Comparer des méthodes

	Évaluation d'impact contrefactuelle en recherche sur l'éducation	Méthode du Contrôle Synthétique (MCS)
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	2000s–2010s	2003–2010
Auteur d'origine	Blundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research Centre	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Type	Quasi-experimental causal inference framework	Quasi-experimental causal inference
Source fondatrice	Blundell, R., & Costa Dias, M. (2002). Alternative approaches to evaluation in empirical microeconomics. Portuguese Economic Journal, 1(2), 91-115.	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.
Alias	CIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluation	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Apparentées	5	4
Résumé	Counterfactual impact evaluation (CIE) is the systematic application of causal inference designs — such as difference-in-differences, regression discontinuity, matching, and instrumental variables — to measure the genuine effect of education programs, policies, or interventions by constructing a credible counterfactual: what would have happened to participants had they not been treated.	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.