Сравнение методов

	Робастные оценки разности разностей (Robust Difference-in-Differences)	Различия в различиях гетерогенных эффектов воздействия (HTE-DiD)
Область	Причинно-следственный вывод	Причинно-следственный вывод
Семейство	Regression model	Regression model
Год появления	2021-2023	2021
Автор метода	Callaway & Sant'Anna; Sun & Abraham; Roth et al. (synthesised 2021-2023)	Callaway & Sant'Anna; Sun & Abraham
Тип	Causal inference / panel regression	Causal inference / panel regression
Основополагающий источник	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.
Другие названия	robust DiD, heterogeneity-robust DiD, staggered DiD, disaggregated ATT DiD	HTE-DiD, heterogeneous DiD, CATT estimator, group-time ATT
Связанные	5	4
Сводка	Robust Difference-in-Differences is a family of modern DiD estimators designed to remain valid when treatment timing is staggered across units and treatment effects are heterogeneous over time or across groups. Classical two-way fixed-effects (TWFE) DiD can be severely biased in such settings; robust variants estimate group-time average treatment effects (ATTs) separately and then aggregate them in a theoretically sound way.	HTE-DiD extends the classic Difference-in-Differences estimator to settings where treatment effects vary across units, time periods, or treatment cohorts. Developed formally by Callaway and Sant'Anna (2021) and Sun and Abraham (2021), it avoids the biases that arise when a conventional two-way fixed-effects regression is used with staggered adoption or effect heterogeneity, by estimating cohort-and-time-specific average treatment effects that can then be aggregated flexibly.