There are three main topics in research on the effects of work on health. The first topic is workplace accidents where the main issues are reporting behavior and workplace safety policies. A worker seems to be less inclined to report a workplace accident for fear of job loss when unemployment is high or when the worker has a temporary contract that may not be renewed. Workplace safety legislation has intended to reduce the incidence and severity of workplace accidents but empirical evidence on this result is unclear. The second topic is employment and health where the focus is on how job characteristics and job loss affect health, in particular mental health. Physically demanding jobs have negative health effects. The effects of working hours vary and the effects of job loss on physical and mental health are not uniform. Job loss seems to increase mortality. The third topic concerns retirement and health. Retirement seems to have a negative effect on cognitive skills and short-term positive effects on overall health. Other than that, the effects are very inconsistent, that is, even with as clear a measure as mortality, it is not clear whether life expectancy goes up, goes down, or remains constant due to retirement.
Jan C. van Ours
Susan Averett and Jennifer Kohn
An individual’s health is produced in large part by family investments that start before birth and continue to the end of life. The health of an individual is intertwined with practically every economic decision including education, marriage, fertility, labor market, and investments. These outcomes in turn affect income and wealth and hence have implications for intergenerational transfer of economic advantage or disadvantage. A rich body of theoretical and empirical work considers the role of the family in health production over the life cycle and the role of health in household economic decisions. This literature starts by considering family inputs regarding health at birth, then moves through adolescence and midlife, where relationship decisions affect health. After midlife, health, particularly the health of family members, becomes an input into retirement and investment decisions. The literature on family and health showcases economists’ skills in modeling complex family dynamics, deriving theoretical predictions, and using clever econometric strategies to identify causal effects.
Courtney Van Houtven, Fiona Carmichael, Josephine Jacobs, and Peter C. Coyte
Across the globe, the most common means of supporting older disabled adults in their homes is through “informal care.” An informal carer is a family member or friend, including children or adults, who help another person because of their illness, frailty, or disability. There is a rich economics literature on the direct benefits of caregiving, including allowing the care recipient to remain at home for longer than if there was no informal care provided. There is also a growing literature outlining the associated costs of care provision. Although informal care helps individuals with disabilities to remain at home and is rewarding to many carers, there are often negative effects such as depression and lost labor market earnings that may offset some of these rewards. Economists have taken several approaches to quantify the net societal benefit of informal care that consider the degree of choice in caregiving decisions and all direct and indirect benefits and costs of informal care.
Gregory Colman, Dhaval Dave, and Otto Lenhart
Health insurance depends on labor market activity more in the U.S. than in any other high-income country. A majority of the population are insured through an employer (known as employer-sponsored insurance or ESI), benefiting from the risk pooling and economies of scale available to group insurance plans. Some workers may therefore be reluctant to leave a job for fear of losing such low-cost insurance, a tendency known as “job lock,” or may switch jobs or work more hours merely to obtain it, known as “job push.” Others obtain insurance through government programs for which eligibility depends on income. They too may adapt their work effort to remain eligible for insurance. Those without access to ESI or who are too young or earn too much to qualify for public coverage (Medicare and Medicaid) can buy insurance only in the individual or nongroup market, where prices are high and variable. Most studies using data from before the passage of the Patient Protection and Affordable Care Act (ACA) in 2010 support the prediction that ESI reduced job mobility, labor-force participation, retirement, and self-employment prior to the ACA, but find little effect on the labor supply of public insurance. The ACA profoundly changed the health insurance market in the U.S., removing restrictions on obtaining insurance from new employers or on the individual market and expanding Medicaid eligibility to previously ineligible adults. Research on the ACA, however, has not found substantial labor supply effects. These results may reflect that the reforms to the individual market mainly affected those who were previously uninsured rather than workers with ESI, that the theoretical labor market effects of expansions in public coverage are ambiguous, and that the effect would be found only among the relatively small number on the fringes of eligibility.
