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Magnitude and Impact Factors of the Gender Pay Gap in EU Countries
Report financed by and prepared for the European Commission
• Sector affiliation and working hours are the main drivers of the gender earnings divide in EU countries
Today, HWWI has published a report financed by and prepared for the European Commission. The study undertakes a comprehensive analysis of the sources of wage differences between male and female workers in Europe. To this end, the 2010 wave of the Structure of Earnings Survey (SES), the 2013 wave of the EU Statistics on Income and Living Conditions (SILC) and the 2013 wave of the EU Labour Force Survey (LFS) were explored. Corresponding to the three data sets, the study consists of three modules which build on each other. A non-technical summary precedes the comprehensive report. In what follows, some core results of the study are highlighted.
Based on SES data for 21 EU countries plus Norway, we measure the European (country overarching) gap in average wages of men and women to be about 15.3% in 2010. This is slightly lower than the most recent result of 16.1% published by Eurostat for 2014. Apart from the different time of measurement, this discrepancy is explicable by the fact that some countries faced data constraints with respect to the potential sources of the gap which are analysed in this study. The study therefore refers to 21 EU-countries plus Norway.
About one third of the overall gap (4.4%) can be traced back to the role of influences accounted for in our analysis. A wage difference of 10.9% remains as the unexplained gap. Hence, women earn 10.9% less than men even when gender differences in educational attainment, occupational choice, working hours and other observable attributes have been taken into account. However, at country level the picture varies considerably (see the diagram below). The overall gap ranges from 3.6% for Poland to 25.1% for Estonia. From a geographical perspective, it is noteworthy that 7 out of 10 Middle and Eastern European states exhibit gaps clearly below average, with the Czech Republic, Slovakia and Estonia marking the exceptions. Among the West European countries, only Italy exhibits a very small gap (4.5%). That is, countries with low wage gaps tend to be characterized by low female labour market participation, suggesting the existence of a positive selection of working women with respect to productivityrelevant characteristics and/or a trade-off between familycompatible jobs and jobs offering attractive pay.
Splitting the gap into single driving factors reveals considerable variation across countries. However, there is a range of countries where gender discrepancies in job-related characteristics explain significant portions of the overall gap. Specifically, a significant part of the gender pay gap is due to the fact that women are overrepresented in industries with low pay levels.
The unexplained gap is positive everywhere and makes up the largest part of the overall gap in all countries except Germany and Norway. In interpreting these figures, it is important to stress that the unexplained wage differential must not be equated with the extent of gender discrimination in wage setting.
Additional insights are gained from the EU-SILC data based on 31 countries, particularly with respect to the household context. In many countries, the wage premium for being married is higher for men than for women. Adding to the higher incidence of marriage among men in our sample of workers, marriage contributes to the pay gap. The presence of inactive household members also amplifies the pay gap, whereas unemployed household members in total have a mitigating effect.
Finally, the LFS data revealed an EU-wide share of overeducated workers amounting to 27% for highskilled and 19% for medium-skilled workers in 2013. These discrepancies are consistent with previous work (e. g. European Commission 2012). Gender differences are negligible for the mediumskilled, whereas among graduates men are slightly more at risk to be overeducated. Despite notable earnings penalties, overeducation does not contribute significantly to the gender pay gap, as gender differences in overeducation incidence are rather small. Moreover, the probability of overeducation decreases with increasing job tenure. Furthermore, the risk notably varies with age, education, field of study and household context. In all, the persistent EU-internal country differences in educational mismatch show that the European community is still far away from reaping the full benefits from crossborder labour migration created by the common market legislation.
In summary, the report identifies gender differences in industry affiliation and working hours as the two main drivers of the gender earnings divide in Europe. By contrast, due to a tremendous heterogeneity on the country level, occupational segregation rather takes a back seat on the European level, but interacts with gender differences in industry and hours worked. Inferences drawn from this study address politics, firms and social partners. Policies combating gender stereotypes and boosting fathers’ family engagement seem to be promising. The same applies to innovative leadership models balancing employees’ family and work demands, strategies aiming to cut the cost of time flexibility and measures to promote a revaluation of ‘female’ work. Thus, collaborative effort is required to close the gap.
Please find the full report here: http://www.hwwi.org/fileadmin/hwwi/Publikationen/Publika-tionen_PDFs_2016/Magnitude_And_Impact_Factors.pdf
And 22 country fiches here: http://hwwi.org/fileadmin/hwwi/Publikationen/Publika-tionen_PDFs_2016/Magnitude_And_Impact-Factors_Country_Fiches.pdf
On the European Commission’s website you find the corresponding docu-ments here: http://ec.europa.eu/justice/gender-equality/document/index_en.htm#pay
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