Robust Data-Driven Inference in the Regression-Discontinuity Design. (December 2014)

• Record Type: Journal Article
• Authors: Calonico, Sebastian; Cattaneo, Matias D.; Titiunik, Rocío
• Is Part Of: Stata journal. Volume 14:Number 4(2014)
• Page Start: 909
• Page End: 946
• Publication Date: 2014-12
• Subjects: st0366 -- rdrobust -- rdbwselect -- rdplot -- regression discontinuity (RD) -- sharp RD -- sharp kink RD -- fuzzy RD -- fuzzy kink RD -- treatment effects -- local polynomials -- bias correction -- bandwidth selection -- RD plots; Statistics -- Periodicals; Statistics -- Computer programs -- Periodicals; 001.422
• DOI: 10.1177/1536867X1401400413
• Languages: English
• ISSNs: 1536-867X

Abstract

In this article, we introduce three commands to conduct robust data-driven statistical inference in regression-discontinuity (RD) designs. First, we presentrdrobust, a command that implements the robust bias-corrected confidence intervals proposed in Calonico, Cattaneo, and Titiunik (2014d, Econometrica 82: 2295–2326) for average treatment effects at the cutoff in sharp RD, sharp kink RD, fuzzy RD, and fuzzy kink RD designs. This command also implements other conventional nonparametric RD treatment-effect point estimators and confidence intervals. Second, we describe the companion commandrdbwselect, which implements several bandwidth selectors proposed in the RD literature. Following the results in Calonico, Cattaneo, and Titiunik (2014a, Working paper, University of Michigan), we also introducerdplot, a command that implements several data-driven choices of the number of bins in evenly spaced and quantile-spaced partitions that are used to construct the RD plots usually encountered in empirical applications. A companion R package is described in Calonico, Cattaneo, and Titiunik (2014b, Working paper, University of Michigan).