Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/202712 
Year of Publication: 
2019
Series/Report no.: 
IZA Discussion Papers No. 12366
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
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 "naïve" 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.
Subjects: 
nonclassical measurement error
regression discontinuity
heterogeneous measurement error
JEL: 
C21
C14
I12
J65
Document Type: 
Working Paper

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