1{2 "record_id": "7f206890031d1d54ba82515e526e51ef8c34c412",3 "eligible": false,4 "exclusion_reason": "No printed characteristic coefficients: the paper fits a structured additive distributional regression (GAMLSS-type, batchwise backfitting with regional clustering) to >1 million German apartment asking prices per m2, but reports covariate effects only graphically (effect plots, county maps) and in Table 1 (out-of-sample prediction accuracy); Tables 2-3 are descriptive statistics only. Methodological/predictive study; keep qualitatively (AI/ML section).",5 "study": {6 "title": "A Parsimonious Hedonic Distributional Regression Model for Large Data with Heterogeneous Covariate Effects",7 "year": 2025,8 "doi": "10.17713/ajs.v54i2.1904",9 "country": "Germany",10 "region_city": "Germany (national, county-level clusters)",11 "sample_start": 2016,12 "sample_end": 2022,13 "property_type": "condo_apartment",14 "price_type": "listing",15 "data_source": "Large German dataset of apartment asking prices (> 1 million listings), quarters 2016-2022Q2",16 "document_type": "journal",17 "estimators": [18 "ML_marginal",19 "other"20 ],21 "spatial_method": "model-based regional clustering of county effects; structured additive distributional regression (location and scale)",22 "time_fe": false,23 "location_fe": true,24 "se_type": "unknown",25 "n_obs_total": 0,26 "ai_methods": [27 "structured additive distributional regression (GAMLSS)",28 "batchwise backfitting",29 "boosting-type variable selection",30 "model-based clustering"31 ],32 "notes": "Dependent variable log(price per square metre). n_obs_total not printed exactly (stated as over one million)."33 },34 "models": [],35 "coefficients": []36}