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Estudo de Eventos em Painel Robusto×Diferenças em Diferenças (DiD)×
ÁreaInferência causalEconometria
FamíliaRegression modelRegression model
Ano de origem20211994
Autor originalSun & Abraham (2021); Freyaldenhoven, Hansen, Shapiro & Weidner (2021)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipoQuasi-experimental / causal inferenceCausal inference / panel regression
Fonte seminalSun, L., & Abraham, S. (2021). Estimating dynamic treatment effects in event studies with heterogeneous treatment effects. Journal of Econometrics, 225(2), 175-199. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Outros nomesrobust event-study estimator, heteroskedasticity-robust panel event study, staggered-robust event study, robust ES designdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionados45
ResumoA 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.
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ScholarGateComparar métodos: Robust Panel Event Study · Difference-in-Differences. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare