Comparer des méthodes

	Synthèse de la méthode des différences de différences	Projections locales
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2021	2005
Auteur d'origine	Arkhangelsky, Athey, Hirshberg, Imbens, and Wager	Oscar Jorda
Type	Treatment-effect estimation	Multi-horizon regression
Source fondatrice	Arkhangelsky, D., Athey, S., Hirshberg, D. A., Imbens, G. W., & Wager, S. (2021). Synthetic difference-in-differences. American Economic Review, 111(12), 4088-4118.	Jorda, O. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161-182.
Alias	Synthetic DID, SDID	LP-IR, Multi-horizon regression
Apparentées	3	3
Résumé	Synthetic Difference-in-Differences (SDID) combines synthetic control and difference-in-differences approaches to estimate treatment effects when a policy or intervention affects one unit (country, firm) at a point in time. Introduced by Arkhangelsky et al. (2021), it improves upon both methods alone by using weighted combinations of controls to match treated units' pre-treatment trends and levels. This yields more precise and robust estimates than classical DiD or synthetic control.	Local Projections (LP) is a semi-parametric method for estimating impulse responses directly via multi-horizon regressions, bypassing VAR-model specification. Introduced by Jorda (2005), it projects outcomes h periods ahead onto current shocks and lags, producing impulse-response functions without assuming a particular lag structure or VAR order. This flexibility has made it the dominant approach in applied macroeconomics for measuring policy effects and shock transmission.