Comparer des méthodes

	Étude d'événements sur données de panel robustes	Différence-en-différences (Diff-in-Diff)
Domaine	Inférence causale	Économétrie
Famille	Regression model	Regression model
Année d'origine	2021	1994
Auteur d'origine	Sun & Abraham (2021); Freyaldenhoven, Hansen, Shapiro & Weidner (2021)	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Type	Quasi-experimental / causal inference	Causal inference / panel regression
Source fondatrice	Sun, L., & Abraham, S. (2021). Estimating dynamic treatment effects in event studies with heterogeneous treatment effects. Journal of Econometrics, 225(2), 175-199.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Alias	robust event-study estimator, heteroskedasticity-robust panel event study, staggered-robust event study, robust ES design	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Apparentées	4	5
Résumé	A robust panel event study extends the standard panel event study design by applying heteroskedasticity- and autocorrelation-robust (HAC) standard errors and, where staggered treatment adoption exists, interaction-weighted estimators that remain valid even when treatment effects are heterogeneous across cohorts and time periods. It is widely used in economics, finance, and policy research to trace the dynamic causal path of an intervention.	Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.