方法对比

	面板数据安慰剂检验	合成控制法 (SCM)
领域	因果推断	因果推断
方法族	Regression model	Regression model
起源年份	2004-2010	2003–2010
提出者	Bertrand, Duflo & Mullainathan; Abadie, Diamond & Hainmueller	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
类型	Falsification / validation test	Quasi-experimental causal inference
开创性文献	Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How Much Should We Trust Differences-in-Differences Estimates? Quarterly Journal of Economics, 119(1), 249-275.	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.
别名	placebo regression test, falsification test, pseudo-treatment test, in-time placebo	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
相关	4	4
摘要	A panel data placebo test is a falsification procedure used to assess the credibility of causal estimates in quasi-experimental panel designs. By applying the same estimation strategy to a period, group, or outcome where no true effect should exist, researchers verify that the observed treatment effect is not merely an artifact of model specification, coincidental trends, or data patterns unrelated to the intervention.	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.