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Identification and Inference in Regression Discontinuity Designs with a Manipulated Running Variable

Author

Listed:
  • Gerard, Francois

    (Queen Mary, University of London)

  • Rokkanen, Miikka

    (Columbia University)

  • Rothe, Christoph

    (University of Mannheim)

Abstract

A key assumption in regression discontinuity analysis is that units cannot manipulate the value of their running variable in a way that guarantees or avoids assignment to the treatment. Standard identification arguments break down if this condition is violated. This paper shows that treatment effects remain partially identified in this case. We derive sharp bounds on the treatment effects, show how to estimate them, and propose ways to construct valid confidence intervals. Our results apply to both sharp and fuzzy regression discontinuity designs. We illustrate our methods by studying the effect of unemployment insurance on unemployment duration in Brazil, where we find strong evidence of manipulation at eligibility cutoffs.

Suggested Citation

  • Gerard, Francois & Rokkanen, Miikka & Rothe, Christoph, 2015. "Identification and Inference in Regression Discontinuity Designs with a Manipulated Running Variable," IZA Discussion Papers 9604, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9604
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    References listed on IDEAS

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    More about this item

    Keywords

    manipulation; treatment effects; regression discontinuity; partial identification;
    All these keywords.

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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