Linked lives, linked retirement? Relative income differences within couples and gendered retirement decisions in Europe

Gendered life courses and cognitive functioning in later life: the role of context-specific gender norms and lifetime employment

With increasing life expectancy, dementia poses an epidemiological challenge. As a cure has not been developed, the investigation into preventive factors becomes pivotal. Previous research emphasizes the cognitively stimulating and socio-emotional benefits of lifetime employment, but research on heterogeneous patterns across social groups and societal contexts remains sparse. Sociological approaches have a promising potential to provide insights into health inequalities and can contribute to the study of this major societal challenge. We investigate the influence of previous employment biographies on cognitive functioning for men and women aged 50 to 75 in 19 European countries, using longitudinal and retrospective information from the Survey of Health, Ageing and Retirement in Europe. We link individual information on employment biographies and cognitive functioning to contextual measures of gender norms, using aggregated agreement rates to both men's and women's role in employment and family. We find that previous employment affects cognitive functioning men and women differently. Part-time employment is beneficial for women's cognitive functioning, but not for men's. Traditional gender norms are associated with lower levels of cognitive functioning for both genders and moderate the linkage between previous employment and cognitive functioning. In contexts with more traditional gender norms, men's part-time employment is associated with lower and women's part-time employment with higher cognitive functioning. We conclude that employment and non-employment participation can, depending on characteristics of individuals and contexts, benefit or hinder the life-course accumulation of cognitive reserve, and those with norm-deviating behaviour are disadvantaged.

Health among workers retiring after the state pension age: a longitudinal and comparative study

BACKGROUND

In recent decades, many countries have observed increasing labor force participation beyond the state pension age (SPA). However, there is a lack of research on employment beyond SPA and how it relates to older workers' health. Moreover, there is a need to better understand how institutional factors affect the relationship between older workers' employment and health. In this study, we examine simultaneous employment and health trajectories over 11 years in 12 countries from Europe and the Americas, and study how these trajectories differ by welfare state regime and level of old-age pension redistribution.

METHODS

We used a harmonized pooled-country dataset of 3699 older workers based on four representative panel surveys: the Survey of Health, Ageing and Retirement in Europe (SHARE), the English Longitudinal Study of Ageing (ELSA), the Health and Retirement Survey (HRS), and the Chilean Social Protection Survey (EPS). We conducted multichannel sequence analysis to estimate the types of simultaneous employment-health trajectories, and multinomial regression analysis to examine the relationship between trajectory types and institutional factors.

RESULTS

We found that late retirement was equally associated with poor and good health. There is also a higher prevalence of late retirement trajectories in combination with poor health in liberal welfare regimes and in countries with lower levels of old-age pension redistribution.

CONCLUSION

Our study indicates that nonliberal welfare regimes and redistributive old-age pension policies may be better suited to protect vulnerable workers while providing those in good health with the opportunity to work beyond the SPA.

Does Machine Learning Offer Added Value Vis-à-Vis Traditional Statistics? An Exploratory Study on Retirement Decisions Using Data from the Survey of Health, Ageing, and Retirement in Europe (SHARE)

Do machine learning algorithms perform better than statistical survival analysis when predicting retirement decisions? This exploratory article addresses the question by constructing a pseudo-panel with retirement data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The analysis consists of two methodological steps prompted by the nature of the data. First, a discrete Cox survival model of transitions to retirement with time-dependent covariates is compared to a Cox model without time-dependent covariates and a survival random forest. Second, the best performing model (Cox with time-dependent covariates) is compared to random forests adapted to time-dependent covariates by means of simulations. The results from the analysis do not clearly favor a single method; whereas machine learning algorithms have a stronger predictive power, the variables they use in their predictions do not necessarily display causal relationships with the outcome variable. Therefore, the two methods should be seen as complements rather than substitutes. In addition, simulations shed a new light on the role of some variables—such as education and health—in retirement decisions. This amounts to both substantive and methodological contributions to the literature on the modeling of retirement.

Working beyond SPA and the trajectories of cognitive and mental health of UK pensioners: Do gender, choice, and occupational status matter?

We assessed the association between work status beyond state pension age (SPA) and the long-term trajectories of cognitive and mental health for men and women separately, and the extent to which this relationship is conditioned by their occupational status and whether the choice to retire or continue working is voluntary or involuntary. Data are pensioners (aged between SPA and SPA + 9) from the English Longitudinal Study of Ageing waves 4 (2008/09) through 9 (2018/19). The analytic sample includes 959 men and 1217 women when considering cognitive outcomes and 1131 men and 1434 women when evaluating depression. Findings based on growth curve models reveal that, compared to women who retired at SPA and without any particular reason, their peers who retired due to frailing health reported a more precipitous decline in memory over time (coefficient = −0.10). However, analysis stratified by occupation shows that this association between ill-health retirement and long-term memory decline was concentrated among older women of the highest occupational status. We also found that men who retired or worked past SPA voluntarily reported a better baseline verbal fluency and were less likely to report depression over time (coefficient for work = 0.80; coefficient for retired = 0.87). Women who worked past SPA voluntarily were less likely to report depression at baseline (OR = 0.53). Policies that extend work life should offer older people more personal control over decision surrounding retirement.