So sánh phương pháp

	Phương pháp Kiểm soát Tổng hợp Mạnh mẽ	Sai Khác Mạnh Mẽ trong Sai Khác
Lĩnh vực	Suy luận nhân quả	Suy luận nhân quả
Họ	Regression model	Regression model
Năm ra đời	2021	2021-2023
Người khởi xướng	Cattaneo, Feng & Titiunik (2021); building on Abadie, Diamond & Hainmueller (2010)	Callaway & Sant'Anna; Sun & Abraham; Roth et al. (synthesised 2021-2023)
Loại	Quasi-experimental causal inference	Causal inference / panel regression
Công trình gốc	Cattaneo, M. D., Feng, Y., & Titiunik, R. (2021). Prediction Intervals for Synthetic Control Methods. Journal of the American Statistical Association, 116(536), 1865-1880.	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	Robust SCM, Inference-robust synthetic control, Synthetic control with valid inference, SCM with prediction intervals	robust DiD, heterogeneity-robust DiD, staggered DiD, disaggregated ATT DiD
Liên quan	5	5
Tóm tắt	The robust synthetic control method extends the classic synthetic control estimator by providing statistically valid uncertainty quantification and inference. Developed by Cattaneo, Feng and Titiunik (2021), it addresses a core limitation of the original approach — the lack of formal prediction intervals — making causal conclusions more defensible when only a single treated unit is observed.	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.