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| Sai Khác Mạnh Mẽ trong Sai Khác× | Ước lượng Sai khác-trong-Sai khác Hiệu ứng Điều trị Dị biệt (HTE-DiD)× | |
|---|---|---|
| Lĩnh vực | Suy luận nhân quả | Suy luận nhân quả |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 2021-2023 | 2021 |
| Người khởi xướng≠ | Callaway & Sant'Anna; Sun & Abraham; Roth et al. (synthesised 2021-2023) | Callaway & Sant'Anna; Sun & Abraham |
| Loại | Causal inference / panel regression | Causal inference / panel regression |
| Công trình gốc | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ |
| Tên gọi khác | robust DiD, heterogeneity-robust DiD, staggered DiD, disaggregated ATT DiD | HTE-DiD, heterogeneous DiD, CATT estimator, group-time ATT |
| Liên quan≠ | 5 | 4 |
| Tóm tắt≠ | 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. |
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