We consider a panel data analysis to examine the heterogeneity in treatment effects with respect to a pre-treatment covariate of interest in the staggered difference-in-differences setting of Callaway and Sant'Anna (2021). Under standard identification conditions, a doubly robust estimand conditional on the covariate identifies the group-time conditional average treatment effect given the covariate. Focusing on the case of a continuous covariate, we propose a three-step estimation procedure based on nonparametric local polynomial regressions and parametric estimation methods. Using uniformly valid distributional approximation results for empirical processes and multiplier bootstrapping, we develop doubly robust inference methods to construct uniform confidence bands for the group-time conditional average treatment effect function. The accompanying R package didhetero allows for easy implementation of the proposed methods.

翻译：我们考虑面板数据分析，以Callaway和Sant'Anna（2021）提出的交错差分中差分设定中，检验处理效应关于感兴趣预处理协变量的异质性。在标准识别条件下，一个关于协变量的双重稳健估计量可识别给定协变量下的群体-时间条件平均处理效应。本文聚焦连续协变量情形，提出基于非参数局部多项式回归与参数估计方法的三步估计流程。利用经验过程的统一有效分布近似理论与乘子自助法，我们发展了双重稳健推断方法，用于构建群体-时间条件平均处理效应函数的统一置信带。配套的R语言包didhetero可便捷实现所提方法。