Universal Treatment Designs with Auxiliary Outcomes

Nicholas Brown, Kyle Butts, and Irene Botosaru

We study causal effects when treatment is universal under a factor model. We propose an imputation-style treatment effect estimator that uses auxiliary variables that are known to not be impacted by treatment but subject to the same factor model.