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Determinants of Lifetime Unemployment - A Micro Data Analysis with Censored Quantile Regressions

Author

Listed:
  • Achim Schmillen

    (Osteuropa-Institut, Regensburg (Institut for East European Studies))

  • Joachim Möller

    (Institute for Employment Research (IAB))

Abstract
Building on a large administrative micro data set for the time span 1975 - 2004 we look at lifetime unemployment for West German birth cohorts 1950 to 1954. Descriptive evidence shows a highly uneven distribution of unemployment in West Germany - more than 60% of the individuals in our sample were not unemployed for a single day over the better part of their professional career while almost half of the total amount of unemployment fell upon 5% of the individuals covered. We employ censored quantile regressions to explain the amount of individual lifetime unemployment. Explanatory variables are either characteristics of the individual (like education), or of the job (like the wage) or the employer (like the size of the firm) early in the professional career. A particular emphasis is placed on the importance of the occupation: we find that for men working in a disadvantageous occupation at age 25 ceteris paribus leads to a signi cantly higher amount of lifetime unemployment. Educational attainment or the wage earned at age 25 are also related to the amount of men's lifetime unemployment, amongst others. Some of these variables show very interesting patterns when looking at di erent quantiles. For women results are in general less clear-cut.

Suggested Citation

  • Achim Schmillen & Joachim Möller, 2009. "Determinants of Lifetime Unemployment - A Micro Data Analysis with Censored Quantile Regressions," Working Papers 275, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
    • Handle: RePEc:ost:wpaper:275
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    References listed on IDEAS

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    Cited by:

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    3. Michael Stops, 2011. "Job Matching on non-separated Occupational Labour Markets," ERSA conference papers ersa11p372, European Regional Science Association.
    4. Tisch, Anita & Tophoven, Silke, 2011. "Erwerbseinstieg und bisheriges Erwerbsleben der deutschen Babyboomerkohorten 1959 und 1965 : Vorarbeiten zu einer Kohortenstudie," IAB-Forschungsbericht 201108, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Michael Stops, 2014. "Job matching across occupational labour markets," Oxford Economic Papers, Oxford University Press, vol. 66(4), pages 940-958.
    6. Pradhan, Jaya Prakash, 2010. "R&D strategy of small and medium enterprises in India: Trends and determinants," MPRA Paper 20951, University Library of Munich, Germany.
    7. Farrukh Bashir & Tusawar Iftikhar Ahmad & Tehmina Hidayat, 2013. "Causes of Unemployment Among Highly Educated Women in Pakistan: A Case Study Of Bahawalnagar District," Pakistan Journal of Humanities and Social Sciences, International Research Alliance for Sustainable Development (iRASD), vol. 1(1), pages 1-10, June.
    8. Marcelo Cajias & Philipp Freudenreich & Anna Heller & Wolfgang Schaefers, 2018. "Censored Quantile Regressions and the Determinants of Real Estate Liquidity," ERES eres2018_203, European Real Estate Society (ERES).
    9. Münstermann, Leonard & Schneck, Stefan & Wolter, Hans-Jürgen, 2012. "Die Bedeutung des Kurzarbeitergeldes im Mittelstand," IfM-Materialien 215, Institut für Mittelstandsforschung (IfM) Bonn.

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    More about this item

    Keywords

    Lifetime unemployment; Censored-Quantile Regressions; Occupations specific human capital;
    All these keywords.

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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