A0224
Title: Optimal estimation of average treatment effect on the treated under endogeneous treatment assignment
Authors: Trinetri Ghosh - University of Wisconsin-Madison (United States) [presenting]
Menggang Yu - University of Wisconsin - Madison (United States)
Jiwei Zhao - University of Wisconsin-Madison (United States)
Abstract: When evaluating a complex intervention, instead of average treatment effect (ATE), researchers are more interested in the average treatment effect on the treated (ATT), which is the quantity most relevant to policymakers. We consider the ATT estimation motivated by a case study, where the treatment assignment might depend on the potential untreated outcome and hence is endogenous. We study the scenario that the ATT can be identified. We investigate the optimal estimation of ATT by characterizing the geometric structure of the model. We derive the semiparametric efficiency bound for ATT estimation and propose an estimator that can achieve this bound. Consistency and asymptotic normality of the proposed estimator are established. The finite-sample performance of the proposed estimator is studied through comprehensive simulations and an application to our motivated study.
