A Practical Introduction to Regression Discontinuity Designs

By M. D. Cattaneo, N. Idrobo, R. Titiunik. 2019

625 citations recorded by the source corpus.

In this Element and its accompanying Element, Matias D. Cattaneo, Nicolas Idrobo, and Rocio Titiunik provide an accessible and practical guide for the analysis and interpretation of Regression Discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. In this Element, the authors discuss the foundations of the canonical Sharp RD design, which has the following features: (i) the score is continuously distributed and has only one dimension, (ii) there is only one cutoff, and (iii) compliance with the treatment assignment is perfect. In the accompanying Element, the authors discuss practical and conceptual extensions to the basic RD setup.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3c012e3515533dd42a3ea4fd100b4febfb09c83f

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Citations in the corpus

Regression Discontinuity Designs (2021, positive): “Cattaneo and Titiunik (2022) give a comprehensive review of the RD literature, and recent practical introductions to RD methods can be found in Cattaneo, Idrobo and Titiunik (2020, 2024) and Cattaneo, Keele and Titiunik (2023).”
A Survey of Learning Causality with Data (2018, background): “A practical guide of RDD can be found in Reference [23].”
Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs (2018, methodology): “For introductions to RD designs, literature reviews, and background references, see Imbens and Lemieux (2008), Lee and Lemieux (2010), Cattaneo and Escanciano (2017), and Cattaneo et al. (2019, 2020).”