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The impact of COVID on the rate of return to schooling among US industries

Author

Listed:
  • Yanan Chen
  • Kyle Kelly

Abstract

Purpose - This empirical study aims to examine the COVID impact on the rate of return to schooling in 20 US industries. Design/methodology/approach - An extended Mincer earnings equation with the COVID dummy variable and dummy interactive terms is used to examine the COVID effect on the rate of return to schooling for different industries. We use Heckman selection model to account for sample selection bias. Findings - During COVID years, the change in the wage differential between college-and-above and below-college workers is different for industries, which leads to different changes in the rate or return to schooling among the 20 industries. During COVID, the rate of return to schooling increased for seven industries, decreased for seven industries and remained the same for six industries. Originality/value - There is a lack of empirical tests of recession effects on the rate of return to schooling focusing on industry differentials. This study fills the research gap in this field. Our results will contribute to the ongoing discussion of the COVID impact on wages and returns from human capital investment.

Suggested Citation

  • Yanan Chen & Kyle Kelly, 2024. "The impact of COVID on the rate of return to schooling among US industries," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 52(5), pages 1007-1021, September.
    • Handle: RePEc:eme:jespps:jes-03-2024-0147
    DOI: 10.1108/JES-03-2024-0147
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