Focused Information Criterion for Propensity Score Matching Estimators
Speaker(s)Yoshiyasu Rai (University of Mannheim, Germany)
LocationUniversity of Amsterdam and online (hybrid seminar), room E5.22
Date and time
May 13, 2022
12:30 - 13:30
This paper studies the model selection problem for propensity score matching estimators of the average treatment effect (ATE) and the average treatment effect on treated (ATET). I derive the large sample distribution of propensity score matching estimators in a local asymptotic framework and characterize the asymptotic bias with respect to the first stage propensity score model choice. I show that the propensity score model choice induces a nontrivial asymptotic bias-variance trade-off for the ATET estimator. I also show that the largest propensity score model achieves the smallest asymptotic mean squared error for the ATE estimator. I then propose a focused information criterion for the propensity score matching estimator of the ATET that aims to minimize the estimated mean squared error. A simulation study indicates that the proposed method generally achieves a smaller mean squared error than other methods.