手法を比較

	空間的反事実影響評価（SCIE）	地理的に重み付けされた回帰分析 (GWR)
分野	因果推論	空間分析
系統	Regression model	Regression model
提唱年	2010s	2002
提唱者	Cerqua, Pellegrini, and regional-science scholars building on counterfactual econometrics	Fotheringham, Brunsdon & Charlton
種類	Quasi-experimental / causal inference	Local spatial regression
原典	Cerqua, 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.	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
別名	SCIE, spatial CIE, place-based counterfactual evaluation, regional counterfactual analysis	GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
関連	5	5
概要	Spatial 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.