undidR - Difference-in-Differences with Unpoolable Data

A framework for estimating difference-in-differences with unpoolable data, based on Karim, Webb, Austin, and Strumpf (2024) <doi:10.48550/arXiv.2403.15910>. Supports common or staggered adoption, multiple groups, and the inclusion of covariates. Also computes p-values for the aggregate average treatment effect on the treated via the randomization inference procedure described in MacKinnon and Webb (2020) <doi:10.1016/j.jeconom.2020.04.024>.