Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/236436 
Year of Publication: 
2021
Series/Report no.: 
IZA Discussion Papers No. 14405
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
We contribute new UK evidence about measurement errors and employment earnings to a field dominated by findings about the USA. We develop and apply new econometric models for linked survey and administrative data that generalize those of Kapteyn and Ypma (Journal of Labor Economics, 2007). Our models incorporate mean-reverting measurement error in administrative data in addition to linkage mismatch and mean-reverting survey measurement error and 'reference period' error, while also allowing error distributions to vary across individuals. Annualised survey earnings underestimate true annual earnings on average. Mean-reversion in survey measurement errors is absent. Both earnings sources underestimate true earnings inequality. The survey earning measure is more reliable than the administrative data earnings measure, but hybrid earnings predictors based on both sources are distinctly more reliable than either source-specific measure. The models with heterogeneous measurement error distributions indicate how data quality may be improved. For example, for survey quality, our results highlight how respondents showing payslips to interviewers have smaller survey error variances. For administrative data, our results suggest that greater error variances are associated with non-standard jobs, private sector jobs, and employers without good payroll systems.
Subjects: 
measurement error
earnings
survey data
administrative data
finite mixture models
JEL: 
C81
C83
D31
Document Type: 
Working Paper

Files in This Item:
File
Size
2.18 MB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.