Estimating Average Treatment Effects via Orthogonal Regularization
Estimating Average Treatment Effects via Orthogonal Regularization
Decision-making often requires accurate estimation of treatment effects from observational data. This is challenging as outcomes of alternative decisions are not observed and have to be estimated. Previous methods estimate outcomes based on unconfoundedness but neglect any constraints that unconfoundedness imposes on the outcomes. In this paper, we propose a …