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Testing for the presence of measurement error in Stata

Author

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  • Young Jun Lee

    (Institute for Fiscal Studies)

  • Daniel Wilhelm

    (Institute for Fiscal Studies and University College London)

Abstract

In this paper, we describe how to test for the presence of measurement error in explanatory variables. First, we discuss the test of such hypotheses in parametric models such as linear regressions and then introduce a new Stata command [R] dgmtest for a nonparametric test proposed in Wilhelm (2018b). 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, 2018. "Testing for the presence of measurement error in Stata," CeMMAP working papers CWP51/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:51/18
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