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University prestige, performance evaluation, and promotion: Estimating the employer learning model using personnel datasets

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  • Araki, Shota
  • Kawaguchi, Daiji
  • Onozuka, Yuki

Abstract

Employers rely on educational credentials to form their initial belief about a worker's ability and update the belief by observing the worker's performance on the job. We study the careers of white-collar university graduates, using personnel data from two large Japanese manufacturers. These data contain information about the university from which the worker graduated, as well as the worker's performance evaluations and positions in the promotion ladder. As employees move up the career ladder, performance evaluations become a more important determinant for promotion than educational credentials. Structural estimates suggest that employers learn workers' ability quickly through observing their performance on the job, with expectation errors halving after about 3 to 6years.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:labeco:v:41:y:2016:i:c:p:135-148
    DOI: 10.1016/j.labeco.2016.05.024
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    Cited by:

    1. Jong-Wha Lee & Dainn Wie, 2017. "Returns to Education and Skills in the Labor Market: Evidence from Japan and Korea," Asian Economic Policy Review, Japan Center for Economic Research, vol. 12(1), pages 139-160, January.
    2. Yuta Kuroda, 2023. "What do high-achieving graduates bring to nonacademic track high schools?," DSSR Discussion Papers 138, Graduate School of Economics and Management, Tohoku University.
    3. Gavriil Agarkov & Daniil Sandler & Anastasia Sushchenko Anastasia Dmitrievna, 2018. "Financial and Social Success of University Graduates in the Ural Region," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 1312-1326.
    4. Robin Cowan & Giulia Rossello, 2018. "Emergent structures in faculty hiring networks, and the effects of mobility on academic performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 527-562, October.
    5. 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.
    6. Bordón, Paola & Braga, Breno, 2020. "Employer learning, statistical discrimination and university prestige," Economics of Education Review, Elsevier, vol. 77(C).
    7. Kenjiro Hirata & Shinpei Sano & Katsuya Takii, 2021. "How can a college's admissions policies help produce future business leaders?," OSIPP Discussion Paper 21E003, Osaka School of International Public Policy, Osaka University.
    8. Matthieu Bunel & Dominique Meurs & Élisabeth Tovar, 2024. "Moving apart: job-driven residential mobility and the gender pay gap Evidence from a large industrial firm," EconomiX Working Papers 2024-6, University of Paris Nanterre, EconomiX.
    9. Weinstein, Russell, 2017. "University Selectivity, Initial Job Quality, and Longer-Run Salary," IZA Discussion Papers 10911, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Bayesian learning; Promotion; Personnel data; Internal labor market;
    All these keywords.

    JEL classification:

    • J46 - Labor and Demographic Economics - - Particular Labor Markets - - - Informal Labor Market

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