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تقييم الأثر المكاني للواقع البديل (SCIE)×الانحدار الموزون جغرافيًا (GWR)×
المجالالاستدلال السببيالتحليل المكاني
العائلةRegression modelRegression model
سنة النشأة2010s2002
صاحب الطريقةCerqua, Pellegrini, and regional-science scholars building on counterfactual econometricsFotheringham, Brunsdon & Charlton
النوعQuasi-experimental / causal inferenceLocal spatial regression
المصدر التأسيسيCerqua, A., & Pellegrini, G. (2014). Do subsidies to private capital boost firms' growth? A multiple regression discontinuity design approach. Journal of Public Economics, 109, 114-126. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
الأسماء البديلةSCIE, spatial CIE, place-based counterfactual evaluation, regional counterfactual analysisGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
ذات صلة55
الملخصSpatial Counterfactual Impact Evaluation (SCIE) is a family of quasi-experimental methods that estimate the causal effect of geographically targeted policies — such as EU Cohesion Funds, enterprise zones, or place-based subsidies — by constructing a spatial counterfactual: what outcomes the treated region would have experienced without the intervention, inferred from comparable untreated regions or from discontinuities at policy boundaries.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
ScholarGateمجموعة البيانات
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  3. PUBLISHED
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ScholarGateقارن الطرق: Spatial Counterfactual Impact Evaluation · Geographically Weighted Regression. استُرجع بتاريخ 2026-06-19 من https://scholargate.app/ar/compare