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Education, educational mismatch and occupational status: an analysis using PIAAC data

Author

Listed:
  • Inés P. Murillo Huertas

    (Universidad de Extremadura)

  • José L. Raymond

    (Universidad Autónoma de Barcelona)

Abstract

The aim of this paper is to estimate the effect of longer schooling on the probability of entering a high-skill job and analyse whether the size of this effect depends on the (mis)match between the education attained by workers and the education required by the jobs. We use PIAAC data to estimate a multinomial logit model that predicts the odds of working in each occupational category and then simulate how these probabilities change for workers who have completed one more year of education, broken down by whether or not this additional year matches the educational requirements of the job. Our results suggest that, as observed from wages estimated according to an ORU equation, better education is positively associated with better jobs but the increased probability of getting a high-skill job as a result of completing one more year of education is greater for required than for mismatched education. The results differ notably by gender, with women being the ones who benefit most from an increase in education, especially in the absence of educational mismatch. These trends are observed whatever the institutional context, but we also found noteworthy differences by country.

Suggested Citation

  • Inés P. Murillo Huertas & José L. Raymond, 2024. "Education, educational mismatch and occupational status: an analysis using PIAAC data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 41(3), pages 717-738, October.
    • Handle: RePEc:spr:epolit:v:41:y:2024:i:3:d:10.1007_s40888-024-00328-z
    DOI: 10.1007/s40888-024-00328-z
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    More about this item

    Keywords

    Education; Educational mismatch; Occupational status; Multinomial logit models;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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