It is well established that, on average, women – even those with equivalent education and experience – earn less than men in all advanced societies (Bertrand 2010, Bertrand and Duflo 2017). It is also well established that, since the 1960s, the pay gap between women and men has narrowed substantially but has not disappeared. In the US, for instance, the ratio of the average (mean) full-time equivalent earnings of female workers to that of their male counterparts has increased from about 0.6 (in the period from 1960 to 1980) to approximately 0.8 in 2015 (Blau and Kahn 2017). These figures are similar to those found in UK Canada, the Netherlands, and Finland. For other countries, such Australia, Belgium, France, Italy, Spain, Denmark, Norway, and Sweden, the gap is smaller but still favours men; while for others, such as Korea and Japan, it is much larger (see Olivetti and Petrongolo 2016). This narrowing of the gap in pay reflects the converging economic roles of men and women in the labour market, a reality that is among the most considerable social and economic advances over the last 100 years.
There are many aspects to this convergence and, equally, there are many aspects to the remaining gap. Since the inﬂuential survey by Altonji and Blank (1999), economists have offered a variety of new explanations about gender gaps. Bertrand (2010) provides an insightful review of recent contributions, drawing on advances in the psychology and experimental literatures. Her review emphasiaes the importance of gender differences in risk preferences, attitudes toward competition and negotiation, and the strength of other-regarding preferences as well as the importance of social norms that may induce differential sorting of men and women across occupations. Recently, Costa Dias et al. (2018) have emphasised the role of fertility and differences in career patterns with the arrival of the first child. In another recent survey looking at a large sample of high-income countries, Olivetti and Petrongolo (2016) stress the role played by changes in the industry structure with the shift from manufacturing to services, which might have increased female employment and reduced (but not eliminated) the gender wage gap.
In recent work, we revisit one of the main factors discussed by Altonji and Blank as a source of gender differentials, that is, differences in human capital accumulation (Francesconi and Parey 2018). We follow this approach to study gender gaps in Germany, which provides an extremely interesting case for this analysis. Germany is the fourth largest economy in the world, with a highly educated population and one of the most skilled workforces. Germany also has a longstanding body of anti-discrimination laws. In terms of the economy, Germany has signiﬁcantly increased its competiveness over recent years (Dustmann et al. 2014). But at the same time, the gender pay gap remains high in international comparison. For example, OECD (2012, Figure 13.1) shows that among OECD countries, Germany is among the countries with the highest pay gap among full-time employees (data for 2009-10).
Early gaps in university education and pay
We make use of a unique data source, collected by the German Centre for Higher Education Research and Science Studies (DZHW), which allows us to analyse a representative survey of six cohorts of university graduates between 1989 and 2009 from all ﬁelds of study and across the range of higher education institutions in Germany, soon after they complete their college education. The DZHW survey also follows the same individuals ﬁve to six years into their careers. We focus only on the ﬁrst snapshot after graduation. The reason is that career opportunities within the ﬁrm (which may involve ﬁrm-speciﬁc investment, ability to negotiate with employers, or internal promotions) as well as other crucial family-related decisions (such as starting a family and committing resource allocations within the household) are likely to be less relevant than later on in life.
Our analysis provides new evidence on a variety of facets of gender gaps. We consider two broad sets of outcomes. The ﬁrst refers to the educational performance of men and women while they are at university and explores gender differentials in enrolment rates, marks at university entry (i.e. secondary school grades), graduation rates and graduation marks. The second set refers to early labour market performance and focuses on gender differences in the probability of having a full-time job and in pay within 12 to 18 months after graduation.
We emphasise six main ﬁndings on the gender gap in university education.
- Since the mid-1990s, roughly equal numbers of men and women enrol in higher education programmes in Germany.
- Conditional on having completed college, women enter university with better secondary school marks.
- At the end of their university career, more women than men obtain a degree. This is consistent with differential dropout rate by gender, which might have consequences for the cohorts of male and female graduates entering the labour market.
- There is some persistent educational specialisation by gender, with substantially more men in STEM subjects and more women in arts and humanities, although this segregation has lessened in recent years.
- Female graduates do not outperform male graduates in terms of ﬁnal exit marks. The difference reveals a better performance among male graduates. This is clearer when we look at the top of the ﬁnal university grade distribution, whereby men are 3.5 percentage point more likely to obtain top grades than women over the whole sample period.
- Gender gaps in graduation marks differ by ﬁeld of study. When we pool graduation cohorts, we detect larger differentials among graduates in the humanities and STEM subjects. The reversal of relative performance at the end as opposed to the start of the university career is interesting and, to our knowledge, new. This again might reﬂect a greater dropout rate among men. But it might also reﬂect other factors (such as men achieving maturity and catching up with women in terms of academic skills, or universities offering programs that are better suited to men’s than to women’s abilities), which deserve more research in the future.
