So sánh phương pháp

	Phương pháp Kiểm soát Tổng hợp Đa kỳ	Phương pháp Kiểm soát Tổng hợp (SCM)
Lĩnh vực	Suy luận nhân quả	Suy luận nhân quả
Họ	Regression model	Regression model
Năm ra đời	2010-2021	2003–2010
Người khởi xướng	Abadie, Diamond & Hainmueller (2010); extended to multi-period settings by Abadie (2021) and Ben-Michael et al. (2021)	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Loại	Quasi-experimental causal inference	Quasi-experimental causal inference
Công trình gốc	Abadie, A. (2021). Using synthetic controls: Feasibility, data requirements, and methodological aspects. Journal of Economic Literature, 59(2), 391-425.	Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505.
Tên gọi khác	multi-period SCM, extended synthetic control, synthetic control with multiple treatment periods, staggered synthetic control	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Liên quan	5	4
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.	The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect.