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Donut Regression Discontinuity Designs

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  • Cladia Noack
  • Chistoph Rothe

Abstract

We study the econometric properties of so-called donut regression discontinuity (RD) designs, a robustness exercise which involves repeating estimation and inference without the data points in some area around the treatment threshold. This approach is often motivated by concerns that possible systematic sorting of units, or similar data issues, in some neighborhood of the treatment threshold might distort estimation and inference of RD treatment effects. We show that donut RD estimators can have substantially larger bias and variance than contentional RD estimators, and that the corresponding confidence intervals can be substantially longer. We also provide a formal testing framework for comparing donut and conventional RD estimation results.

Suggested Citation

  • Cladia Noack & Chistoph Rothe, 2023. "Donut Regression Discontinuity Designs," Papers 2308.14464, arXiv.org.
    • Handle: RePEc:arx:papers:2308.14464
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    References listed on IDEAS

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    1. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    2. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    3. Michal Kolesár & Christoph Rothe, 2018. "Inference in Regression Discontinuity Designs with a Discrete Running Variable," American Economic Review, American Economic Association, vol. 108(8), pages 2277-2304, August.
    4. Alberto Abadie & Guido W. Imbens & Fanyin Zheng, 2014. "Inference for Misspecified Models With Fixed Regressors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1601-1614, December.
    5. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
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    1. Salvi, Irene & Cordier, Johannes & Kuklinski, David & Vogel, Justus & Geissler, Alexander, 2023. "Price sensitivity and demand for healthcare services: Investigating demand-side financial incentives using anonymised claims data from Switzerland," Working Paper Series in Health Economics, Management and Policy 2023-06, University of St.Gallen, School of Medicine, Chair of Healthcare Management.

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