Gender Pension Gaps
In my dissertation I explore through which mechanisms Gender Pension Gaps are related to work-family life course patterns or specific aspects of work and family lives.
Women in Europe receive much less pension income compared to men. Based on the life course perspective and the pertinent gender literature I argue that previous approaches risk concealing complex inequality (re)producing mechanisms that arise over the life course and shape these Gender Pension Gaps (GPG). Particularly, the existing empirical literature on GPGs lacks a multidimensional, gender- and life-course-sensitive analysis by focussing predominantly on the impact of employment. This thesis aims to implement novel methodological approaches to analyse gendered pension income inequalities considering gendered life course complexities and contribute empirically to our understanding of how GPGs unfold.
I apply Sequence analysis, decomposition, and feature selection techniques to assess and quantify the relation between gendered work-family life courses, or specific life course aspects, with gendered pension income inequality. Comparing the analyses across country contexts or pension types reveals how these associations are channelled through different pension designs.
The results reveal that, independently of the pension system and methods applied, the overarching driver of the GPGs is the large amount of unpaid care work that only women performed over their life courses and that is not equivalently rewarded in pension systems compared to other activities. Particularly, typical life courses with strong interdependences between family and work are only experienced by mothers and are highly associated with GPGs. In other words: gendered pension inequality emerges due to an interaction of i) welfare state contexts of the 20th century which incentivised a traditional gendered division of labour and gender inequalities arising therefrom, with ii) pension policies rewarding gendered life courses emerging from it highly unequally nowadays. I conclude that pension policymakers must consider this intertemporal interaction of present pension designs and past welfare state policies for pension reforms if they aim to prevent a severe reproduction of accumulated gender inequalities in old age.
Published
Life-course-sensitive analysis of group inequalities: Combining sequence analysis with the Kitagawa-Oaxaca-Blinder decomposition
With Emanuela Struffolino & Anette Fasang
Processes that unfold over individuals’ life courses are often associated with inequalities later in life. The literature lacks methodological approaches to analyze inequalities in outcomes between groups, for example, between women and men, in a life-course-sensitive manner. We propose a combination of methods—of sequence analysis, which enables us to study the multidimensional complexity of life courses with Kitagawa–Oaxaca–Blinder decomposition. This approach allows us to distinguish the share of inequalities between groups that is due to group-specific life courses from the share that is due to group-specific returns to similar life courses. We illustrate the combination of the two methods by analyzing work–family life courses and gender pension gaps in Italy and Germany. Our contribution is to systematically compare possible core analytical choices when combining typologies derived using sequence analysis with the Kitagawa–Oaxaca–Blinder decomposition. For future applications, we propose a set of practical guidelines for sequence analysis–Kitagawa–Oaxaca–Blinder decomposition..
Video recording of paper presentation
In Review
Differences in Gender Pension Gaps in public and private pensions in West Germany: Which role do work-family life courses play?
How are work-family life courses associated with the Gender Pension Gap (GPG)? Do these mechanisms vary between the gender gap in public compared to private pensions? I assess these questions by applying an innovative combination of the Multichannel Sequence Analysis with the Kitagawa-Blinder-Oaxaca decomposition and linking survey to register data for Germany to decompose GPGs based on work-family life courses. Additionally, I decompose GPGs based on the relative earning positions of individuals over the life course. Differentiating between pension types sheds light on the impact of pension privatization and provides more targeted suggestions for policy makers. The results reveal that gender differences in life course patterns mirroring gender inequalities of current cohorts in labour force (e.g. Gender Wage Gap) drive the GPG in private pensions to a higher extent than the gap in public pensions highlighting the risk of high GPGs in the future.
Full-time employment is all that matters? Decomposing Gender Pension Gaps based on relevant life course features in Germany & the Netherlands
Gender Pension Gaps (GPG) are so far either analysed based on selective sets of life course summary measures, mostly the duration in full-time employment, or based on life course typologies. Whereas the first approach neglects other dimensions such as the timing or ordering of events over the life course of other work and family categories, the latter risks concealing specific attributes of life courses particularly relevant for pension income inequality. This study contributes by, first, applying the Life Course Feature Selection to identify which work and family life course aspects are the most important pension income predictors. The second step decomposes the GPG based on these relevant life course aspects, revealing how they are related to gendered pension income inequality. Comparing the results across the different pension regimes of Germany and the Netherlands provides insights on whether similarly gendered life course aspects are differently related to GPG across different pension designs. Results show that aspects of all life course dimensions (duration, timing, ordering, and complexity) play a role for pension inequality. Life course aspects related to unpaid care work, particularly the years engaged in care work, are among the most relevant pension predictors in both countries. Contrary to what previous literature suggested, the duration of full-time employment plays a much less important role.
The non-parametric Ñopo decomposition reveals that the extremely gender-specific combination of the observed life course experiences, particularly regarding care work, is the main contributor to the Gender Pension Gap in both countries. Highlighting the relevance of specific life course aspects allows policy makers to employ more targeted policies to prevent the reproduction of gender inequalities over the life course in old age. Furthermore, the results advice to consider life course proxies beyond the years spent in (full-time) employment as well as the extremely gender-specific combination of life course aspects.