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Which factors safeguard employment? : An analysis with misclassified German register data

Author

Listed:
  • Wichert, Laura

    (University of Konstanz)

  • Wilke, Ralf A.

    (University of Nottingham ; ZEW)

Abstract

"We analyse the main determinants for job separation with transition to unemployment using individual administrative data from Germany. While the sample size is large and the information in target variables is often highly accurate, non-target variables are subject to considerable measurement error due to a lack of relevance for the data generating process. We show that the high degree of misclassification can even persist after comprehensive logical editing and imputation rules were applied. We find that the measurement error has a sizable effect on our estimation results. Long tenure rather than a higher educational qualification appears to be the key ingredient for a safe job in Germany." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Wichert, Laura & Wilke, Ralf A., 2010. "Which factors safeguard employment? : An analysis with misclassified German register data," FDZ-Methodenreport 201011 (en), Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    • Handle: RePEc:iab:iabfme:201011(en)
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    Cited by:

    1. Nina Westerheide & Goran Kauermann, 2014. "Unemployed in Germany: Factors Influencing the Risk of Losing the Job," Research in World Economy, Research in World Economy, Sciedu Press, vol. 5(2), pages 43-55, September.
    2. Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2017. "Generalized partially linear regression with misclassified data and an application to labour market transitions," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 145-159.
    3. Rothe, Thomas & Giannelli, Gianna C. & Jaenichen, Ursula, 2013. "Doing well in reforming the labour market? Recent trends in job stability and wages in Germany," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79932, Verein für Socialpolitik / German Economic Association.
    4. Kohlbrecher, Britta & Merkl, Christian & Nordmeier, Daniela, 2016. "Revisiting the matching function," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 350-374.
    5. Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2015. "Generalised partially linear regression with misclassified data and an application to labour market transitions," ZEW Discussion Papers 15-043, ZEW - Leibniz Centre for European Economic Research.
    6. Lo, Simon M.S. & Stephan, Gesine & Wilke, Ralf, 2012. "Estimating the Latent Effect of Unemployment Benefits on Unemployment Duration," IZA Discussion Papers 6650, Institute of Labor Economics (IZA).
    7. Serena Pattaro & Nick Bailey & Chris Dibben, 2020. "Using Linked Longitudinal Administrative Data to Identify Social Disadvantage," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(3), pages 865-895, February.
    8. Jan Marcus, 2014. "Does Job Loss Make You Smoke and Gain Weight?," Economica, London School of Economics and Political Science, vol. 81(324), pages 626-648, October.
    9. Dlugosz, Stephan, 2011. "Give missings a chance: Combined stochastic and rule-based approach to improve regression models with mismeasured monotonic covariates without side information," ZEW Discussion Papers 11-013, ZEW - Leibniz Centre for European Economic Research.
    10. Melanie Arntz & Stephan Dlugosz & Ralf A. Wilke, 2017. "The Sorting of Female Careers after First Birth: A Competing Risks Analysis of Maternity Leave Duration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 689-716, October.
    11. 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.
    12. Neumann, M., 2017. "Earnings responses to social security contributions," Labour Economics, Elsevier, vol. 49(C), pages 55-73.
    13. Stephan Humpert, 2012. "Age and Gender Differences in Job Opportunities," Working Paper Series in Economics 235, University of Lüneburg, Institute of Economics.
    14. repec:iab:iabfme:201510(en is not listed on IDEAS

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