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The consequences of being different - Statistical discrimination and the school-to-work transition

Author

Listed:
  • Barbara Mueller

    (EHB Schweiz)

  • Stefan C. Wolter

    (Institute of Economics, University of Berne)

Abstract
When information about the true abilities of job-seekers and applicants are hard to get, statistical discrimination by employers can be an efficient strategy in the hiring and wage setting process. But statistical discrimination can induce costs, if labor relations cannot be terminated in the short term and wages are fixed over a certain period. In this paper we use a unique longitudinal survey that follows the PISA 2000 students in their educational and work-life career. We test whether deviance in the PISA test scores from what one would have predicted based on observable characteristics, influences the probability to succeed in the transition from compulsory school into a firm-based apprenticeship and whether it can explain differences of the individual performances during training. Our results suggest that hard-to-get information plays a significant role in the transition, but not always in a symmetric manner.

Suggested Citation

  • Barbara Mueller & Stefan C. Wolter, 2011. "The consequences of being different - Statistical discrimination and the school-to-work transition," Economics of Education Working Paper Series 0053, University of Zurich, Department of Business Administration (IBW).
    • Handle: RePEc:iso:educat:0053
    as

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    References listed on IDEAS

    as
    1. Daron Acemoglu & Jörn-Steffen Pischke, 1998. "Why Do Firms Train? Theory and Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(1), pages 79-119.
    2. Galindo-Rueda, Fernando, 2003. "Employer learning and schooling-related statistical discrimination in Britain," LSE Research Online Documents on Economics 19491, London School of Economics and Political Science, LSE Library.
    3. Joseph G. Altonji & Charles R. Pierret, 2001. "Employer Learning and Statistical Discrimination," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 313-350.
    4. Gibbons, Robert & Katz, Lawrence F, 1991. "Layoffs and Lemons," Journal of Labor Economics, University of Chicago Press, vol. 9(4), pages 351-380, October.
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    6. Bauer, Thomas K. & Haisken-DeNew, John P., 2001. "Employer learning and the returns to schooling," Labour Economics, Elsevier, vol. 8(2), pages 161-180, May.
    7. Brunello, Giorgio, 2009. "The Effect of Economic Downturns on Apprenticeships and Initial Workplace Training: A Review of the Evidence," IZA Discussion Papers 4326, Institute of Labor Economics (IZA).
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    11. Mühlemann, Samuel & Wolter, Stefan C. & Wüest, Adrian, 2009. "Apprenticeship Training and the Business Cycle," IZA Discussion Papers 4460, Institute of Labor Economics (IZA).
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    Cited by:

    1. Gebhard Kirchgässner, 2015. "Wissenschaftlicher Fortschritt in den Wirtschaftswissenschaften: Einige Bemerkungen," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 135(2), pages 209-248.
    2. Ricardo Martínez & Antonio Villar, 2018. "Multilevel Proficiency Comparisons With An Application To Educational Outcomes In Pisa," Working Papers 18.04, Universidad Pablo de Olavide, Department of Economics.
    3. Sofie J. Cabus & Carla Haelermans, 2017. "Work or Schooling? On the Return to Gaining In-School Work Experiences," British Journal of Industrial Relations, London School of Economics, vol. 55(1), pages 34-57, March.

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    More about this item

    Keywords

    Statistical discrimination; school-to-work transition; PISA;
    All these keywords.

    JEL classification:

    • I2 - Health, Education, and Welfare - - Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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