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Covariate Adjustment in Regression Discontinuity Designs

Matias D. Cattaneo, Luke Keele, Rocio Titiunik

arXiv 15 Oct 2021 · Statistics — Methodology · 21 citations (OpenAlex)

arXiv:2110.08410 · PDF · DOI · OpenAlex · Extracted main text

Abstract

The Regression Discontinuity (RD) design is a widely used non-experimental method for causal inference and program evaluation. While its canonical formulation only requires a score and an outcome variable, it is common in empirical work to encounter RD analyses where additional variables are used for adjustment. This practice has led to misconceptions about the role of covariate adjustment in RD analysis, from both methodological and empirical perspectives. In this chapter, we review the different roles of covariate adjustment in RD designs, and offer methodological guidance for its correct use.

Citation extraction

40
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Calonico, S., Cattaneo, M. D., Farrell, M. H., and Titiunik, R (2019) Regression Discontinuity Designs using Covariates self0.81142100%
2Cattaneo, M. D., Titiunik, R., and Vazquez-Bare, G (2017) Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality self0.73732100%
3Cattaneo, M. D., and Titiunik, R (2022) Regression Discontinuity Designs self0.73732100%
4Imbens, G. W., and Rubin, D. B (2015) Causal inference in statistics, social, and biomedical sciences0.73732100%
5Cattaneo, M. D., Idrobo, N., and Titiunik, R (2020) a) self0.64422100%
6height .65ex depth -.6ex width 3em\ (2022) a)0.64422100%
7Cattaneo, M. D., Keele, L., and Titiunik, R (2022) b), A Guide to Regression Discontinuity Designs in Medical Applications self0.64422100%
8height .65ex depth -.6ex width 3em\ (2020) b), The Regression Discontinuity Design, in0.64422100%
9Rosenbaum, P. R (2010) Design of observational studies0.64422100%
10Angrist, J. D., and Rokkanen, M (2015) Wanna get away? Regression discontinuity estimation of exam school effects away from the cutoff0.51121100%

Showing the top 10 of 40 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Extrapolating Away from the Cutoff in Regression Discontinuity Designs0.73732
2Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs This version: April 22, 20240.40511
3Regression Discontinuity Designs0.40511
4Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs0.40511
5A Practical Introduction to Regression Discontinuity Designs: Extensions0.40511
6A Guide to Regression Discontinuity Designs in Medical Applications0.40511
7rdhte: Conditional Average Treatment Effects in RD Designs0.40511
8Leveraging Covariates in Regression Discontinuity Designs0.40511