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Robust uniform inference for quantile treatment effects in regression discontinuity designs

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  • Chiang, Harold D.
  • Hsu, Yu-Chin
  • Sasaki, Yuya

Abstract

The practical importance of inference with robustness against large bandwidths for causal effects in regression discontinuity and kink designs is widely recognized. Existing robust methods cover many cases, but do not handle uniform inference for CDF and quantile processes in fuzzy designs. In this light, this paper extends the literature by developing a unified framework of inference with robustness against large bandwidths that applies to uniform inference for quantile treatment effects in fuzzy designs, as well as all the other cases. We present Monte Carlo simulation studies and an empirical application for evaluations of the Oklahoma pre-K program.

Suggested Citation

  • Chiang, Harold D. & Hsu, Yu-Chin & Sasaki, Yuya, 2019. "Robust uniform inference for quantile treatment effects in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 211(2), pages 589-618.
  • Handle: RePEc:eee:econom:v:211:y:2019:i:2:p:589-618
    DOI: 10.1016/j.jeconom.2019.03.006
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    Cited by:

    1. Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2018. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP50/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. He, Yang & Bartalotti, Otávio, 2019. "Wild Bootstrap for Fuzzy Regression Discontinuity Designs: Obtaining Robust Bias-Corrected Confidence Intervals," IZA Discussion Papers 12801, Institute of Labor Economics (IZA).
    3. He, Yang & Bartalotti, Otávio, 2019. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals," ISU General Staff Papers 201903010800001071, Iowa State University, Department of Economics.
    4. Yingying DONG & Ying-Ying LEE & Michael GOU, 2019. "Regression Discontinuity Designs with a Continuous Treatment," Discussion papers 19058, Research Institute of Economy, Trade and Industry (RIETI).
    5. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    6. Jun Ma & Zhengfei Yu, 2020. "Coverage Optimal Empirical Likelihood Inference for Regression Discontinuity Design," Papers 2008.09263, arXiv.org.

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    More about this item

    Keywords

    Bias correction; Local Wald estimator; Multiplier bootstrap; Quantile; Regression discontinuity design; Regression kink design; Robustness;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • 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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