Arbeitspapier

Reconciling Reports: Modelling Employment Earnings and Measurement Errors Using Linked Survey and Administrative Data

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.

Sprache
Englisch

Erschienen in
Series: IZA Discussion Papers ; No. 14405

Klassifikation
Wirtschaft
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
Survey Methods; Sampling Methods
Personal Income, Wealth, and Their Distributions
Thema
measurement error
earnings
survey data
administrative data
finite mixture models

Ereignis
Geistige Schöpfung
(wer)
Jenkins, Stephen P.
Rios-Avila, Fernando
Ereignis
Veröffentlichung
(wer)
Institute of Labor Economics (IZA)
(wo)
Bonn
(wann)
2021

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Jenkins, Stephen P.
  • Rios-Avila, Fernando
  • Institute of Labor Economics (IZA)

Entstanden

  • 2021

Ähnliche Objekte (12)