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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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    Cited by:

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    2. David Wuepper & Robert Finger, 2023. "Regression discontinuity designs in agricultural and environmental economics," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(1), pages 1-28.
    3. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    4. 'Agoston Reguly, 2021. "Heterogeneous Treatment Effects in Regression Discontinuity Designs," Papers 2106.11640, arXiv.org, revised Oct 2021.
    5. Matilde Cappelletti & Leonardo M. Giuffrida & Gabriele Rovigatti, 2022. "Procuring Survival," CESifo Working Paper Series 10124, CESifo.
    6. Pedro Forquesato, 2022. "Who Benefits from Political Connections in Brazilian Municipalities," Papers 2204.09450, arXiv.org.
    7. Chen, Wei-Lin & Lin, Ming-Jen & Yang, Tzu-Ting, 2023. "Curriculum and national identity: Evidence from the 1997 curriculum reform in Taiwan," Journal of Development Economics, Elsevier, vol. 163(C).
    8. Yu‐Chin Hsu & Shu Shen, 2021. "Testing monotonicity of conditional treatment effects under regression discontinuity designs," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 346-366, April.
    9. Cappelletti, Matilde & Giuffrida, Leonardo M., 2021. "Procuring survival," ZEW Discussion Papers 21-093, ZEW - Leibniz Centre for European Economic Research.
    10. Matias D. Cattaneo & Luke Keele & Rocio Titiunik, 2021. "Covariate Adjustment in Regression Discontinuity Designs," Papers 2110.08410, arXiv.org, revised Aug 2022.
    11. Rodríguez Arenas, Jorge Leonardo, 2024. "¿Ampliando oportunidades o desigualdades? Efectos de un crédito-beca en estudiantes de bajo desempeño académico," Documentos CEDE 21189, Universidad de los Andes, Facultad de Economía, CEDE.
    12. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "Inference on many jumps in nonparametric panel regression models," Papers 2312.01162, arXiv.org, revised Aug 2024.
    13. Bansak, Kirk & Nowacki, Tobias, 2022. "Effect Heterogeneity and Causal Attribution in Regression Discontinuity Designs," SocArXiv vj34m, Center for Open Science.

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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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