Economics Working Papers

Publication Date





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 there is a group structure to the measurement error. We develop a procedure to make use of this group-specific measurement error structure to correct estimates obtained in a regression discontinuity framework using auxiliary data. This procedure extends the prior literature on measurement error on the running variable by leveraging auxiliary information in order to account for more general forms of measurement error. Additionally, we develop adjusted asymptotic variance and standard errors that take in consideration the variability introduced by the nonparametric estimation of nuisance parameters from auxiliary data.
Simulations provide evidence that the proposed procedure adequately corrects for measurement error introduced bias and tests using the new adjusted formulas exhibit empirical coverage closer nominal test size than ``naive'' alternatives. We provide two empirical illustrations to 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

Version History

Original Release Date: May 16, 2018


Department of Economics, Iowa State University

File Format



36 pages