Robust Data-Driven Inference in the Regression-Discontinuity Design

In this article, we introduce three commands to conduct robust data-driven statistical inference in regression-discontinuity (RD) designs. First, we present rdrobust, 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 command rdbwselect, which implements several bandwidth selectors proposed in the RD literature. Following the results in Calonico,…

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  National Science Foundation