David E. Bloom, Michael Kuhn, and Klaus Prettner
The strong observable correlation between health and economic growth is crucial for economic development and sustained well-being, but the underlying causality and mechanisms are difficult to conceptualize. Three issues are of central concern. First, assessing and disentangling causality between health and economic growth are empirically challenging. Second, the relation between health and economic growth changes over the process of economic development. In less developed countries, poor health often reduces labor force participation, particularly among women, and deters investments in education such that fertility stays high and the economy remains trapped in a stagnation equilibrium. By contrast, in more developed countries, health investments primarily lead to rising longevity, which may not significantly affect labor force participation and workforce productivity. Third, different dimensions of health (mortality vs. morbidity, children’s and women’s health, and health at older ages) relate to different economic effects. By changing the duration and riskiness of the life course, mortality affects individual investment choices, whereas morbidity relates more directly to work productivity and education. Children’s health affects their education and has long-lasting implications for labor force participation and productivity later in life. Women’s health is associated with substantial intergenerational spillover effects and influences women’s empowerment and fertility decisions. Finally, health at older ages has implications for retirement and care.
Jason M. Fletcher
Two interrelated advances in genetics have occurred which have ushered in the growing field of genoeconomics. The first is a rapid expansion of so-called big data featuring genetic information collected from large population–based samples. The second is enhancements to computational and predictive power to aggregate small genetic effects across the genome into single summary measures called polygenic scores (PGSs). Together, these advances will be incorporated broadly with economic research, with strong possibilities for new insights and methodological techniques.
Martin Karlsson, Tor Iversen, and Henning Øien
An open issue in the economics literature is whether healthcare expenditure (HCE) is so concentrated in the last years before death that the age profiles in spending will change when longevity increases. The seminal article “aging of Population and HealthCare Expenditure: A Red Herring?” by Zweifel and colleagues argued that that age is a distraction in explaining growth in HCE. The argument was based on the observation that age did not predict HCE after controlling for time to death (TTD). The authors were soon criticized for the use of a Heckman selection model in this context. Most of the recent literature makes use of variants of a two-part model and seems to give some role to age as well in the explanation. Age seems to matter more for long-term care expenditures (LTCE) than for acute hospital care. When disability is accounted for, the effects of age and TTD diminish. Not many articles validate their approach by comparing properties of different estimation models. In order to evaluate popular models used in the literature and to gain an understanding of the divergent results of previous studies, an empirical analysis based on a claims data set from Germany is conducted. This analysis generates a number of useful insights. There is a significant age gradient in HCE, most for LTCE, and costs of dying are substantial. These “costs of dying” have, however, a limited impact on the age gradient in HCE. These findings are interpreted as evidence against the red herring hypothesis as initially stated. The results indicate that the choice of estimation method makes little difference and if they differ, ordinary least squares regression tends to perform better than the alternatives. When validating the methods out of sample and out of period, there is no evidence that including TTD leads to better predictions of aggregate future HCE. It appears that the literature might benefit from focusing on the predictive power of the estimators instead of their actual fit to the data within the sample.
Thomas E. Getzen
During the 18th and 19th centuries, medical spending in the United States rose slowly, on average about .25% faster than gross domestic product (GDP), and varied widely between rural and urban regions. Accumulating scientific advances caused spending to accelerate by 1910. From 1930 to 1955, rapid per-capita income growth accommodated major medical expansion while keeping the health share of GDP almost constant. During the 1950s and 1960s, prosperity and investment in research, the workforce, and hospitals caused a rapid surge in spending and consolidated a truly national health system. Excess growth rates (above GDP growth) were above +5% per year from 1966 to 1970, which would have doubled the health-sector share in fifteen years had it not moderated, falling under +3% in the 1980s, +2% in 1990s, and +1.5% since 2005. The question of when national health expenditure growth can be brought into line with GDP and made sustainable for the long run is still open. A review of historical data over three centuries forces confrontation with issues regarding what to include and how long events continue to effect national health accounting and policy. Empirical analysis at a national scale over multiple decades fails to support a position that many of the commonly discussed variables (obesity, aging, mortality rates, coinsurance) do cause significant shifts in expenditure trends. What does become clear is that there are long and variable lags before macroeconomic and technological events affect spending: three to six years for business cycles and multiple decades for major recessions, scientific discoveries, and organizational change. Health-financing mechanisms, such as employer-based health insurance, Medicare, and the Affordable Care Act (Obamacare) are seen to be both cause and effect, taking years to develop and affecting spending for decades to come.