Which are the most important life course aspects for wealth inequality in older age? Life course aspects cover the duration in specific states (e.g. the years being married), the order of events (e.g. marriage or divorce before or after childbirth), the timing of events (e.g. first child born at which age of parents) as well as the complete complexity of life courses. We first focus on family life courses and assessed how the relevant features are related to wealth inequalities, focussing particularly on the differences between men and women.

Next, we also consider work life courses, next to the family dimension, and use the selected life course variables to decompose the Gender Wealth Gap.

Looking ahead, we are going to include country comparisons to assess to what extent country contexts such as norms and policies shape these mechanisms and include working life courses besides family life courses.

Published

Uncovering what matters: Family life course aspects and personal wealth in late working age

With Nicole Kapelle

Background: Capturing the complexity of family life courses as predictors of later-life outcomes like wealth is challenging. Previous research has either (a) assessed a few selective but potentially irrelevant summary indicators, or (b) examined entire life-course clusters without identifying specific important aspects within and between them.

Objective: Our aim is to investigate which family life-course variables that capture the order, duration, and timing of states and transitions are key personal wealth predictors for Western Germans aged 50 to 59, and to analyse the strength and direction of associations between the relevant variables and personal wealth, and whether these differ by gender.

Methods: We used German Socio-Economic Panel (SOEP) data and combined feature selection, sequence analysis tools, and regression techniques.

Results: We identified 23 family life-course variables as relevant predictors, with 2 – the time spent never-married, with and without children – deemed most relevant. Most family life-course variables were negatively associated with personal wealth and characterised by single parenthood, marital separation, or early marital transitions with or without fertility transitions. The prevalence and significance of some of the associations between these variables and personal wealth differed across genders. The results highlight the importance of previously concealed family life-course variables for wealth inequalities in late working age.

Contribution: We extend previous research on the nexus between family demography and wealth stratification by using a novel, data-driven approach that more effectively explores family life-course complexities by considering the ‘entire’ universe of variables that describe such life courses and identifying those life-course variables that are relevant wealth predictors.

Published paper Working paper

Work in progress

Decomposing the Gender Wealth Gap in late working age based on the most relevant family and work life course aspects

With Nicole Kapelle

Less is known about the Gender Wealth Gap (GWG) and its drivers although private wealth is crucial for older-age financial well-being. Previous literature focuses on the role of cross-sectional employment characteristics or the employment duration when assessing the drivers of the GWG. However, these studies do not consider complexities over the life course beyond the duration in selected states, such as when or in what order transitions happen, and neglect the interlinked relationship between the family and work domain. Empirically addressing such complexity in family and work-life courses has, however, been challenging. The present study addresses this shortcoming by using a feature selection approach to detect the most important wealth-related life course predictors—paying attention to the timing, duration, order, and complexity of work-family life courses. Next, we decompose the GWG based on these predictors. The results suggest that the most important wealth predictors are the duration in education and unemployment – life course proxies that have been assessed previously. However, many variables follow that are related to more complex life course dynamics, such as the order and timing of events. Additionally, family life course states are important wealth predictors. Gender-specific results unveil further that life course wealth predictors differ largely across genders, with men-specific wealth predictors related to unemployment and full-time employment being more commonly covered in previous literature. However, the decomposition results suggest that predictors for women’s life courses tend to be more important drivers of the gender wealth gap. This is because comparable men do not experience similar combinations of life course aspects including homemaking and the unpredictability of working lives that are related to lower wealth.