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Doubly Robust Estimation of Treatment Effects in Staggered Difference-in-Differences with Time-Varying Covariates
The difference-in-differences (DiD) design is a quasi-experimental method for estimating treatment effects from panel data. With staggered adoption, the average treatment effect on the treated (ATT) is defined at the group-period level and aggregated into groupwise, periodwise, dynamic, and overall
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