Population Research and Policy Review

The relationships between education and employment have long been of interest to social scientists. During the transition from a completely agricultural economy to one that is developing nonfarm opportunities, however, the relationships between education and employment may dramatically change. We examine how two components of education—schooling enrollment and attainment—affect the transition to employment for men and women in the Chitwan Valley of Nepal. Using discrete-time event history models, we find that school enrollment tends to delay employment, while school attainment accelerates employment. We also test how these effects may have changed across successive cohorts. Over time, the effects of enrollment have become stronger, while the effects of attainment appear to have weakened. These shifts in the nature of education may be related to increasing conflict between student and employee roles, as well as changes in the types and availability of employment.

In a first-ever nation-wide census tract evaluation, we assess the accuracy of the Hamilton–Perry population projection method for 65,221 census tracts. We started with 73,607 census tracts but eliminated those for which zeros appeared in age/sex groups. The test uses 1990 and 2000 census tract data by age and gender to construct cohort change ratios, which are then applied to 2000 census tract data to generate 2010 Hamilton–Perry projections that are evaluated in an ex post facto test against the reported 2010 census tract data by age and gender. The projections include: (1) uncontrolled age and gender projections; and (2) age and gender projections controlled to a projection of the population total by census tract. Mean Absolute Percent Error (MAPE) is used to evaluate precision and Mean Algebraic Percent Error (MALPE) is used to evaluate bias. We find that controlling the Hamilton–Perry projections by age for each tract to the linearly projected total population of each tract reduces both MAPE and MALPE within age groups by gender and for total females and total males. As this result suggests, simple linear extrapolation provides more accurate projections of the total population than does the Hamilton–Perry Method. However, even with controlling we find the Hamilton–Perry projections by age to be biased upward. Finally, we use MAPE-R (MAPE- Revised) to evaluate the effect of extreme outliers and find that high MAPEs in the uncontrolled projections are largely driven by extreme errors (outliers) found in less than 1 percent of the 65,221 census tracts used in the study.

Forecasts are needed for everyday decisions and must be in the form of numbers. Yet forecasts invariably turn out to be different than the numbers that actually occur. Yet, most producers of forecasts only present a deterministic view of the future in the form of point predictions. However, the presence of uncertainty is inherent in management or policy decisions and there is often concern that benefits are overstated and risks are understated. Such concerns are difficult to address by providing only point forecasts with no assessment of their uncertainty. Having a better understanding of uncertainty can enhance the usefulness of forecasts and make the work of forecasting agencies an even more valuable product for planners, policy makers, and the public. The purpose of this paper is twofold. First, it presents an overview of the current state-of-the-practice is assessing forecast uncertainty. Second, it offers a guidelines and options for implementing and building uncertainty into small area forecasting processes. There are options for assessing forecasting uncertainty that can and should be implemented by most, if not all, producers of forecasts.

After decades of lower or comparable mortality rates in rural than in urban areas of the U.S., numerous studies have documented a rural mortality penalty that started in the 1990s and has grown since the mid-2000s. The widening of the gap appears to be especially pronounced among non-Hispanic (NH) whites. However, the rural U.S. is not monolithic, and some rural places have experienced much larger mortality rate increases than others over the past 30 years. Drawing on restricted mortality files from the National Vital Statistics System (NVSS), I examine metro versus nonmetro and intra-nonmetro (divisional and economic dependency) all-cause and cause-specific mortality trends among working-age (25–64) NH white males and females, 1990–2018. Results show that the nonmetro mortality penalty is wide and growing and is pervasive across multiple disease and injury categories. Trends for females are particularly concerning. Smaller nonmetro declines in mortality from cancers and cardiovascular disease (throughout the 1990s and 2000s) and larger increases in metabolic and respiratory diseases, suicide, alcohol-related, and mental/behavioral disorders (throughout the 2010s) collectively drove the growth in the nonmetro disadvantage. There are also large divisional disparities (which are growing for females), with particularly poor trends in New England, South Atlantic, ES Central, WS Central, and Appalachia and more favorable trends in the Mid-Atlantic, Mountain, and Pacific. Mining-dependent counties have diverged from the other economic dependency types since the mid-2000s due to multiple causes of death, whereas farming counties have comparatively lower mortality rates. High and rising mortality rates across a variety of causes and rural places, some of which have been occurring since the 1990s and others that emerged more recently, suggest that there is not one underlying explanation. Instead, systemic failures across a variety of institutions and policies have contributed to rural America’s troubling mortality trends generally and within-rural disparities more specifically.

Asian American men and women have been largely neglected in previous studies of romantic relationship formation and status. Using data from the first and fourth waves of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examine romantic and sexual involvement among young adults, most of whom were between the ages of 25 and 32 (N = 11,555). Drawing from explanations that focus on structural and cultural elements as well as racial hierarchies, we examine the factors that promote and impede involvement in romantic/sexual relationships. We use logistic regression to model current involvement of men and women separately and find, with the exception of Filipino men, Asian men are significantly less likely than white men to be currently involved with a romantic partner, even after controlling for a wide array of characteristics. Our results suggest that the racial hierarchy framework best explains lower likelihood of involvement among Asian American men.

This study aims to evaluate the impact of demographic change on long-term, macro-level childcare and adult care transfers, accounting for the associated well-being effects of informal caregiving. We measure the impact of demographic change on non-monetary care exchanged between different groups by estimating matrices of time transfers by age and sex, and weighting the time flows by self-reported indicators of well-being, for activities related to childcare and adult care. The analysis employs cross-sectional data from the American Time Use Survey 2011–2013, and the Panel Study of Income Dynamics, Disability, and Use of Time Module 2013 to produce the estimates of well-being associated with the two forms of care and their future projections. Both men and women experience more positive feelings when caring for children than when caring for adults. As a whole, caregiving is an overwhelmingly more positive experience than it is negative across both genders and care types. Yet women often report more tiredness and stress than men when providing childcare, while also experiencing more pain while performing adult care, as compared to childcare activities. Women of reproductive ages spend double the amount of care time associated with negative feelings, relative to men, most of which is spent on early childcare. We project a progressively widening gender gap in terms of positive feelings related to care in the coming decades. Future reductions in absolute caregiver well-being influenced by demographic changes at the population level may reduce workforce participation, productivity, and adversely impact psycho-physical condition of caregivers, if not offset by targeted policies.