This dissertation comprises four empirical chapters which contribute to the fields of inequality research and labor economics.
The first chapter examines the interaction between socioeconomic status, place of residence and life expectancy, which so far remains poorly understood. I contribute to deepening this understanding by, firstly, using administrative data from the German Pension Insurance to provide novel estimates for remaining life expectancy at age 65 by lifetime earnings quintiles and geographic areas (NUTS2). I show evidence for substantial heterogeneity in the link between lifetime earnings and life expectancy across NUTS2 regions in Germany. Subsequently, I use these life expectancy estimates together with a rich set of place characteristics to conduct a correlational analysis investigating which place factors are associated with longevity. Specifically, I examine whether place matters differently for individuals’ life expectancy depending on their socioeconomic status and whether this interaction between place factors, socioeconomic status and life expectancy has changed over time. Place factors associated with longevity are better healthcare supply, lower air pollution levels, lower regional poverty levels and a higher prevalence of healthy behaviors. Strikingly, the correlations between place factors and life expectancy appear to be homogeneous rather than heterogeneous in magnitude and direction for individuals at the top and the bottom of the lifetime earnings distribution. Furthermore, I find suggestive evidence that the importance of place for the life expectancy of low income individuals may have decreased over time.
While the second chapter of this thesis also investigates lifetime earnings, here we refrain from using administrative data. Instead, we use data from the Socio-economic Panel (SOEP) together with a dynamic microsimulation approach to facilitate lifetime analysis for a more comprehensive sample (including women, self-employed individuals and civil servants). The aim of this chapter is to advance understanding of the persisting gender earnings gap in Germany. First, we briefly investigate gender inequality in wages and annual earnings in the cross-section, which is mainly driven by gender differences in hours worked and accumulated work experience. Subsequently, we focus on the simulation of complete earnings biographies from SOEP data, which in the next step facilitates the investigation of the gender gap in lifetime earnings. We find evidence for an average gender lifetime earnings gap of 51.5% for birth cohorts 1964-1972. We show that this unadjusted gender lifetime earnings gap increases strongly with the number of children, ranging from 17.3% for childless women to 68.0% for women with three or more children. However, using a counterfactual analysis we find that the adjusted gender lifetime earnings gap only differs slightly by women’s family background.
In the third chapter, we examine the effect of an individual’s involuntary job loss on their partner’s actual and desired labor supply response. Thus—while existing research has found little to no evidence for an added worker effect in Germany—we shed light on the question of whether a desired added worker effect exists. Using data from the SOEP, we study individuals’ changes in actual and desired working hours after their partners’ involuntary job loss in an event study design. Our results show that neither desired nor actual working hours change significantly. These findings are robust for several sub-groups and for different econometric specifications. Therefore, we provide first evidence that the absence of the added worker effect is in line with individuals’ stated labor supply preferences and is not the result of an inability to realize desired working hours.
In the fourth chapter, we construct a comprehensive wealth distribution for Germany in order to inform the national and international debate on the distribution of wealth including pension entitlements. We estimate the net present value of pension wealth in Germany in 2012 and 2017 using SOEP data. To ensure international comparability, we also implement state-of-the-art methods to deal with two well- documented shortcomings of survey data. First, to address the undercoverage of assets such as financial and business assets, we uprate the survey data to macroeconomic aggregates. Second, in order to address the underrepresentation of the rich, we top-correct the survey data using rich lists. We show that including pension wealth increases German households’ wealth-income ratio from 570% to 850% in 2017. Furthermore, we provide evidence that pension wealth has an equalizing role by showing that the wealth share of the bottom 50% increases from 2% to 9% once pension wealth is included, while the wealth share of the top 1% declines from 30% to 20%.
