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When a Door Closes, a Window Opens? Long-term Labor Market Effects of Involuntary Separations

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  • Simone Balestra

    (Department of Business Administration, University of Zurich)

  • Uschi Backes-Gellner

    (Department of Business Administration, University of Zurich)

Abstract

This study estimates the earning losses of workers experiencing an involuntary job separation. We employ, for the first time in the earning losses literature, a Poisson pseudo-maximum-likelihood estimator with fixed effects that has several advantages with respect to conventional fixed effects models. The Poisson estimator allows considering the full set of involuntary separations, including those with zero labor market earnings because of unemployment. By including individuals with zero earnings and by using our new method, the loss in the year of separation becomes larger than in previous studies. The loss starts with roughly 30 percent and, although it quickly shrinks, it remains at around 15 percent in the following years. In addition, we find that compared to other reasons for separation, the earning loss pattern is unique for involuntary separations, because no other type of separation implies such permanent scarring. This latter finding makes us confident that the self-reported involuntariness of a separation is a reliable source of information.

Suggested Citation

  • Simone Balestra & Uschi Backes-Gellner, 2012. "When a Door Closes, a Window Opens? Long-term Labor Market Effects of Involuntary Separations," Economics of Education Working Paper Series 0072, University of Zurich, Department of Business Administration (IBW), revised Dec 2015.
    • Handle: RePEc:iso:educat:0072
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    3. Katherine Caves & Simone Balestra, 2018. "The impact of high school exit exams on graduation rates and achievement," The Journal of Educational Research, Taylor & Francis Journals, vol. 111(2), pages 186-200, March.
    4. Pfister, Curdin & Koomen, Miriam & Harhoff, Dietmar & Backes-Gellner, Uschi, 2021. "Regional innovation effects of applied research institutions," Research Policy, Elsevier, vol. 50(4).

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    More about this item

    Keywords

    wage trajectories; job loss; earning loss; PPML;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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