Testing for the presence of measurement error in Stata
Young Jun Lee and
Additional contact information
Young Jun Lee: Institute for Fiscal Studies
No CWP47/19, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies
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 (2018). To illustrate the new command, we provide Monte Carlo simulations and an empirical application to testing for measurement error in administrative earnings data.
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://www.ifs.org.uk/uploads/CW4719-Testing-for- ... t-error-in-Stata.pdf (application/pdf)
Working Paper: Testing for the presence of measurement error in Stata (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ifs:cemmap:47/19
Ordering information: This working paper can be ordered from
The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE
Access Statistics for this paper
More papers in CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE. Contact information at EDIRC.
Bibliographic data for series maintained by Emma Hyman ().