On the pay gap, the results confirm what has been found for the population at large in many other countries, even though we look at fresh graduates. Twelve to 18 months after graduation, the raw (unadjusted) gender gap in full-time monthly earnings is about 20 log points on average, even though male and female full-timers work relatively similar hours. Including a large set of controls reduces (but does not eliminate) the gap to 5–10 log points, with the lion’s share of the reduction being accounted for by ﬁeld of study at university. There is heterogeneity in the magnitude of the gender pay gap by ﬁeld of study, with the largest differentials emerging among graduates from economics/business and STEM subjects. Once the full set of controls is taken into account, the remaining wage gap is about 8 log points across all available cohorts. As mentioned, within-firm career opportunities (such as ‘inability to ask’ or promotions) and family-related choices (such as children) are likely to be less relevant for men and women soon after their college graduation than later in life.
Where we stand
Several channels may be at work behind our results. One could be related to human capital considerations. The importance of ﬁeld of study indicates the relevance of pre-market choices. These also interact with subsequent market decisions (such as occupational choice) at the very beginning of professional careers (e.g. Liu 2016). In turn, such choices could be partly driven by gender diﬀerences in preferences (e.g. risk aversion and time discounting), self-conﬁdence, competitiveness, earnings expectations, and valuation of non-wage beneﬁts (e.g. Buser et al. 2014, Mas and Pallais 2017, Reuben et al. 2017). Another possible channel is related to statistical discrimination against women, based on employers’ difficulty in distinguishing more from less career-oriented women (e.g. Gayle and Golan 2012, Reuben et al. 2014). These mechanisms deserve more attention in future research.
A number of relevant research questions emerge in order to inform the next steps forward in terms of policy.
- As universities critically look at their programmes in terms of the challenges of new technologies and labour market demands, what are the possibilities to further address gender imbalances in university related choices, given (for example) the strong link between field of study and labour market opportunities?
- How can firms be put in a position to allow greater flexibility to their workers without compromising career prospects? For instance, what makes temporal flexibility (which might benefit women in specific professional careers) difficult to achieve, resulting in non-linearity in number of hours (and the particular hours) worked?
Progress on these research questions can ultimately contribute to convergence in pay between genders (for example, through technological and institutional changes) and in turn improve well-being in our society. The recent emergence of a gender focus in higher education research is an encouraging sign in this direction.
Altonji, J G and R Blank (1999), “Race and Gender in the Labor Market”, in O Ashenfelter and D Card (eds), Handbook of Labor Economics, volume 3C, pp. 3144–3259. Amsterdam: Elsevier.
Bertrand, M (2010), “New Perspectives on Gender”, in O Ashenfelter and D Card (eds), Handbook of Labor Economics, volume 4B, pp. 1545–1592. Amsterdam: Elsevier.
Bertrand, M, and E Duﬂo (2017), “Field Experiments on Discrimination”, in A Banerjee and E Duﬂo (eds), Handbook of Field Experiments, vol. 1, pp. 309–393. Amsterdam: Elsevier.
Blau, F D and L M Kahn (2017), “The Gender Wage Gap: Extent, Trends, and Explanations”, Journal of Economic Literature 55(3): 789–865.
Buser, T, M Niederle, and H Oosterbeek (2014), “Gender, Competitiveness, and Career Choices”, Quarterly Journal of Economics 129(3): 1409–1447.
Costa Dias, M, R Joyce and F Parodi (2018), “The gender pay gap in the UK: children and experience in work”, IFS Working Paper 18/02.
Dustmann, C, B Fitzenberger, U Schönberg, and A Spitz-Oener (2014), “From the Sick Man of Europe to the Economic Superstar: Germany’s Resurgent Economy”, Journal of Economic Perspectives 28(1): 167–188.
Francesconi, M, and M Parey (2018), “Early Gender Gaps Among University Graduates.” CEPR Discussion Paper No. 12754; forthcoming in European Economic Review.
Gayle, G-L, and L Golan (2012), “Estimating a Dynamic Adverse-Selection Model: Labour-Force Experience and the Changing Gender Earnings Gap 1968–1997”, Review of Economic Studies 79(1): 227–67.
Liu, K (2016), “Explaining the Gender Wage Gap: Estimates from a Dynamic Model of Job Changes and Hours Changes”, Quantitative Economics 7(2): 411–447.
Mas, A, and A Pallais (2017), “Valuing Alternative Work Arrangements”, American Economic Review 107(12): 3722–3759.
OECD (2012), Closing the Gender Gap, Paris: OECD Publishing.
Olivetti, C, and B Petrongolo (2016), “The Evolution of Gender Gaps in Industrialized Countries”, Annual Review of Economics 8: 405–434.
Reuben, E, P Sapienza, and L Zingales (2014), “How Stereotypes Impair Women’s Careers in Science”, Proceedings of the National Academy of Sciences 111(12): 4403–4408.
Reuben, E, M Wiswall, and B Zafar (2017), “Preferences and Biases in Educational Choices and Labour Market Expectations: Shrinking the Black Box of Gender”, Economic Journal 127(604): 2153–2186.
NB: This blog was originally posted on Vox EU