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Testing treatment effect heterogeneity in regression discontinuity designs

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  • Hsu, Yu-Chin
  • Shen, Shu

Abstract

Treatment effect heterogeneity is frequently studied in regression discontinuity (RD) applications. This paper proposes, under the RD setup, formal tests for treatment effect heterogeneity among individuals with different observed pre-treatment characteristics. The proposed tests study whether a policy treatment (1) is beneficial for at least some subpopulations defined by pre-treatment covariate values, (2) has any impact on at least some subpopulations, and (3) has a heterogeneous impact across subpopulations. The empirical section applies the tests to study the impact of attending a better high school and discovers interesting patterns of treatment effect heterogeneity neglected by previous studies.

Suggested Citation

  • Hsu, Yu-Chin & Shen, Shu, 2019. "Testing treatment effect heterogeneity in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 208(2), pages 468-486.
    • Handle: RePEc:eee:econom:v:208:y:2019:i:2:p:468-486
    DOI: 10.1016/j.jeconom.2018.10.004
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    More about this item

    Keywords

    Sharp regression discontinuity; Fuzzy regression discontinuity; Treatment effect heterogeneity;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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