方法对比

	面板事件研究	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	1990s–2020s (modern panel formulation)	2003–2010
提出者	Formalized by Freyaldenhoven, Hansen, Perez-Orive & Shapiro (2021); widely applied in finance (Fama et al. 1969) and policy evaluation	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
类型	Quasi-experimental / causal panel design	Quasi-experimental causal inference
开创性文献	Freyaldenhoven, S., Hansen, C., Perez-Orive, J., & Shapiro, J. M. (2021). Visualization, Identification, and Estimation in the Linear Panel Event-Study Design. NBER Working Paper 29170. National Bureau of Economic Research.	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	event-study regression, dynamic DiD, relative-time regression, distributed-lag panel model	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
相关	4	4
摘要	A panel event study estimates the dynamic causal effect of a treatment or policy by regressing an outcome on a full set of relative-time indicators — one for each period before and after the event — while controlling for unit and time fixed effects. The resulting coefficient plot shows how the treated units diverged from untreated units at each point in calendar time relative to their treatment date, making both pre-treatment trend violations and post-treatment effect trajectories immediately visible.	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.