Educational mismatch and wages: Evidence from a cross-country comparison.

Autor/in	Sun, Hongye
Titel	Educational mismatch and wages: Evidence from a cross-country comparison. Gefälligkeitsübersetzung: Bildungsinkongruenz und Löhne: Erkenntnisse aus einem länderübergreifenden Vergleich.
Quelle	In: Economic modelling, (2026) 155, Art. 107448, 30 S. PDF als Volltext Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	0264-9993
DOI	10.1016/j.econmod.2025.107448
Schlagwörter	Bildungsertrag; Einkommenseffekt; Mismatch; Bildungsadäquate Beschäftigung; Unterqualifikation; Überqualifikation; Internationaler Vergleich; Auswirkung; Einflussfaktor; Geschlechtsspezifik; OECD (Organisation für wirtschaftliche Zusammenarbeit und Entwicklung); Abhängig Beschäftigter
Abstract	"Rapid technological change and educational expansion raise fundamental questions about educational mismatch and efficient human capital allocation. This study employs an OECD-administered survey to identify educational mismatch using self-assessment measures and to investigate its wage effects across 20 countries. The results show that overeducated workers earn 14% less than their adequately matched counterparts, whereas undereducated workers earn 10% more. Furthermore, gender-disaggregated analysis reveals that women experience larger penalties for overeducation and smaller premiums for undereducation than men. Propensity score matching estimates indicate substantial cross-country heterogeneity in wage effects, with particularly large penalties in Spain, Korea, and Japan, implying that rigid labor market regulation with limited occupational mobility yield larger penalties, while countries with well-developed vocational systems exhibit smaller effects. This study provides novel comparative evidence on the causal wage effects of educational mismatch and underscores the importance of institution-specific policies linking education quality, labor market flexibility, and lifelong learning." The study refers to the period 2011-2014 (Author's abstract, IAB-Doku, © 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.).
Erfasst von	Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg
Update	2026/2