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Testing for the presence of measurement error in Stata

Author

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  • Young Jun Lee

    (University of Copenhagen)

  • Daniel Wilhelm

    (University College London, CeMMAP)

Abstract

In this article, we describe how to test for the presence of measure- ment error in explanatory variables. First, we discuss the test of such hypotheses in parametric models such as linear regressions and then introduce a new com- mand, dgmtest, for a nonparametric test proposed in Wilhelm (2018, Working Paper CWP45/18, Centre for Microdata Methods and Practice, Institute for Fis- cal Studies). To illustrate the new command, we provide Monte Carlo simulations and an empirical application to testing for measurement error in administrative earnings data.

Suggested Citation

  • Young Jun Lee & Daniel Wilhelm, 2020. "Testing for the presence of measurement error in Stata," Stata Journal, StataCorp LP, vol. 20(2), pages 382-404, June.
    • Handle: RePEc:tsj:stataj:v:20:y:2019:i:2:p:382-404
    DOI: 10.1177/1536867X20931002
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