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DRDID

Doubly Robust Difference-in-Differences Estimators

v1.2.3 · Dec 3, 2025 · GPL-3

Description

Implements the locally efficient doubly robust difference-in-differences (DiD) estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) <doi:10.1016/j.jeconom.2020.06.003>. The estimator combines inverse probability weighting and outcome regression estimators (also implemented in the package) to form estimators with more attractive statistical properties. Two different estimation methods can be used to estimate the nuisance functions.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Reverse Dependencies (2)

imports

Dependency Network

Dependencies Reverse dependencies trust BMisc Rcpp fastglm (>= 0.0.3) did ptetools DRDID

Version History

new 1.2.3 Mar 9, 2026