  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.
