1{2 "record_id": "21199d311319fd0034523954fb23eaaf34739428",3 "eligible": false,4 "exclusion_reason": "Regression tables (Tables 4 and 6, p. 14) regress price per m2 on three expert-weighted composite indicators (location Cl, position Cp, technical Ct) built by multi-attribute aggregation; no coefficient is attached to an identifiable property, neighbourhood, environmental or location characteristic, so nothing maps to the taxonomy.",5 "study": {6 "title": "Assessing the Impact of Urban Improvement on Housing Values: A Hedonic Pricing and Multi-Attribute Analysis Model for the Historic Centre of Venice",7 "year": 2017,8 "doi": "10.3390/buildings7040112",9 "country": "Italy",10 "region_city": "Venice (historic centre)",11 "sample_start": null,12 "sample_end": null,13 "property_type": "condo_apartment",14 "price_type": "transaction",15 "data_source": "197 apartment sales in the historic centre of Venice (real estate agents), split into touristic (85) and residents' (112) segments",16 "document_type": "journal",17 "estimators": [18 "OLS"19 ],20 "spatial_method": "none",21 "time_fe": false,22 "location_fe": false,23 "se_type": "robust",24 "n_obs_total": 197,25 "ai_methods": [],26 "notes": "Dependent variable: market price in EUR per m2 (level). OLS with HC1 robust SEs; R2 0.26 (touristic) and 0.40 (residents). Individual attributes (view, brightness, lift/floor, maintenance, finishes, flood height, noise, distance to access) enter only through the composite indicators; kept for qualitative synthesis (MOSE flood-protection valuation)."27 },28 "models": [],29 "coefficients": []30}