Overeducation Wage Penalty among Ph.D. Holders: An Unconditional Quantile Regression Analysis on Italian Data

Giuseppe Lucio Gaeta (), Giuseppe Lubrano Lavadera and Francesco Pastore
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Giuseppe Lucio Gaeta: University of Naples L’Orientale

No 11325, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: The wage effect of job-education vertical mismatch (i.e. overeducation) has only recently been investigated in the case of Ph.D. holders. The existing contributions rely on OLS estimates that allow measuring the average effect of being mismatched at the mean of the conditional wages distribution. This paper, instead, observes the heterogeneity of the overeducation penalty along the wage distribution and according to Ph.D. holders' study field and sector of employment (academic/non-academic). We implement a Recentered Influence Function (RIF) to estimate an hourly wage equation and compare PhD holders who are over-educated with those who are not. The results reveal that overeducation hits the wages of those Ph.D. holders who are employed in the academic sector and in non-R&D jobs outside of the academic sector. Instead, no penalty exists among those who carry out R&D outside the Academia. The size of the penalty is higher among those who are in the mid-top of the wage distribution and hold a Social Science and Humanities specialization.

Keywords: wages; Ph.D. holders; unconditional quantile regression; overeducation; job-education mismatch; Italy (search for similar items in EconPapers)
JEL-codes: C26 I23 I26 J13 J24 J28 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2018-02
New Economics Papers: this item is included in nep-edu, nep-eur, nep-lma and nep-ltv
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Citations: View citations in EconPapers (1)

Published - published in: International Journal of Manpower, 2023, 44 (6), 1096-1117

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Related works:
Journal Article: Overeducation wage penalty among Ph.D. holders: an unconditional quantile regression analysis on Italian data (2022)
Working Paper: Overeducation wage penalty among Ph.D. holders. An unconditional quantile regression analysis on Italian data (2018)
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