The Impact of Health and Education on Labor Force Participation in Aging Societies: Projections for the United States and Germany from Dynamic Microsimulations.

We project the labor force in the United States to 2060 and contrast the outcomes with comparative projections for Germany. In both countries, the population will age, but the demographic dynamics are fundamentally different. According to our dynamic microsimulations, the labor force in the U.S. will increase by 17 percent between 2020 and 2060 (about 29 million workers) despite population aging. In contrast, the labor force in Germany will decline by 11 percent (about 4.5 million workers). Our baseline projections indicate that an expansion of education will increase the labor force by about 3 million persons in the United States and about half a million persons in Germany by 2060. In several what-if scenarios, we examine the effects of further expanding education and of removing health barriers on labor force participation. Higher educational attainment among those with currently low education has the largest impact on labor force participation, relative to the additional years of schooling. However, health improvements and the labor market integration of people with health limitations suggest a larger increase in labor force participation rates. Using Sweden as a benchmark, we show that reducing the health participation gap would increase the U.S. labor force by as much as 13 million people in 2060 (+6.8 percent compared to our baseline).

The effect of sample attrition in the EU Statistics on Income and Living Conditions on the estimates of Eurostat's Healthy Life Years.

Eurostat's official Healthy Life Years (HLY) estimates are based on European Union Statistics on Income and Living Conditions (EU-SILC) cross-sectional data. As EU-SILC has a rotational sample design, the largest part of the samples are longitudinal, health-related attrition constituting a potential source of bias of these estimates. Bland-Altman plots assessing the agreement between pairs of HLY based on total and new rotational, representative samples demonstrated no significant, systematic attrition-related bias. However, the wide limits of agreement indicate considerable uncertainty, larger than accounted for in the confidence intervals of HLY estimates.

Cross-sectional estimates of population health from the survey of health and retirement in Europe (SHARE) are biased due to health-related sample attrition.

Cross-sectional data from the Survey of Health, Ageing and Retirement in Europe (SHARE) are a common source of information in comparative studies of population health in Europe. In the largest part, these data are based on longitudinal samples, which are subject to health-specific attrition. This implies that estimates of population health based on cross-sectional SHARE datasets are biased as the data are selected on the outcome variable of interest. We examine whether cross-sectional datasets are selected based on health status. We compare estimates of the prevalence of full health, healthy life years at age 50 (HLY), and rankings of 18 European countries by HLY based on the observed, cross-sectional SHARE wave 7 datasets and full samples. The full samples consist of SHARE observed and attrited respondents, whose health trajectories are imputed by microsimulation. Health status is operationalized across the global index of limitations in activities of daily living (GALI). HLY stands for life expectancy free of activity limitations. Cross-sectional datasets are selected based on health status, as health limitations increase the odds of attrition from the panel in older age groups and reduce them in younger ones. In older age groups, the prevalence of full health is higher in the observed cross-sectional data than in the full sample in most countries. In most countries, HLY is overestimated based on the cross-sectional data, and in some countries, the opposite effect is observed. While, due to the small sample sizes of national surveys, the confidence intervals are large, the direction of the effect is persistent across countries. We also observe shifts in the ranking of countries according to HLYs of the observed data versus the HLYs of the full sample. We conclude that estimates on population health based on cross-sectional datasets from longitudinal, attrited SHARE samples are over-optimistic.

Union instability as an engine of fertility? A microsimulation model for France.

Opportunities for conceiving and bearing children are fewer when unions are not formed or are dissolved during the childbearing years. At the same time, union instability produces a pool of persons who may enter new partnerships and have additional children in stepfamilies. The balance between these two opposing forces and their implications for fertility may depend on the timing of union formation and parenthood. In this article, we estimate models of childbearing, union formation, and union dissolution for female respondents to the 1999 French Etude de l'Histoire Familiale. Model parameters are applied in microsimulations of completed family size. We find that a population of women whose first unions dissolve during the childbearing years will end up with smaller families, on average, than a population in which all unions remain intact. Because new partnerships encourage higher parity progressions, repartnering minimizes the fertility gap between populations with and those without union dissolution. Differences between the two populations are much smaller when family formation is postponed-that is, when union formation and dissolution or first birth occurs after age 30, or when couples delay childbearing after union formation.