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Manipulation-Robust Regression Discontinuity Designs

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  • Takuya Ishihara
  • Masayuki Sawada

Abstract

We present a new identification condition for regression discontinuity designs. We replace the local randomization of Lee (2008) with two restrictions on its threat, namely, the manipulation of the running variable. Furthermore, we provide the first auxiliary assumption of McCrary's (2008) diagnostic test to detect manipulation. Based on our auxiliary assumption, we derive a novel expression of moments that immediately implies the worst-case bounds of Gerard, Rokkanen, and Rothe (2020) and an enhanced interpretation of their target parameters. We highlight two issues: an overlooked source of identification failure, and a missing auxiliary assumption to detect manipulation. In the case studies, we illustrate our solution to these issues using institutional details and economic theories.

Suggested Citation

  • Takuya Ishihara & Masayuki Sawada, 2020. "Manipulation-Robust Regression Discontinuity Designs," Papers 2009.07551, arXiv.org, revised Oct 2023.
    • Handle: RePEc:arx:papers:2009.07551
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    Cited by:

    1. Koki Fusejima & Takuya Ishihara & Masayuki Sawada, 2022. "Joint diagnostic test of regression discontinuity designs: multiple testing problem," Papers 2205.04345, arXiv.org, revised Oct 2023.

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