SMU SOE Seminar (Nov 18, 2016): Testing Treatment Effect Heterogeneity in Regression Discontinuity Design

    Treatment effect heterogeneity is frequently studied in regression discontinuity (RD) applications. This paper is the first to propose tests for treatment effect heterogeneity under the RD setup. The proposed tests study whether a policy treatment is 1) beneficial for at least some subpopulations defined by covariate values, 2) has any impact on at least some subpopulations, and 3) has a heterogeneous impact across subpopulations. Compared with other methods currently adopted in applied RD studies, such as the subsample regression method and the interaction term method, our tests have the advantage of being fully nonparametric, robust to weak inference and powerful. Monte Carlo simulations show that our tests perform very well in small samples. We apply the tests to study the impact of attending a better high school and discover interesting patterns of treatment effect heterogeneity that were neglected by classic mean RD analyses.

JEL Classification: C21, C31

Keywords: Sharp regression discontinuity, fussy regression discontinuity, treatment effect heterogeneity.

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