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Méthode du Contrôle Synthétique (SCM)×Variables instrumentales par moindres carrés en deux étapes (VI/2SLS)×
DomaineInférence causaleInférence causale
FamilleRegression modelRegression model
Année d'origine20102009
Auteur d'origineAbadie, Diamond & HainmuellerAngrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)
TypeCounterfactual causal-inference modelInstrumental-variables regression
Source fondatriceAbadie, 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. DOI ↗Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Aliassynthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)instrumental variables, IV estimation, 2SLS, instrumental variable regression
Apparentées55
RésuméThe Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists.IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009).
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ScholarGateComparer des méthodes: Synthetic Control · Two-Stage Least Squares (2SLS). Consulté le 2026-06-18 sur https://scholargate.app/fr/compare