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.
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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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