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Estimativa Duplamente Robusta Multi-Período×Diferenças em Diferenças Dinâmicas×
ÁreaInferência causalInferência causal
FamíliaRegression modelRegression model
Ano de origem1994-20212021
Autor originalRobins, Rotnitzky, and Zhao; extended by Bang & Robins (2005) and Callaway & Sant'Anna (2021)Callaway & Sant'Anna; Sun & Abraham
TipoSemiparametric causal estimatorCausal inference / quasi-experimental
Fonte seminalBang, H., & Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics, 61(4), 962-973. DOI ↗Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗
Outros nomeslongitudinal DR estimation, multi-period DR, multi-wave doubly robust, sequential doubly robust estimationDynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD
Relacionados64
ResumoMulti-period doubly robust (DR) estimation extends the classic doubly robust approach to longitudinal settings with multiple treatment periods and time points. It combines an outcome regression model and a propensity score model for each period, retaining consistency of the causal effect estimate as long as at least one of the two models is correctly specified at every time point.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 Doubly Robust Estimation · Dynamic Difference-in-Differences. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare