IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp1015.html

Does Employer Learning Vary by Occupation?

Author

Listed:
  • Hani Mansour

Abstract

Models in which employers learn about the productivity of young workers, such as Altonji and Pierret (2001), have two principal implications: First, the distribution of wages becomes more dispersed as a cohort of workers gains experience; second, the coefficient on a variable that employers initially do not observe, such as the Armed Forces Qualification Test (AFQT) score, grows with experience. If employers' learning varies significantly across occupations, both of these indicators of learning should covary positively across groups defined by a worker's occupational assignment at labor market entry. This paper tests this implication of the employer learning model using data from the NLSY and CPS. I find that occupations with high growth in the variance of residual wages over the first ten years of the worker's career are also the occupations with high growth in the AFQT coefficient, confirming the learning perspective. Interestingly, occupations that my analysis characterizes as having a low level of employer learning are not occupations where employers know little about the worker after ten years of experience; instead they appear to be occupations where employers have already learned about the worker's AFQT score at the time of hire. I provide several pieces of evidence that occupational assignment affects the learning process independently from education and that the results are not driven by workers' occupational mobility.

Suggested Citation

  • Hani Mansour, 2010. "Does Employer Learning Vary by Occupation?," Discussion Papers of DIW Berlin 1015, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1015
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.357357.de/dp1015.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Audrey Light & Andrew McGee, 2015. "Employer Learning and the “Importance†of Skills," Journal of Human Resources, University of Wisconsin Press, vol. 50(1), pages 72-107.
    2. repec:diw:diwwpp:dp1683 is not listed on IDEAS
    3. Rune V. Lesner, 2016. "Testing for Statistical Discrimination based on Gender," Economics Working Papers 2016-07, Department of Economics and Business Economics, Aarhus University.
    4. Araki, Shota & Kawaguchi, Daiji & Onozuka, Yuki, 2016. "University prestige, performance evaluation, and promotion: Estimating the employer learning model using personnel datasets," Labour Economics, Elsevier, vol. 41(C), pages 135-148.
    5. Wang, Jun & Li, Bo, 2020. "Does employer learning with statistical discrimination exist in China? Evidence from Chinese Micro Survey Data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 319-333.
    6. Mohrenweiser, Jens & Wydra-Sommaggio, Gaby & Zwick, Thomas, 2015. "Work-related ability as source of information advantages of training employers," ZEW Discussion Papers 15-057, ZEW - Leibniz Centre for European Economic Research.
    7. Audrey Light & Andrew McGee, 2011. "Employer Learning and the “Importance” of Skills," Working Papers 11-02, Ohio State University, Department of Economics.
    8. Light, Audrey & McGee, Andrew, 2015. "Does employer learning vary by schooling attainment? The answer depends on how career start dates are defined," Labour Economics, Elsevier, vol. 32(C), pages 57-66.
    9. Sun, Qian, 2024. "Asymmetric employer learning and gender-based statistical discrimination in China," China Economic Review, Elsevier, vol. 87(C).
    10. Bordón, Paola & Braga, Breno, 2020. "Employer learning, statistical discrimination and university prestige," Economics of Education Review, Elsevier, vol. 77(C).
    11. NAKABAYASHI, Masaki, 2011. "Acquired Skills and Learned Abilities: Wage Dynamics of Blue-collar Workers in Internal Labor Markets," ISS Discussion Paper Series (series F) f153, Institute of Social Science, The University of Tokyo, revised Apr 2012.
    12. Tani, Massimiliano, 2017. "Local signals and the returns to foreign education," Economics of Education Review, Elsevier, vol. 61(C), pages 174-190.
    13. Mahmut Ablay & Fabian Lange, 2023. "Approaches to learn about employer learning," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(2), pages 343-356, May.
    14. Homroy, Swarnodeep & Mukherjee, Shibashish, 2021. "The role of employer learning and regulatory interventions in mitigating executive gender pay gap," Journal of Corporate Finance, Elsevier, vol. 71(C).
    15. Sylvie Démurger & Eric A. Hanushek & Lei Zhang, 2024. "Employer Learning and the Dynamics of Returns to Universities: Evidence from Chinese Elite Education during University Expansion," Economic Development and Cultural Change, University of Chicago Press, vol. 73(1), pages 339-379.
    16. Seik Kim & Emiko Usui, 2021. "Employer learning, job changes, and wage dynamics," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1286-1307, July.
    17. Alexander Konon & Alexander Kritikos, 2017. "Media and Occupational Choice," Discussion Papers of DIW Berlin 1683, DIW Berlin, German Institute for Economic Research.
    18. Melinda Petre, 2018. "Are Employers Omniscient? Employer Learning About Cognitive and Noncognitive Skills," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 57(3), pages 323-360, July.
    19. Rao, Neel, 2016. "Asymmetric information and search frictions: A neutrality result," Economics Letters, Elsevier, vol. 147(C), pages 138-141.
    20. Daniel Kreisman & Jonathan Smith & Bondi Arifin, 2023. "Labor Market Signaling and the Value of College: Evidence from Resumes and the Truth," Journal of Human Resources, University of Wisconsin Press, vol. 58(6), pages 1820-1849.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:diw:diwwpp:dp1015. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.