{
 "record_id": "23a821c97160e852a6c2dd5c6097aa79bfac7ed3",
 "eligible": false,
 "exclusion_reason": "Aggregate unit of analysis: 1498 residential price samples averaged into 653 sample-area means (Shunde District, Foshan, China, 1999/2001-2010, Yuan/m2, calibrated to 2010 level) and modelled with a flexible spatiotemporal mixed model (FSTM) built for spatial prediction. The only coefficient table (Table 1, p.15: level Yuan/m2 on distance to centre, road/market/bus/telecom/supermarket/post/bank densities, public area, shared area, 2003 population density; SE and p-values printed, units of regressors undefined) contains no dwelling characteristic coefficients and the regressors are area-level densities with unstated units. Not usable for coefficient synthesis; keep as qualitative (ML/spatiotemporal prediction) evidence.",
 "study": {
  "title": "Prediction and analysis of residential house price using a flexible spatiotemporal model",
  "year": 2022,
  "doi": "10.1080/15140326.2022.2045466",
  "country": "China",
  "region_city": "Shunde District, Foshan, Guangdong",
  "sample_start": 2001,
  "sample_end": 2010,
  "property_type": "unknown",
  "price_type": "transaction",
  "data_source": "Shunde District residential house price database / real estate transaction system and Land Bureau land price updating database; 1498 samples in 653 sample areas",
  "document_type": "journal",
  "estimators": [
   "other"
  ],
  "spatial_method": "flexible spatiotemporal mixed-effects model (FSTM, random coefficients, Gaussian Markov random fields, ML)",
  "time_fe": true,
  "location_fe": false,
  "se_type": "unknown",
  "n_obs_total": 653,
  "ai_methods": [],
  "notes": "Dependent variable: residential house price per m2 (Chinese Yuan/m2, level) averaged by sample area; year factor dummies 2002-2010 reported. Table 1 (p.15) reports coefficient, standard error and p-value. Prediction accuracy via 10-fold CV (RMSE 2087 Yuan/m2, R2 0.275)."
 },
 "models": [],
 "coefficients": []
}