Higher education has long been pivotal for an individual’s monetary and non-monetary life chances (Gebel und Pfeiffer 2007). Sociological and economic discussions over the last decades have repeatedly questioned if this is still the case. Whereas higher education might lose its value as scarce good due to the expansion of education (Araki 2020; Horowitz 2018), the growing demand for highly educated workers in knowledge based societies might enhance the importance of higher education for the individual (Acemoglu und Autor 2011; Goldin und Katz 2008). From an individual perspective, especially the extent to which the momentary returns on education have changed over the last couple of decades can giving an indication if higher education is still worthwhile pursuing in economic terms (Mincer 1974; Becker 1964).

The second expansion of higher education started later in Germany than in other industrialized countries and the foremost expansion took place from 2000 to 2010. This development may lead to pressure on relative wages because on the one hand there are now more highly educated individuals available which leads to an increase in the supply of highly educated for the individuals relative to the educational status of the general population. On the other hand, an increase in highly educated workers may be beneficial for innovation and firm performance and therefore foster the demand for highly educated individuals and increase their wages relative to other education groups even further. However, it remains an empirical question to demonstrate which of these forces is stronger in Germany and to highlight and test possible explanations. In our paper we will therefore ask three questions: 1) How do wage and wage differentials develop in Germany? 2) Does the expansion of higher education explain the changes in wage and wage differentials? 3) Which other factors explain our findings?

Using statistical data and the German Socio-Economic Panel (GSOEP, v35) we look into the educational and occupational composition in Germany from 1996 to 2018, the development of employment status as well as educational wage differentials over the same time frame and our explanatory approaches. The analytic GSOEP sample is unbalanced and restricted to 206,904 observations of 26,632 employed individuals aged 25 to 65, 13,306 of which are women. Our subsamples contain women and men as well as people age 30 to 40 and age 40 to 55. The dependent variable is the natural logarithm of gross earnings per hour worked. The explanatory variable in focus is measured by the highest educational degree. We use the degrees provided by the GSOEP to reflect the special characteristics of the German education system: no educational degree, apprenticeship or vocational training, master craftsmanship including occupational academy and civil servant training and (applied) university. To calculate the wage differentials we estimate pooled OLS (1996-2018) with individuals with an apprenticeship degree as reference, as they still represent the majority of all degree holders. Our explanations are tested using different methodological approaches: First we regress the educational shares (vocational training degree and master craftsmen/university of applied sciences/university) of each individual year on the estimates educational wage differentials (n=23). Second we estimate the wage differentials for the younger cohorts (age 30-39) and also regress the educational shares of the whole sample on those estimates. Third, we estimate separate OLS-models substituting the type of higher education (university of applied science and university) with the study subjects. Due to data restrictions, we only calculate those for the later years 2012-2018. Finally, we explore the relationship between the growing wage inequality in Germany and the development of wages over time.

Our descriptives show that women experience a strong increase in labor force integration in our ob-servation window. The same holds true for men, but to a much lower extent. Over the 23 years un-der observation the average real wage more than doubled for all individuals aged 30 to 55 with an averaged annual wage growth of 3.3 percent. Yet, that wage growth differed between educational groups: employees with a degree of a university of applied sciences experienced the strongest growth rates whereas vocational training graduates had the lowest growth rates. The stratification of wage differentials by attained educational degree persists but the wage differen-tials for university graduates have lost their upward dynamic. Compared to degrees of universities of applied sciences, a university degree still yields higher returns for both sexes but the differences be-tween both types of higher education are higher for women than for men. Compared to degrees of universities of applied sciences, a university degree still yields higher returns for both sexes but the differences between both types of higher education are higher for women than for men. Turning to the expansion of higher education and the composition of study majors as explanatory factors for the described development of educational wage differentials we find that 1) the educa-tional expansion explains the described trend in wage differentials of university graduates but not as much of degree holders of universities of applied sciences, 2) younger women and men are more affected by the slightly negative trend in wage differentials, but there is also an impact on older graduates and 3) that the change is strongly driven by changes in the composition of study majors. Finally, we find that the increased wage competition between higher education graduates on the labor market results in an increased wage inequality.

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