Skilled or unskilled - Improving the information on qualification for employee data in the IAB Employee Biography

Ulrich Thomsen, Johannes Ludsteck and Alexandra Schmucker
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Ulrich Thomsen: Institute for Employment Research (IAB), Nuremberg, Germany
Johannes Ludsteck: Institute for Employment Research (IAB), Nuremberg, Germany
Alexandra Schmucker: Institute for Employment Research (IAB), Nuremberg, Germany

No 201809 (en), FDZ-Methodenreport from Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]

Abstract: "This FDZ-Methodenreport describes the implementation of a deterministic imputation model for education in the Employee History (Beschäftigtenhistorik (BeH)) of the Institute for Employment Research (IAB). The imputation model was originally invented by Fitzenberger, Osikominu, and Völter, but now was adapted for the current Employee History. First the extent of the data quality problem is sketched out and different variants of the solving imputation model are evaluated. Then the implementation of the selected variant in the Employee History is described in detail. Afterwards some descriptive graphs show the resulting imputed data. In order to give the user a good impression about the goodness of the selected imputation model the quality of the imputed information is tested with some regression models. The regression results indicate, which variables in the Employee History have an influence on the quality of the imputed values. This allows an assessment of its usability for certain subgroups in the data." (Author's abstract, IAB-Doku) ((en))

Keywords: Bundesrepublik Deutschland; Ausbildungsabschluss; berufliche Qualifikation; Bildungsabschluss; Datengewinnung; Datenqualität; IAB-Beschäftigtenhistorik; Imputationsverfahren (search for similar items in EconPapers)
Pages: 22 pages
Date: 2018
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https://doi.org/10.5164/IAB.FDZM.1809.en.v1

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Persistent link: https://EconPapers.repec.org/RePEc:iab:iabfme:201809(en)

DOI: 10.5164/IAB.FDZM.1809.en.v1

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