So sánh phương pháp

	Phương pháp Kiểm soát Tổng hợp Đa kỳ	Phương pháp Sai phân theo Sai phân Đa thời kỳ (Staggered DiD)
Lĩnh vực	Suy luận nhân quả	Suy luận nhân quả
Họ	Regression model	Regression model
Năm ra đời	2010-2021	2021
Người khởi xướng	Abadie, Diamond & Hainmueller (2010); extended to multi-period settings by Abadie (2021) and Ben-Michael et al. (2021)	Callaway & Sant'Anna; Goodman-Bacon
Loại	Quasi-experimental causal inference	Causal inference / panel regression
Công trình gốc	Abadie, A. (2021). Using synthetic controls: Feasibility, data requirements, and methodological aspects. Journal of Economic Literature, 59(2), 391-425.	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.
Tên gọi khác	multi-period SCM, extended synthetic control, synthetic control with multiple treatment periods, staggered synthetic control	staggered DiD, multi-period DiD, staggered difference-in-differences, heterogeneous timing DiD
Liên quan	5	5
Tóm tắt	The multi-period synthetic control method extends the classic synthetic control framework to settings where treatment occurs across several distinct periods or where the researcher needs to track causal effects over a prolonged post-treatment window. It constructs a weighted combination of untreated units that reproduces the treated unit's pre-treatment trajectory, then uses that synthetic counterfactual across all post-treatment periods to estimate time-varying treatment effects.	Multi-period Difference-in-Differences extends the classic two-period DiD framework to settings where units adopt treatment at different points in time. Formalised by Callaway and Sant'Anna (2021) and Goodman-Bacon (2021), it decomposes the overall treatment effect into group-time average treatment effects and addresses the bias that arises when conventional two-way fixed-effects regressions are applied to staggered adoption designs.