Campus Units


Document Type


Publication Version

Accepted Manuscript

Publication Date


Journal or Book Title

Journal of Business & Economic Statistics




When the running variable in a regression discontinuity (RD) design is measured with error, identification of the local average treatment effect of interest will typically fail. While the form of this measurement error varies across applications, in many cases the measurement error structure is heterogeneous across different groups of observations. We develop a novel measurement error correction procedure capable of addressing heterogeneous mismeasurement structures by leveraging auxiliary information. We also provide adjusted asymptotic variance and standard errors that take into consideration the variability introduced by the estimation of nuisance parameters, and honest confidence intervals that account for potential misspecification. Simulations provide evidence that the proposed procedure corrects the bias introduced by heterogeneous measurement error and achieves empirical coverage closer to nominal test size than “naive” alternatives. Two empirical illustrations demonstrate that correcting for measurement error can either reinforce the results of a study or provide a new empirical perspective on the data.

JEL Classification

C14, C21, I12, J65


This is a manuscript of an article published as Bartalotti, Otávio, Quentin Brummet, and Steven Dieterle. "A correction for regression discontinuity designs with group-specific mismeasurement of the running variable." Journal of Business & Economic Statistics (2020). doi: 10.1080/07350015.2020.1737081. Posted with permssion.

Copyright Owner

American Statistical Association



File Format


Available for download on Friday, April 02, 2021

Published Version Working Paper