• Graduate Program
    • Why study Business Data Science?
    • Research Master
    • Admissions
    • Course Registration
    • Facilities
  • Research
  • News
  • Events
  • Alumni
  • Magazine
Home | Events Archive | Focused Information Criterion for Propensity Score Matching Estimators
Seminar

Focused Information Criterion for Propensity Score Matching Estimators


  • Location
    University of Amsterdam and online (hybrid seminar), room E5.22
    Amsterdam
  • Date and time

    May 13, 2022
    12:30 - 13:30

Abstract
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.