On event studies and distributed‐lags in two‐way fixed effects models: Identification, equivalence, and generalization
讨论了事件研究设计的三个重要性质：通过分箱识别动态处理效应、分箱端点与分布滞后模型的数值等价性、以及将经典虚拟变量事件研究推广到多处理情形，并用失业救济金时长对求职努力影响的实例展示其实用价值。
Summary We discuss three important properties of panel data event study designs. First, assuming constant treatment effects before and/or after some event time, also known as binning, is a natural restriction, which identifies dynamic treatment effects in the absence of never‐treated units. Second, event study designs with binned endpoints and distributed‐lag models are numerically identical. Third, classic dummy variable event study designs can be generalized to models that account for multiple treatments of different signs and varying intensities. We demonstrate the practical relevance of our methodological points in an application studying the effects of unemployment benefit duration on job search effort.