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Cited by 678

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Regression Discontinuity Designs Using Covariates

Calonico, Sebastian, Cattaneo, Matias D., Farrell, Max H., Titiunik, Rocío·2019·The Review of Economics and Statistics
DOI 10.1162/rest_a_00760
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Abstract

We study regression discontinuity designs when covariates are included in the estimation. We examine local polynomial estimators that include discrete or continuous covariates in an additive separable way, but without imposing any parametric restrictions on the underlying population regression functions. We recommend a covariate-adjustment approach that retains consistency under intuitive conditions and characterize the potential for estimation and inference improvements. We also present new covariate-adjusted mean-squared error expansions and robust bias-corrected inference procedures, with heteroskedasticity-consistent and cluster-robust standard errors. We provide an empirical illustration and an extensive simulation study. All methods are implemented in R and Stata software packages.

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Metadata

Authors
Calonico, S., Cattaneo, M. D., Farrell, M. H., & Titiunik, R.
Venue
The Review of Economics and Statistics
Publisher
MIT Press - Journals
Published
2019-07
Volume
101
Issue
3
Pages
442-451
ISSN
  • 0034-6535 (ISSN-L)
  • 1530-9142
DOI
10.1162/rest_a_00760
OpenAlex
W2884548321
Cited by
678
References
25
FWCI
42.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Regression Discontinuity Designs Using Covariates. https://app.cochat.ai/papers/10.1162/rest_a_00760
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Calonico, S., Cattaneo, M. D., Farrell, M. H., & Titiunik, R. (2019). Regression Discontinuity Designs Using Covariates. The Review of Economics and Statistics. https://doi.org/10.1162/rest_a_00760

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