Pre-Event Trends in the Panel Event-Study Design
研究面板事件研究中，当未观测混杂因素同时影响结果和政策变量时，如何利用仅通过混杂因素与政策相关的协变量来识别因果效应，并允许结果存在事前趋势。
We consider a linear panel event-study design in which unobserved confounds may be related both to the outcome and to the policy variable of interest. We provide sufficient conditions to identify the causal effect of the policy by exploiting covariates related to the policy only through the confounds. Our model implies a set of moment equations that are linear in parameters. The effect of the policy can be estimated by 2SLS, and causal inference is valid even when endogeneity leads to pre-event trends (“pre-trends”) in the outcome. Alternative approaches perform poorly in our simulations.