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Testing for the Presence of Measurement Error in Stata

Wilhelm, D; Lee, YJ; (2020) Testing for the Presence of Measurement Error in Stata. The Stata Journal , 20 (2) pp. 382-404. 10.1177/1536867X20931002. Green open access

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Abstract

In this article, 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 command, dgmtest, for a nonparametric test proposed in Wilhelm (2018, Working Paper CWP45/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies). To illustrate the new command, we provide Monte Carlo simulations and an empirical application to testing for measurement error in administrative earnings data.

Type: Article
Title: Testing for the Presence of Measurement Error in Stata
Open access status: An open access version is available from UCL Discovery
DOI: 10.1177/1536867X20931002
Publisher version: https://doi.org/10.1177/1536867X20931002
Language: English
Additional information: https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Keywords: st0600, dgmtest, nonparametric test, measurement error, measurement error bias
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics
URI: https://discovery.ucl.ac.uk/id/eprint/10086466
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