Comparer des méthodes

	Méthode de Contrôle Synthétique des Effets Hétérogènes du Traitement	Méthode du Contrôle Synthétique (MCS)
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	2010-2021	2003–2010
Auteur d'origine	Abadie, Diamond & Hainmueller (SCM foundation); Ben-Michael, Feller & Rothstein (augmented/HTE extensions)	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Type	Quasi-experimental causal inference	Quasi-experimental causal inference
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.	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	HTE-SCM, heterogeneous SCM, heterogeneous synthetic control, SCM with HTE	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Apparentées	6	4
Résumé	The Heterogeneous Treatment Effect Synthetic Control Method (HTE-SCM) extends the classical synthetic control framework by allowing the causal effect of an intervention to vary across time periods, subgroups, or outcome dimensions rather than collapsing it to a single average estimate. It combines the counterfactual donor-pool matching logic of Abadie et al. (2010) with modern heterogeneous-effects machinery to recover time-varying or subgroup-specific treatment paths.	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.