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Imputation rules for the implementation of the pre-unification education variable in the BASiD Data Set
[Imputationsregeln für die Generierung der Bildungsvariable in den BASiD-Daten vor der Wiedervereinigung]

Author

Listed:
  • Nicole Gürtzgen

    (Institute for Employment Research
    University of Regensburg)

  • André Nolte

    (Department of Labour Markets, Human Resources and Social Policy)

Abstract

Using combined data from the German Pension Insurance and the Federal Employment Agency (BASiD), this study proposes different procedures for imputing the pre-unification education variable in the BASiD data. To do so, we exploit information on education-related periods that are creditable for the Pension Insurance. Combining these periods with information on the educational system in the former GDR, we propose three different imputation procedures, which we validate using external GDR census data for selected age groups. A common result from all procedures is that they tend to underpredict (overpredict) the share of high-skilled (low-skilled) for the oldest age groups. Comparing our imputed education variable with information on educational attainment from the Integrated Employment Biographies (IEB) reveals that the best match is obtained for the vocational training degree. Although regressions show that misclassification with respect to IEB information is clearly related to observables, we do not find any systematic pattern across skill groups.

Suggested Citation

  • Nicole Gürtzgen & André Nolte, 2017. "Imputation rules for the implementation of the pre-unification education variable in the BASiD Data Set [Imputationsregeln für die Generierung der Bildungsvariable in den BASiD-Daten vor der Wieder," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 50(1), pages 45-65, August.
    • Handle: RePEc:spr:jlabrs:v:50:y:2017:i:1:d:10.1007_s12651-017-0219-3
    DOI: 10.1007/s12651-017-0219-3
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    1. Nicola Fuchs-Schündeln & Paolo Masella, 2016. "Long-Lasting Effects of Socialist Education," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 428-441, July.
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    7. Büttner, Thomas & Rässler, Susanne, 2008. "Multiple imputation of right-censored wages in the German IAB Employment Sample considering heteroscedasticity," IAB-Discussion Paper 200844, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    8. Freeman, Richard B. & Katz, Lawrence F. (ed.), 1995. "Differences and Changes in Wage Structures," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226261607, December.
    9. Antonia Manzari, 2004. "Combining editing and imputation methods: an experimental application on population census data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(2), pages 295-307, May.
    10. Bernd Fitzenberger & Aderonke Osikominu & Robert Völter, 2006. "Imputation Rules to Improve the Education Variable in the IAB Employment Subsample," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 126(3), pages 405-436.
    11. Daniela Hochfellner & Dana Müller & Anja Wurdack, 2012. "Biographical Data of Social Insurance Agencies in Germany – Improving the Content of Administrative Data," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 132(3), pages 443-451.
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    Cited by:

    1. Pfister, Mona & Lorenz, Svenja & Zwick, Thomas, 2018. "Calculation of pension entitlements in the sample of integrated labour market biographies (SIAB)," FDZ Methodenreport 201801_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Nicole Gürtzgen & André Diegmann (né Nolte), 2020. "Does low‐pay persist across different regimes? Evidence from German Unification," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 28(3), pages 413-440, July.
    3. repec:iab:iabfme:201801(en is not listed on IDEAS
    4. Lorenz, Svenja & Pfister, Mona & Zwick, Thomas, 2018. "Identification of the statutory retirement dates in the Sample of Integrated Labour Market Biographies (SIAB)," FDZ Methodenreport 201808_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Nolte, Andre & Gürtzgen, Nicole, 2015. "Changing Fortunes during Economic Transition - Low-Wage Persistence before and after German Unification," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112828, Verein für Socialpolitik / German Economic Association.
    6. repec:iab:iabfme:201808(en is not listed on IDEAS

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    More about this item

    Keywords

    Imputation rules; Administrative data; East Germany; Education; Institutions;
    All these keywords.

    JEL classification:

    • I2 - Health, Education, and Welfare - - Education
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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