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This paper estimates size and impact factors of the gender pay gap in Europe. It adds to the literature in three aspects. First, we update existing figures on the gender pay gaps in the EU based on the Structure of Earnings Survey 2010 (SES). Second, we enrich the literature by undertaking comprehensive country comparisons of the gap components based on an Oaxaca-Blinder decomposition. Overall, we analyse 21 EU countries plus Norway, which clearly exceeds the scope of existing microdata studies. Third, we examine the sources of the unexplained gap. We find that about one third of the gap can be traced back to the role of the explanatory factors included in our analysis. Human capital related factors are of minor importance. Instead, the sectoral segregation of genders is identified as the most important barrier to gender pay equality in European countries. In addition, the fact that part-time positions are more frequent among women notably contributes to the gap. Furthermore, sector premiums are generally to men's advantage, this might point to a less advanta-geous within-sector positional sorting for women compared to men. We conclude that policies aiming at closing the gender pay gap should focus more on the sector level than on the aggregate economy.

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This study investigates the incidence of overeducation among graduate workers in 21 European Union countries and its underlying factors based on the European Labor Force Survey 2016. Although controlling for a wide range of covariates, the particular interest lies in the role of fields of study for vertical educational mismatch. The study reveals country differences in the impact of these factors. Compared to Social sciences, male graduates from, for example, Education, Health and welfare, Engineering, and ICT (Information and Communication Technologies) are less and those from Services and Natural sciences are more at risk in a clear majority of countries. These findings are robust against changes of the standard education. Moreover, some fields show gender-specific risks. We suggest that occupational closure, productivity signals and gender stereotypes answer for these cross-field and cross-country differentials. Moreover, country fixed effects point to relevant structural differences between national labor markets and between educational systems.