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How Do Firms Deal with the Risks of Employing Ex-prisoners?

Author

Listed:
  • Köllő, János

    (Institute of Economics, Budapest)

  • Boza, István

    (Centre for Economic and Regional Studies)

  • Ilyés, Virág

    (HUN-REN Centre for Economic and Regional Studies)

  • Kőműves, Zsófia

    (Cambridge Economic Policy Associates)

  • Mark, Lili Katalin

    (Central European University, Budapest)

Abstract

We use linked employer-employee data to investigate a large sample of past and future prisoners in Hungary, 2003-2011. We first compare their jobs, focusing on attributes that can reduce the penalty the employer must pay for a mistaken hiring decision. Second, we study if employers insure themselves by paying lower wages to ex-prisoners. Third, we analyze whether the probability of the match dissolving within a few months is lower if the firm could potentially base its hiring decision on referrals. The composition of former prisoners' employment is biased toward easy-to-cancel jobs. In the unskilled jobs held by most of them, they do not earn less than future convicts, but a minority in white-collar positions are paid significantly less. Ex-prisoners' jobs are less likely to dissolve quickly if the hiring firm potentially had access to co-worker, employer, or labor office referrals.

Suggested Citation

  • Köllő, János & Boza, István & Ilyés, Virág & Kőműves, Zsófia & Mark, Lili Katalin, 2023. "How Do Firms Deal with the Risks of Employing Ex-prisoners?," IZA Discussion Papers 16645, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp16645
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    References listed on IDEAS

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    1. Cecilia Rouse & Claudia Goldin, 2000. "Orchestrating Impartiality: The Impact of "Blind" Auditions on Female Musicians," American Economic Review, American Economic Association, vol. 90(4), pages 715-741, September.
    2. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    3. Francesco Drago & Roberto Galbiati & Pietro Vertova, 2009. "The Deterrent Effects of Prison: Evidence from a Natural Experiment," Journal of Political Economy, University of Chicago Press, vol. 117(2), pages 257-280, April.
    4. Peter Norman, 2003. "Statistical Discrimination and Efficiency," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(3), pages 615-627.
    5. Jonathan S. Leonard & David I. Levine & Laura Giuliano, 2010. "Customer Discrimination," The Review of Economics and Statistics, MIT Press, vol. 92(3), pages 670-678, August.
    6. Amanda Agan & Sonja Starr, 2018. "Ban the Box, Criminal Records, and Racial Discrimination: A Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 191-235.
    7. Devah Pager, 2003. "The mark of a criminal record," Natural Field Experiments 00319, The Field Experiments Website.
    8. Goldin, Claudia D. & Rouse, Cecilia, 2000. "Orchestrating Impartiality: The Impact of “Blind†Auditions on Female Musicians," Scholarly Articles 30703974, Harvard University Department of Economics.
    9. Reich, Michael & Gordon, David M & Edwards, Richard C, 1973. "A Theory of Labor Market Segmentation," American Economic Review, American Economic Association, vol. 63(2), pages 359-365, May.
    10. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    incarceration; reintegration; mobility; discrimination; Hungary;
    All these keywords.

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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