This paper presents a theoretical and empirical analysis of the role of life expectancy for optimal schooling and lifetime labor supply. The results of a simple prototype Ben-Porath model with age-specific survival rates show that an increase in lifetime labor supply is not a necessary, nor a sufficient, condition for greater life expectancy to increase optimal schooling. The observed increase in survival rates during working ages that follows from the “rectangularization” of the survival function is crucial for schooling and labor supply. The empirical results suggest that the relative benefits of schooling have been increasing across cohorts of US men born 1840-1930. A simple quantitative analysis shows that a realistic shift in the survival function can lead to an increase in schooling and a reduction in lifetime labor hours.
Life Expectancy, Schooling, and Lifetime Labor Supply: Theory and Evidence Revisited by Matteo Cervellati, Uwe Sunde :: SSRNApril 1, 2013
Education and Health: The Role of Cognitive Ability by Govert Bijwaard, Hans Van Kippersluis, Justus Veenman :: SSRNApril 1, 2013
We aim to disentangle the relative contributions of (i) cognitive ability, and (ii) education on health and mortality using a structural equation model suggested by Conti et al. (2010). We extend their model by allowing for a duration dependent variable, and an ordinal educational variable. Data come from a Dutch cohort born around 1940, including detailed measures of cognitive ability and family background at age 12. The data are subsequently linked to the mortality register 1995-2011, such that we observe mortality between ages 55 and 75. The results suggest that the treatment effect of education (i.e. the effect of entering secondary school as opposed to leaving school after primary education) is positive and amounts to a 4 years gain in life expectancy, on average. Decomposition results suggest that the raw survival differences between educational groups are about equally split between a ‘treatment effect’ of education, and a ‘selection effect’ on basis of cognitive ability and family background.
the gap between the health haves and the have-nots has narrowed dramatically in recent years.
The haves are those who enjoy great health into their 90s. The have-nots are those who suffer from serious health problems and do not live to see adulthood. As we pointed out in a recent study, among those Americans who were born in 1975, the unluckiest 1 percent died in infancy, while the luckiest 1 percent can expect to live to age 105 or longer. Now let’s fast forward to those born in 2012. The bottom percentile of this cohort can expect to survive until age 18. At the other end of the spectrum, the luckiest 1 percent can expect to live to age 108. That’s a much bigger gain in life expectancy among the have-nots than among the haves. Of course, life expectancy is but one measure of health and well-being, but understanding these trends offers a more complete picture than considering income alone.
Health Insurance Coverage and Use of Family Planning Services among Current and Former Foster Youth: Implications of the Health Care Reform LawMarch 21, 2013
This research uses data from a longitudinal study to examine how two provisions in the Patient Protection and Affordable Care Act could affect health insurance coverage among young women who have aged out of foster care. It also explores how allowing young people to remain in foster care until age twenty-one affects their health insurance coverage, use of family planning services, and information about birth control. We find that young women are more likely to have health insurance if they remain in foster care until their twenty-first birthday and that having health insurance is associated with an increase in the likelihood of receiving family planning services. Our results also suggest that many young women who would otherwise lack health insurance after aging out of foster care will be eligible for Medicaid under the health care reform law. Because having health insurance is associated with use of family planning services, this increase in Medicaid eligibility may result in fewer unintended pregnancies among this high-risk population.
What Happens to the Women Who Fall through the Cracks of Health Care Reform? Lessons from MassachusettsMarch 21, 2013
We investigated the impact of Massachusetts health care reform on low-income women’s experiences accessing insurance and health services, specifically reproductive health services such as contraception. Our findings suggest that concentrated efforts are needed to make sure that health services are available and accessible to populations who fall through the cracks of health care reform, including immigrants, minors and young adults, and women living outside urban areas. In addition, systems changes are needed to ensure that women going through common life transitions, such as pregnancy, marriage, moving, or graduating from school, have continuous access to insurance, and therefore health services, as their lives change. These groups face barriers enrolling in and maintaining their insurance coverage as well as obtaining timely health care benefits they are eligible for through their insurance benefits or public health programs. Without intervention, many in these groups may delay or avoid seeking health care altogether, which may increase health care disparities in the long term. Family planning providers in Massachusetts have played a critical role in mitigating barriers to insurance and health care. However, recent threats to defund family planning providers call into question the ability of these providers to continue providing much-needed services.
A separate study by economists Joseph Sabia of San Diego State University and Robert Nielsen of the University of Georgia explored the impact of the minimum wage on the welfare of the poor. They concluded that the minimum wage is spread out so far up into the income distribution that there is “no statistically significant evidence that a higher minimum wage has helped reduce financial, housing, health, or food insecurity.” The authors couldn’t find a beneficial effect of the wage on the welfare even of those most likely to benefit from it.
Alcoholism and Unemployment – A Panel Data Analysis for the Industrial World by Miltiades Georgiou :: SSRNMarch 14, 2013
In the present paper an empirical analysis will point out that unemployment is one of the various causes of alcoholism. The sample covers all industrial World. Data are drawn from IMF and OECD. The elaboration of these panel data is made feasible by means of the Eviews software package.
Impacts of Parental Health Shocks on Children’s Non-Cognitive Skills by Franz Westermaier, Brant Morefield, Andrea Mühlenweg :: SSRNMarch 14, 2013
We examine how parental health shocks affect children’s non-cognitive skills. Based on a German mother-and-child data base, we draw on significant changes in self-reported parental health as an exogenous source of health variation to identify effects on outcomes for children at ages of three and six years. At the age of six, we observe that maternal health shocks in the previous three years have significant negative effects on children’s behavioral outcomes. The most serious of these maternal health shocks decrease the observed non-cognitive skills up to half a standard deviation. Paternal health does not robustly affect non-cognitive outcomes.
Obesity and Income Distribution: A Panel Data Analysis for Western World by Miltiades Georgiou :: SSRNMarch 14, 2013
In the present paper author attempts to support through an econometric panel data analysis the view of (Darmon and Drewnowski, 2008) that higher income classes have healthier diet, therefore lower obesity levels. The sample covers Western Europe and the United States. Data are taken from Eurostat and OECD. The elaboration of these panel data is made feasible by means of the Eviews software package.
Mortality Differentials by Lifetime Earnings Decile: Implications for Evaluations of Proposed Social Security Law Changes by Hilary Waldron :: SSRNMarch 12, 2013
To evaluate the distributional effects of some proposed Social Security law changes, such as an increase in Social Security’s early entitlement age, retirement policy analysts typically tabulate the number of workers who fall below a predetermined threshold of hardship. Analysts using this technique often implicitly assume that the insured population falls neatly into a low-earnings poor health group and a remaining good health group. If the hardship threshold assumption is correct, there should be no difference in mortality risk between lifetime earnings deciles above a hardship threshold. This study finds that the hardship threshold model is overwhelmingly rejected in US Social Security data, a result consistent with similar studies conducted in Canada, Germany, and England. The bottom 80-95 percent of the male lifetime earnings distribution exhibits an inverse correlation with regard to mortality risk (the higher the earnings, the lower the mortality risk) at ages 63-71.