 "page": 17,195 "confidence": "high",196 "notes": "Bayesian posterior mean; 95% credible interval."197 },198 {199 "model_id": "T2-c1",200 "var_name_printed": "Ventilation (Extract-only)",201 "taxonomy_id": null,202 "x_transform": "dummy",203 "x_unit": "binary",204 "beta": 0.029,205 "se": null,206 "t": null,207 "p": null,208 "p_stars": "",209 "ci_lo": 0.022,210 "ci_hi": 0.036,211 "page": 17,212 "confidence": "high",213 "notes": "Bayesian posterior mean; 95% credible interval. mechanical ventilation type, reference = Natural ventilation; no taxonomy leaf (unmapped)"214 },215 {216 "model_id": "T2-c1",217 "var_name_printed": "Ventilation (Both supply and extract)",218 "taxonomy_id": null,219 "x_transform": "dummy",220 "x_unit": "binary",221 "beta": 0.055,222 "se": null,223 "t": null,224 "p": null,225 "p_stars": "",226 "ci_lo": 0.043,227 "ci_hi": 0.065,228 "page": 17,229 "confidence": "high",230 "notes": "Bayesian posterior mean; 95% credible interval. mechanical ventilation type, reference = Natural ventilation; no taxonomy leaf (unmapped)"231 },232 {233 "model_id": "T2-c1",234 "var_name_printed": "Wind turbine",235 "taxonomy_id": "energy_efficiency",236 "x_transform": "binary",237 "x_unit": "binary",238 "beta": 0.006,239 "se": null,240 "t": null,241 "p": null,242 "p_stars": "",243 "ci_lo": -0.019,244 "ci_hi": 0.031,245 "page": 17,246 "confidence": "high",247 "notes": "Bayesian posterior mean; 95% credible interval. EPC indicator: 1 if the property has a wind turbine (on-site renewable), not a nearby wind farm; mapped to energy_efficiency"248 },249 {250 "model_id": "T2-c1",251 "var_name_printed": "log (1 + CO2 emission)",252 "taxonomy_id": "energy_efficiency",253 "x_transform": "log",254 "x_unit": "kg/m2/year",255 "beta": -0.031,256 "se": null,257 "t": null,258 "p": null,259 "p_stars": "",260 "ci_lo": -0.035,261 "ci_hi": -0.028,262 "page": 17,263 "confidence": "high",264 "notes": "Bayesian posterior mean; 95% credible interval. CO2 emissions per year (kg/m2) from EPC, entered as log(1+x); main effect only (interaction with linear time trend = 0.076 (0.070, 0.081) not extracted)"265 }266 ]267}