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Design de Estudo de Evento Multiperíodo×Diferenças em Diferenças Dinâmicas×
ÁreaInferência causalInferência causal
FamíliaRegression modelRegression model
Ano de origem19932021
Autor originalJacobson, LaLonde & Sullivan (1993); seminal methodological treatment by Sun & Abraham (2021)Callaway & Sant'Anna; Sun & Abraham
TipoQuasi-experimental causal inferenceCausal inference / quasi-experimental
Fonte seminalJacobson, L. S., LaLonde, R. J., & Sullivan, D. G. (1993). Earnings losses of displaced workers. American Economic Review, 83(4), 888-909. link ↗Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗
Outros nomesmulti-period event study, dynamic event study, relative-time event study, leads-and-lags designDynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD
Relacionados34
ResumoThe multi-period event study design estimates causal treatment effects at each point in time relative to the treatment onset, using panel data with multiple pre- and post-treatment periods. By plotting the full path of treatment coefficients rather than a single average, it reveals how effects build up, fade, or remain stable over time — and allows formal tests of pre-treatment parallel trends across many periods simultaneously.Dynamic Difference-in-Differences extends the classic DiD framework to settings where units adopt treatment at different times. Rather than collapsing all variation into a single 2x2 comparison, it estimates group-time average treatment effects for each adoption cohort at each calendar period, then aggregates them into interpretable summaries of the causal effect over event time.
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ScholarGateComparar métodos: Multi-period Event Study Design · Dynamic Difference-in-Differences. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare