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When a Door Closes a Window Opens? Investigating the 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

Using Swiss Labor Force Survey data from 1996 to 2009, this study estimates the earning losses of workers experiencing an involuntary job separation. We follow two empirical approaches: the method usually applied in the literature (fixed-effects estimation) and a new approach (Poisson pseudo-maximum-likelihood estimation) that allows considering the full set of involuntary separations, including those with zero labor market earnings because of unemployment. Using the rst method, we estimate an immediate loss of about 10 percent, a loss remaining statistically significant up to four years after separation at about 11 percent. Using the second approach, we estimate a loss of 40 percent in the year of separation and a longterm loss of almost 20 percent four years after separation. These larger estimates embed the total productivity loss caused by an involuntary separation. 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.

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File URL: http://repec.business.uzh.ch/RePEc/iso/leadinghouse/0072_lhwpaper.pdf
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Bibliographic Info

Paper provided by University of Zurich, Institute for Strategy and Business Economics (ISU) in its series Economics of Education Working Paper Series with number 0072.

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Length: 36 pages
Date of creation: Feb 2012
Date of revision: Aug 2013
Handle: RePEc:iso:educat:0072

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Keywords: Involuntary separation; earning losses; PPML;

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  1. Jacobson, Louis S & LaLonde, Robert J & Sullivan, Daniel G, 1993. "Earnings Losses of Displaced Workers," American Economic Review, American Economic Association, vol. 83(4), pages 685-709, September.
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  17. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
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