1{2 "record_id": "009443a37464c7bfc0c1892b4c485e939d19af7c",3 "eligible": false,4 "exclusion_reason": "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.",5 "study": {6 "title": "Testing Housing Price Drivers in Santiago de Chile: A Hedonic Price Approach",7 "year": 2023,8 "doi": "10.13060/23362839.2023.10.2.558",9 "country": "Chile",10 "region_city": "Greater Santiago",11 "sample_start": 2008,12 "sample_end": 2018,13 "property_type": "mixed",14 "price_type": "transaction",15 "data_source": "Real Estate Register Service of Santiago via inciti.com (456,133 official transactions aggregated monthly) plus Central Bank of Chile macro series",16 "document_type": "journal",17 "estimators": ["OLS"],18 "spatial_method": "none",19 "time_fe": false,20 "location_fe": false,21 "se_type": "OLS",22 "n_obs_total": 0,23 "ai_methods": [],24 "notes": "Critical Housing Analysis 10(2), 44-57. Monthly aggregate series (~130 observations; exact n not printed). Table 4 full model (R2 0.6074) and Table 5 reduced model print coefficient, SE, t, p, VIF. For reference: average age of residential building -0.006 (0.002) t=-2.241 p=0.027 (Table 4) and -0.005 (0.002) t=-2.286 p=0.024 (Table 5); average m2 not significant; IDSE 14.214 (1.940) and 15.159 (1.617)."25 },26 "models": [],27 "coefficients": []28}29