方法对比

	多期事件研究设计	面板事件研究
领域	因果推断	因果推断
方法族	Regression model	Regression model
起源年份	1993	1990s–2020s (modern panel formulation)
提出者	Jacobson, LaLonde & Sullivan (1993); seminal methodological treatment by Sun & Abraham (2021)	Formalized by Freyaldenhoven, Hansen, Perez-Orive & Shapiro (2021); widely applied in finance (Fama et al. 1969) and policy evaluation
类型	Quasi-experimental causal inference	Quasi-experimental / causal panel design
开创性文献	Jacobson, L. S., LaLonde, R. J., & Sullivan, D. G. (1993). Earnings losses of displaced workers. American Economic Review, 83(4), 888-909.	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.
别名	multi-period event study, dynamic event study, relative-time event study, leads-and-lags design	event-study regression, dynamic DiD, relative-time regression, distributed-lag panel model
相关	3	4
摘要	The multi-period event study design estimates causal treatment effects at each point in time relative to the treatment onset, using panel data with multiple pre- and post-treatment periods. By plotting the full path of treatment coefficients rather than a single average, it reveals how effects build up, fade, or remain stable over time — and allows formal tests of pre-treatment parallel trends across many periods simultaneously.	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.