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Educational mismatch and the earnings distribution

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  • Keith A. Bender
  • Kristen Roche

Abstract

This article focuses on the interrelationship between educational mismatch and earnings, taking three new approaches. First, we examine decompositions of the mismatch wage gap, finding that characteristics explain less than half of the mismatch penalty. Second, we use unconditional quantile regression to examine the mismatch penalty across the earnings distribution, showing that the penalty shrinks as the position in the earnings distribution increases. Third, we decompose the differentials using quantile decompositions. Different reasons for mismatch show heterogeneity in our results, with larger penalties for being mismatched due to working conditions, location, family, and no available job.

Suggested Citation

  • Keith A. Bender & Kristen Roche, 2018. "Educational mismatch and the earnings distribution," Southern Economic Journal, John Wiley & Sons, vol. 85(2), pages 441-456, October.
  • Handle: RePEc:wly:soecon:v:85:y:2018:i:2:p:441-456
    DOI: 10.1002/soej.12282
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    References listed on IDEAS

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    1. Joseph G. Altonji & Erica Blom & Costas Meghir, 2012. "Heterogeneity in Human Capital Investments: High School Curriculum, College Major, and Careers," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 185-223, July.
    2. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    3. Keith Bender & John Heywood, 2011. "Educational mismatch and the careers of scientists," Education Economics, Taylor & Francis Journals, vol. 19(3), pages 253-274.
    4. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    5. Lex Borghans & Andries de Grip (ed.), 2000. "The Overeducated Worker?," Books, Edward Elgar Publishing, number 1860.
    6. McGuinness, Seamus & Bennett, Jessica, 2007. "Overeducation in the graduate labour market: A quantile regression approach," Economics of Education Review, Elsevier, vol. 26(5), pages 521-531, October.
    7. Patrizia Ordine & Giuseppe Rose, 2015. "The effect of family background, university quality and educational mismatch on wage: an analysis using a young cohort of Italian graduates," Education Economics, Taylor & Francis Journals, vol. 23(2), pages 213-237, April.
    8. Freeman, Richard B. & Goroff, Daniel L (ed.), 2009. "Science and Engineering Careers in the United States," National Bureau of Economic Research Books, University of Chicago Press, number 9780226261898, October.
    9. Keith A. Bender & John S. Heywood, 2006. "Job Satisfaction Of The Highly Educated: The Role Of Gender, Academic Tenure, And Earnings," Scottish Journal of Political Economy, Scottish Economic Society, vol. 53(2), pages 253-279, May.
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    Cited by:

    1. Rycx, François & Santosuosso, Giulia & Vermeylen, Guillaume, 2022. "The Over-Education Wage Penalty among PhD Holders: A European Perspective," IZA Discussion Papers 15417, Institute of Labor Economics (IZA).
    2. Sholeh A. Maani & Le Wen, 2021. "Over-education and immigrant earnings: a penalized quantile panel regression analysis," Applied Economics, Taylor & Francis Journals, vol. 53(24), pages 2771-2790, May.
    3. Giuseppe Lucio Gaeta & Giuseppe Lubrano Lavadera & Francesco Pastore, 2022. "Overeducation wage penalty among Ph.D. holders: an unconditional quantile regression analysis on Italian data," International Journal of Manpower, Emerald Group Publishing Limited, vol. 44(6), pages 1096-1117, March.

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