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Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals

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  • He, Yang
  • Bartalotti, Otávio

Abstract

This paper develops a novel wild bootstrap procedure to construct robust bias-corrected valid confidence intervals for fuzzy regression discontinuity designs, providing an intuitive complement to existing robust bias-corrected methods. The confidence intervals generated by this procedure are valid under conditions similar to the procedures proposed by Calonico et al. (2014) and related literature. Simulations provide evidence that this new method is at least as accurate as the plug-in analytical corrections when applied to a variety of data-generating processes featuring endogeneity and clustering. Finally, we demonstrate its empirical relevance by revisiting Angrist and Lavy (1999) analysis of class size on student outcomes.

Suggested Citation

  • He, Yang & Bartalotti, Otávio, 2020. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals," ISU General Staff Papers 202005010700001071, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genstf:202005010700001071
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    Cited by:

    1. Carolina Caetano & Gregorio Caetano & Leonard Goff & Eric Nielsen, 2025. "Identification of Causal Effects with a Bunching Design," Papers 2507.05210, arXiv.org.
    2. Ellegård, Lina Maria & Kjellsson, Gustav & Mattisson, Linn, 2021. "An App Call a Day Keeps the Patient Away? Substitution of Online and In-Person Doctor Consultations Among Young Adults," Working Papers in Economics 808, University of Gothenburg, Department of Economics, revised May 2022.
    3. Chen, Yen-Chien & Fan, Elliott & Ho, Yu-Hsin & Lee, Matthew Yi-Hsiu & Liu, Jin-Tan, 2025. "The impact of female political leadership on gender attitudes: Evidence from Taiwan’s local councils," Journal of Development Economics, Elsevier, vol. 174(C).
    4. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    5. Sefa Awaworyi Churchill & Nasir Iqbal & Saima Nawaz & Siew Ling Yew, 2024. "Do unconditional cash transfers increase fertility? Lessons from a large‐scale program," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 74-96, January.
    6. Richard Bluhm & Maxim Pinkovskiy, 2021. "The spread of COVID-19 and the BCG vaccine: A natural experiment in reunified Germany," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 353-376.
    7. Chen, Yen-Chien & Fan, Elliott & Ho, Yu-Hsin & Lee, Matthew Yi-Hsiu & Liu, Jin-Tan, 2023. "How Does Gender Quota Shape Gender Attitudes?," IZA Discussion Papers 16331, Institute of Labor Economics (IZA).

    More about this item

    JEL classification:

    • 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
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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