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Comparing administrative and survey data: Is information on education from administrative records of the German Institute for Employment Research consistent with survey self-reports?

Author

Listed:
  • Jule Adriaans

    (German Institute for Economic Research (DIW Berlin))

  • Peter Valet

    (University of Bamberg)

  • Stefan Liebig

    (German Institute for Economic Research (DIW Berlin))

Abstract

In research on stratification and inequality, administrative data are popular for their wide coverage and assumed high quality. Yet, the quality of the data depends crucially on the aim of data collection. In this paper, we investigate the quality of information on education in administrative data from social security records provided by the German Federal Institute for Employment Research where education was not the primary purpose of data collection. We use linked German employee data with self-reported education as a benchmark to investigate whether the level of education is consistent or provided at all in the administrative data. The results show striking differences between administrative and survey data. Not only is information on education often missing from the administrative data; the information contained often deviates from the information employees reported in the survey. Information on school-leaving certificates is more often missing from the administrative data than information on vocational and university degrees. Furthermore, the information on vocational and university degrees is frequently inconsistent. Our results, moreover, reveal that missingness and inconsistency of information differ by type of degree obtained. Employer characteristics show a systematic correlation with missingness of information on both schooling and vocational degrees but appear less relevant in explaining inconsistencies. Additional analyses of estimated returns to education indicate that misreporting of vocational degrees in particular leads to an underestimation of actual returns to education. These results suggest that further research on the quality of measures of education in administrative data collected for different purposes is needed.

Suggested Citation

  • Jule Adriaans & Peter Valet & Stefan Liebig, 2020. "Comparing administrative and survey data: Is information on education from administrative records of the German Institute for Employment Research consistent with survey self-reports?," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 3-25, February.
  • Handle: RePEc:spr:qualqt:v:54:y:2020:i:1:d:10.1007_s11135-019-00931-4
    DOI: 10.1007/s11135-019-00931-4
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    References listed on IDEAS

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    1. Thomsen, Ulrich & Ludsteck, Johannes & Schmucker, Alexandra, 2018. "Skilled or unskilled - Improving the information on qualification for employee data in the IAB Employee Biography," FDZ Methodenreport 201809_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. David Card & Jörg Heining & Patrick Kline, 2013. "Workplace Heterogeneity and the Rise of West German Wage Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(3), pages 967-1015.
    3. Christopher R. Bollinger & Barry T. Hirsch, 2013. "Is Earnings Nonresponse Ignorable?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 407-416, May.
    4. Thomas J. Kane & Cecilia Elena Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," NBER Working Papers 7235, National Bureau of Economic Research, Inc.
    5. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    6. Jahn, Elke J. & Pozzoli, Dario, 2013. "The pay gap of temporary agency workers — Does the temp sector experience pay off?," Labour Economics, Elsevier, vol. 24(C), pages 48-57.
    7. Stefan Bender & Anja Burghardt & David Schiller, 2014. "International Access to Administrative Data for Germany and Europe," RatSWD Working Papers 229, German Data Forum (RatSWD).
    8. Figlio, D. & Karbownik, K. & Salvanes, K.G., 2016. "Education Research and Administrative Data," Handbook of the Economics of Education,, Elsevier.
    9. Arie Kapteyn & Jelmer Y. Ypma, 2007. "Measurement Error and Misclassification: A Comparison of Survey and Administrative Data," Journal of Labor Economics, University of Chicago Press, vol. 25(3), pages 513-551.
    10. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    11. Rebecca N. Warburton & William P. Warburton, 2004. "Canada Needs Better Data for Evidence-Based Policy: Inconsistencies Between Administrative and Survey Data on Welfare Dependence and Education," Canadian Public Policy, University of Toronto Press, vol. 30(3), pages 241-256, September.
    12. repec:fth:prinin:419 is not listed on IDEAS
    13. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    14. Peter Valet & Jule Adriaans & Stefan Liebig, 2019. "Comparing survey data and administrative records on gross earnings: nonreporting, misreporting, interviewer presence and earnings inequality," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 471-491, January.
    15. Dirk Antonczyk & Thomas DeLeire & Bernd Fitzenberger, 2018. "Polarization and Rising Wage Inequality: Comparing the U.S. and Germany," Econometrics, MDPI, vol. 6(2), pages 1-33, April.
    16. Davila, Tony, 2005. "An exploratory study on the emergence of management control systems: formalizing human resources in small growing firms," Accounting, Organizations and Society, Elsevier, vol. 30(3), pages 223-248, April.
    17. Thomas J. Kane & Cecilia Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," Working Papers 798, Princeton University, Department of Economics, Industrial Relations Section..
    18. repec:iab:iabfme:201809(en is not listed on IDEAS
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    2. Babette Bühler & Katja Möhring & Andreas P. Weiland, 2022. "Assessing dissimilarity of employment history information from survey and administrative data using sequence analysis techniques," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4747-4774, December.
    3. Emmanuel Flachaire & Nora Lustig & Andrea Vigorito, 2023. "Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(4), pages 1033-1059, December.

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