1{2 "record_id": "80c7a3882a0d8e30de9d0f2d3d4f1558e6df1c50",3 "eligible": false,4 "exclusion_reason": "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).",5 "study": {6 "title": "The Transitional Spatial Pattern of Housing Prices in Beijing: Factors and Implications",7 "year": 2014,8 "doi": "10.14246/irspsd.2.3_46",9 "country": "China",10 "region_city": "Beijing",11 "sample_start": 2005,12 "sample_end": 2012,13 "property_type": "condo_apartment",14 "price_type": "transaction",15 "data_source": "Average transaction prices of Beijing housing blocks, 2005 and 2012",16 "document_type": "journal",17 "estimators": [18 "OLS"19 ],20 "spatial_method": "none in regression (Moran's I / LISA exploratory)",21 "time_fe": false,22 "location_fe": false,23 "se_type": "OLS",24 "n_obs_total": null,25 "ai_methods": [],26 "notes": "Semi-log stepwise regressions (SPSS) of ln(average block price per m2) on distances to urban centre and sub-centre (km), bus stations within 800 m, subway within 1500 m, property management fee, greening ratio, plot ratio, hospital/park/key-school dummies, population density, building age and building-type dummies. Number of blocks not printed in extracted pages. Adjusted R2 0.771 (2005), 0.549 (2012)."27 },28 "models": [],29 "coefficients": []30}