{
 "record_id": "036af7575382c2b07d715add3e591d6f0d1ad955",
 "eligible": false,
 "exclusion_reason": "Aggregate unit of analysis: cross-section of 985 Italian railway station areas; dependent variable is the average OMI (Osservatorio del Mercato Immobiliare) residential quotation in euro/m2 for the 1 km area around each station (mean ~1,280 euro/m2), regressed on station/municipal features and CFA latent constructs (Table 7, p. 11). No dwelling-level transactions and no property characteristic coefficients.",
 "study": {
  "title": "Modelling Real-Estate Values Around Railway Stations: Insights from an Italian Case",
  "year": 2026,
  "doi": "10.3390/su18052304",
  "country": "Italy",
  "region_city": "Nationwide (985 RFI railway stations)",
  "sample_start": null,
  "sample_end": null,
  "property_type": "unknown",
  "price_type": "appraisal",
  "data_source": "OMI Quotazioni Immobiliari (zone average residential prices), RFI station data, ISTAT municipal data",
  "document_type": "journal",
  "estimators": [
   "OLS"
  ],
  "spatial_method": "none",
  "time_fe": false,
  "location_fe": false,
  "se_type": "OLS",
  "n_obs_total": 985,
  "ai_methods": [],
  "notes": "Sustainability 2026, 18, 2304. MLR with latent variables from confirmatory factor analysis; adjusted R2 = 0.888, F(12,973)=651.5. OMI data accessed January 2025 (quotation period not stated). Kept qualitatively for transit accessibility capitalisation (station centrality, long-distance rail supply, shared mobility positive; car catchment negative)."
 },
 "models": [],
 "coefficients": []
}