方法对比

	空间面板事件研究	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	2010s–2020s	1990s–2020s (modern panel formulation)
提出者	Synthesized from spatial econometrics and panel event-study literatures; formalized in applied work in the 2010s–2020s	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	Sun, L., & Callaway, B. (2021). Difference-in-differences estimators of intertemporal treatment effects. arXiv:2109.10157.	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	spatial event study, spatial DiD event study, geo-panel event study, spatial panel ES	event-study regression, dynamic DiD, relative-time regression, distributed-lag panel model
相关	4	4
摘要	Spatial panel event study extends the classical panel event-study design to settings where units are geographically located and outcomes may spill over across space. By combining event-time indicators with spatial weights matrices, it estimates dynamic treatment effects while explicitly accounting for spatial autocorrelation, geographic spillovers, and cross-unit contamination that would bias conventional event studies.	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.