विधियों की तुलना करें

	स्थानिक प्रति-तथ्यात्मक प्रभाव मूल्यांकन (SCIE)	सिंथेटिक कंट्रोल मेथड (SCM)
क्षेत्र	कारणात्मक अनुमान	कारणात्मक अनुमान
परिवार	Regression model	Regression model
उद्भव वर्ष	2010s	2003–2010
प्रवर्तक	Cerqua, Pellegrini, and regional-science scholars building on counterfactual econometrics	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
प्रकार	Quasi-experimental / causal inference	Quasi-experimental causal inference
मौलिक स्रोत	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.	Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505.
उपनाम	SCIE, spatial CIE, place-based counterfactual evaluation, regional counterfactual analysis	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
संबंधित	5	4
सारांश	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.	The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect.