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Regression discontinuity designs: a hands-on guide for practice

Published online by Cambridge University Press:  27 July 2021

Vicente Valentim ,
Ana Ruipérez Núñez  and
Elias Dinas Open the ORCID record for Elias Dinas [Opens in a new window]
Vicente Valentim
Affiliation:
Department of Political and Social Sciences, European University Institute, Villa Sanfelice, San Domenico di Fiesole, I-50014, Italy
Ana Ruipérez Núñez
Affiliation:
Department of Political and Social Sciences, European University Institute, Villa Sanfelice, San Domenico di Fiesole, I-50014, Italy
Elias Dinas*
Affiliation:
Department of Political and Social Sciences, European University Institute, Villa Sanfelice, San Domenico di Fiesole, I-50014, Italy
*
*Corresponding author. Email: [email protected]
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Abstract

Regression discontinuity (RD) designs have become increasingly popular in political science, due to their ability to showcase causal effects under weak assumptions. This paper provides an intuition-based guide for the use of the RD in applied research. After an intuitive explanation of how the method works, we provide a checklist that can help researchers understand the main robustness checks they should run, and a quick introduction to software implementing the design. We also provide a list of classic designs and examples of their application in political science. We hope this article can constitute a stepping stone from which researchers interested in RD can jump to more advanced literature; and which makes researchers not interested in implementing RDs better consumers of research employing this design.

Keywords

Causal inferencefuzzy RDpolitical methodologysharp RDteaching statistics
Type
Research Article
Information
Italian Political Science Review / Rivista Italiana di Scienza Politica , Volume 51 , Special Issue 2: Capturing Causation: Issues of Research Design in Political Science , July 2021 , pp. 250 - 268
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Società Italiana di Scienza Politica

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