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Gender wage growth gaps across fields of study in Europe

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Gender wage growth gaps across fields of study in Europe


In spite of the substantial decline in gender differences in labour market outcomes observed over the last few decades in developed countries, substantial gender gaps remain. As discussed in Blau and Kahn (2017), gender gaps in terms of conventional human capital variables are now small, particularly among highly educated individuals. However, a gender pay gap persists, and is more pronounced at the top of the wage distribution.

The dynamics of the gender wage gap during the early career

Empirical evidence of a widening overall gender gap after several years in the labour market has been found in the UK (Manning and Swafield 2008) and the US (Goldin 2014, Erosa et al. 2016). Interestingly, similar findings are reported among a more homogenous sub-sample of the population, such as university graduates, MBAs from top business schools, or associate lawyers (Goldin 2014, Goldin et al. 2017, Azmat and Ferrer 2017). Bertrand et al. (2010) document a male earnings advantage reaching almost 60 log points a decade after MBA completion from a top US business school. Francesconi and Parey (2018) study gender gaps in university and labour market performance twelve to eighteen months after graduation in Germany. They estimate a gender gap of five to ten log points, even after including a large set of controls. Albrecht et al. (2018) track, for 20 years, individuals who completed a university degree in business or economics in Sweden, and show that although women and men had essentially identical wages and earnings at the start of their careers, their career paths diverge substantially as they age. 

Interestingly, among university graduates, Goldin (2014) documents substantial heterogeneity across fields of study in the evolution of the gender gap for the US, with occupations that exhibit nonlinear earnings with respect to hours presenting larger gaps. According to Goldin, the desire for time flexibility due to the arrival of children lies behind the growing divergence between men’s and women’s wages over the lifecycle in occupations with nonlinear wages. 

In a recent paper (Sánchez-Mangas and Sánchez-Marcos 2020), we follow a similar approach to Bertrand et al. (2010) in order to examine the dynamics of wages after graduation across fields of university education. Our sample is made up of European university graduates. 


The literature has pointed out different reasons why men’s and women’s wages may diverge over  their careers. First, according to the human capital theory pioneered by Mincer (1974) and Becker (1993), if the burden of raising children is borne primarily by mothers, women may be less attached to the labour market than men, which may erode their future wages. Second, according to Topel and Ward (1992), job mobility is responsible for one-third of wage growth in the first ten years after labour market entry among US men. If women are more constrained than men in opportunities to change jobs, this may widen the gender wage gap over the lifecycle. Third, as found by Fortin (2008), gender differences in preferences for money/work versus people/family played a significant role when accounting for the gender wage gap among young adults during the mid-1980s in the US. Fourth, individual attitudes such as willingness to compete, risk preference, and negotiation behaviour may be responsible for gender differences in the evolution of wages. As argued by Bertrand (2011) and Goldin (2014), the extent to which psychological perspectives on gender can account for gender gaps in the labour market remains an open question. However, a recent contribution from Card et al. (2016) found that the combination of sorting and bargaining effects explains about one-fifth of the cross-sectional gender wage gap in Portugal. Finally, discrimination may lie behind gender differences in wages, based either on the taste-based discrimination theory pioneered by Becker (1957), or the statistical discrimination theory formulated by Arrow (1973) and Phelps (1972). It is of course important to know the extent to which a bias exists against women with children, or against young women who may have children in the future. Regarding this question, Petit (2007) finds evidence of discrimination against women among young workers in higher-skilled positions in the French finance industry, but not among prime-age workers. More research along these lines is certainly needed.

Our findings for Europe

We use the Flexible Professional in the Knowledge Society (REFLEX) for our analysis. REFLEX is a retrospective data set that collects the results of a survey of graduates from education level ISCED 5A who were interviewed approximately five years after their graduation in 1999-2000. Our sample of 7,429 observations includes individuals from Austria, Belgium (only Flanders), Finland, France, Germany, Italy, the Netherlands, Spain, the UK, Portugal, and Norway. 

Figure 1 Female coefficient of log wage regression

Gender wage growth gaps across fields of study in Europe 2

In Figure 1, we report the gender wage gap at the entrance to the labour market in the first job after graduation, and in the job held five years after graduation. This is the gap after we control for differences in subfield of study, occupation, and industry. In the full sample, we find a gap in the first job of four log points, but there is substantial heterogeneity across fields of education. The gap is only significant in STEM (eight log points), and in Health (six log points). Over the early career (five years after graduation), there is a substantial increase in the gender wage gap. In the full sample, the gap increases up to seven log points. The gap in the job held five years after graduation is larger than in the first job in most categories; exceptions are STEM, in which a reduction from eight to five log points is observed, and education, humanities and the arts, in which the gap remains insignificant. There is a remarkable increase of eight and nine log points in economics, business and law, and in the social sciences, respectively.

We then turn our attention to gender differences in individual annual wage growth during the early-career phase and explore possible drivers. Inspired by recent literature on the wage dynamics of men and women – see Angelov et al. (2016),  Kleven et al. (2018 and 2019), and De Quinto et al. (2020) – we pay attention to the divergence in wages between men and women depending on the arrival of children between the first job and the job held five years after graduation. In Figure 2, we report the female (annual) wage growth penalty after we control for differences in subfield of study, occupation, and industry, but also for differences in job mobility (as measured by the number of jobs held since graduation and changes in occupation) and human capital (as measured by the number of hours worked in the first job, the number of months employed since graduation, and job tenure). We estimate a significant gap of 1.0 percentage points for the full sample among those who became parents, but an insignificant gap for those who remained childless. Again, there are striking differences across fields of study. In particular, only within economics, business, and law is a significant female penalty estimated. In these fields, women who became mothers during the period of analysis exhibit a wage growth penalty of 2.5 percentage points compared to fathers, remarkably higher than the female wage growth penalty of 1.1 percentage points found among childless individuals. Importantly, variables capturing individual differences in job mobility and human capital play a modest role in accounting for gender differences in wage growth (this is not surprising since differences between men and women in these regards are small in our sample). By contrast, in other fields of study, the female wage growth gap either is not significant or becomes insignificant after we control for education subfields or industry and occupation. Finally, including the individual self-reported ability to negotiate as a control variable left the estimated gender gap unchanged.

Figure 2 Female penalty in annual wage growth (percentage points)

Gender wage growth gaps across fields of study in Europe 3

Our findings are in line with Bütikofer et al. (2018), who observe a child earnings penalty for mothers that is larger among MBAs and lawyers than among STEM and medicine graduates in Norway, and in line with the evidence reported in Goldin (2014) for the US. Finally, according to our analysis, only a small fraction of the gender wage growth gap can be attributed to gender differences in labour market attachment or in job mobility. Therefore, most of the gender wage growth gap in economics, business, and law remains unexplained, which is consistent with Albrecht et al. (2018) for the group of high-skilled individuals in Sweden.


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