For the empirical analysis of both questions, an occupational panel was generated on the basis of the sample of the Integrated Labor Market Biographies (SIAB) and the Microcensus, which made it possible to trace longer-term trends in occupational gender segregation and their interaction with other occupational characteristics. The results of these analyses were used to identify inequality-relevant indicators of occupational structure. These were then fed into NEPS data for Starting Cohort 6 to examine how occupational characteristics translate into gender inequalities in non-monetary labor market outcomes and how they affect the gender wage gap.
1. Project phase
In the first project phase, we described long-term trends of occupational sex segregation in Germany and analysed how the share of women in an occupation is causally related with other occupational characteristics, such as wage levels, shares of part-time work, and qualification structure. The findings of these analyses were then used to investigate how various occupational characteristics generate individual gender inequalities in career progressions. Thus, the first project phase focused on the importance of occupational sex segregation for non-monetary aspects of labour market inequalities between women and men.
2. Project phase
Occupational gender segregation, however, is also central in explaining the gender wage gap in Germany. Yet, it was unclear why occupations dominated by women pay less: Is the mere proportion of women responsible for the gender wage gap, or are other occupational characteristics linked to female-typical occupations the decisive mechanisms? If this is true, how has the influence of different occupational characteristics on the gender wage gap changed throughout the last 30 years in Germany?
To answer these questions, we explored in the second phase of our project how the gendered structure of occupations affects the wages of women and men and how this relationship changed since the mid-1970s in Germany. The analyses were based on a unique new wage data ont the individual level: NEPS Starting Cohort 6 was linked with register data of the Institute for Employment Research (IAB). Thus they additionally contain rich longitudinal wage and firm information for respondents. For modelling and decomposing the gender wage gap, we merged these individual data with occupational panel data generated in the first project phase and enriched these data with occupational activity profiles.