1{2 "record_id": "f90cf5207d8f2a48c20e426cb00e7a3d92fecdbe",3 "eligible": false,4 "exclusion_reason": "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.",5 "study": {6 "title": "The Capitalization Effect of Natural Amenities on Housing Price in Urban China: New Evidence From Changsha",7 "year": 2022,8 "doi": "10.3389/fenvs.2022.833831",9 "country": "China",10 "region_city": "Changsha, Hunan",11 "sample_start": 2012,12 "sample_end": 2020,13 "property_type": "condo_apartment",14 "price_type": "transaction",15 "data_source": "Housing transaction records (2012, 2016, 2020) aggregated to community annual mean price; Baidu POI data",16 "document_type": "journal",17 "estimators": [18 "OLS",19 "GWR"20 ],21 "spatial_method": "Geographically weighted regression (Gaussian adaptive kernel, AICc bandwidth) compared with global OLS",22 "time_fe": false,23 "location_fe": false,24 "se_type": "unknown",25 "n_obs_total": 2205,26 "ai_methods": [],27 "notes": "Three cross-sections (2012, 2016, 2020). Dependent variable: logarithm of community mean house price (per m2 implied). Not extracted because the unit of analysis is the residential community mean."28 },29 "models": [],30 "coefficients": []31}