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Quantile treatment effects in the regression discontinuity design

Author

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  • Frandsen, Brigham R.
  • Frölich, Markus
  • Melly, Blaise

Abstract

We introduce a nonparametric estimator for local quantile treatment effects in the regression discontinuity (RD) design. The procedure uses local distribution regression to estimate the marginal distributions of the potential outcomes. We illustrate the procedure through Monte Carlo simulations and an application on the distributional effects of a universal pre-K program in Oklahoma. We find that participation in a pre-K program significantly raises the lower end and the middle of the distribution of test scores.

Suggested Citation

  • Frandsen, Brigham R. & Frölich, Markus & Melly, Blaise, 2012. "Quantile treatment effects in the regression discontinuity design," Journal of Econometrics, Elsevier, vol. 168(2), pages 382-395.
  • Handle: RePEc:eee:econom:v:168:y:2012:i:2:p:382-395
    DOI: 10.1016/j.jeconom.2012.02.004
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    More about this item

    Keywords

    Quantile treatment effect; Causal effect; Endogeneity; Regression discontinuity;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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