A correction for regression discontinuity designs with group-specific mismeasurement of the running variable

Otavio Bartalotti, Quentin Brummet, Steven Dieterle

Research output: Contribution to journalArticlepeer-review

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 “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.
Original languageEnglish
Pages (from-to)1-16
JournalJournal of Business and Economic Statistics
VolumeN/A
Early online date2 Apr 2020
DOIs
Publication statusE-pub ahead of print - 2 Apr 2020

Keywords

  • nonclassical measurement Error
  • regression discontinuity
  • heterogeneous measurement Error

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