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Focused Information Criterion for Propensity Score Matching Estimators

  • Series
    Econometrics Seminars and Workshop Series
  • Speaker(s)
    Yoshiyasu Rai (University of Mannheim, Germany)
  • Field
  • Location
    University 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.