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Χωρική Αντιπαραθετική Αξιολόγηση Επιπτώσεων (SCIE)×Παλινδρόμηση Γεωγραφικά Σταθμισμένη (GWR)×
ΠεδίοΑιτιακή ΣυμπερασματολογίαΧωρική Ανάλυση
ΟικογένειαRegression modelRegression model
Έτος προέλευσης2010s2002
ΔημιουργόςCerqua, Pellegrini, and regional-science scholars building on counterfactual econometricsFotheringham, Brunsdon & Charlton
ΤύποςQuasi-experimental / causal inferenceLocal spatial regression
Θεμελιώδης πηγήCerqua, 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
Εναλλακτικές ονομασίεςSCIE, spatial CIE, place-based counterfactual evaluation, regional counterfactual analysisGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Συναφείς55
ΣύνοψηSpatial 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.
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ScholarGateΣύγκριση μεθόδων: Spatial Counterfactual Impact Evaluation · Geographically Weighted Regression. Ανακτήθηκε στις 2026-06-19 από https://scholargate.app/el/compare