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Bias-Aware Inference in Fuzzy Regression Discontinuity Designs

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  • Claudia Noack
  • Christoph Rothe

Abstract

We propose new confidence sets (CSs) for the regression discontinuity parameter in fuzzy designs. Our CSs are based on local linear regression, and are bias-aware, in the sense that they take possible bias explicitly into account. Their construction shares similarities with that of Anderson-Rubin CSs in exactly identified instrumental variable models, and thereby avoids issues with "delta method" approximations that underlie most commonly used existing inference methods for fuzzy regression discontinuity analysis. Our CSs are asymptotically equivalent to existing procedures in canonical settings with strong identification and a continuous running variable. However, due to their particular construction they are also valid under a wide range of empirically relevant conditions in which existing methods can fail, such as setups with discrete running variables, donut designs, and weak identification.

Suggested Citation

  • Claudia Noack & Christoph Rothe, 2019. "Bias-Aware Inference in Fuzzy Regression Discontinuity Designs," Papers 1906.04631, arXiv.org, revised Sep 2023.
    • Handle: RePEc:arx:papers:1906.04631
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    Cited by:

    1. Tomasz Olma, 2021. "Nonparametric Estimation of Truncated Conditional Expectation Functions," Papers 2109.06150, arXiv.org.
    2. Myung Hwan Seo & Yoichi Arai & Taisuke Otsu, 2021. "Regression Discontinuity Design with Potentially Many Covariates," Working Paper Series no142, Institute of Economic Research, Seoul National University.
    3. Alexander Krei{ss} & Christoph Rothe, 2021. "Inference in Regression Discontinuity Designs with High-Dimensional Covariates," Papers 2110.13725, arXiv.org, revised May 2022.
    4. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    5. Claudia Noack & Tomasz Olma & Christoph Rothe, 2021. "Flexible Covariate Adjustments in Regression Discontinuity Designs," Papers 2107.07942, arXiv.org, revised Dec 2024.

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