Comparer des méthodes

	Méthode du Contrôle Synthétique en Recherche sur l'Éducation	Modèle à effets fixes pour données de panel
Domaine	Inférence causale	Économétrie
Famille	Regression model	Regression model
Année d'origine	2003-2010	2014
Auteur d'origine	Alberto Abadie, Alexis Diamond, and Jens Hainmueller	Hsiao (textbook treatment); within transformation of panel data
Type	Quasi-experimental causal inference	Panel data regression
Source fondatrice	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.	Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press.
Alias	SCM in education, synthetic control, synthetic comparator, SCM	fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Apparentées	5	5
Résumé	The Synthetic Control Method (SCM) estimates the causal effect of an education policy or intervention by constructing a weighted combination of untreated comparison units — the synthetic control — that closely mimics the treated unit's pre-intervention trajectory. Developed by Abadie, Diamond, and Hainmueller, it is especially valuable when only one or a small number of schools, districts, or countries receive a policy change and no natural comparison exists.	The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).