A Local Projections Approach to Difference‐in‐Differences
提出一种基于局部投影的双重差分方法，通过灵活设置“干净对照”条件来定义处理组和对照组，能处理负权重偏差，支持多种加权和归一化方案，可加入协变量或非吸收处理，模拟和实证显示效果良好。
ABSTRACT We propose a local projections (LPs)‐based difference‐in‐differences (DiD) approach that subsumes many of the recent solutions proposed in the literature to address possible biases arising from negative weighting. We combine LPs with a flexible “clean control” condition to define appropriate sets of treated and control units. Our proposed LP‐DiD estimator can be implemented with various weighting and normalization schemes for different target estimands, can be extended to include covariates or accommodate nonabsorbing treatment, and is simple and fast to implement. A simulation and two empirical applications demonstrate that the LP‐DiD estimator performs well in common applied settings.