Martin Karlsson, Tor Iversen, and Henning Öien
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Economics and Finance. Please check back later for the full article.
There has been a rise in recent research regarding the economics on the consequences of population ageing for health care expenditure. The focus of this research is on expenditures in the last years of life and the implications for the age profile of health care spending. One open issue in the literature is whether health care expenditure is so concentrated in the last years before death that the age profiles in spending will change when longevity increases. The previous literature also finds that the age profile of health expenditures, after controlling for time to death, is dependent on the type of health care expenditure that is being predicted. Some studies find that the age is more powerful in predicting long-term care compared to health care expenditures. However, this result appears to depend on the empirical model used.
There are conflicting findings that can be reconciled by carefully reviewing and validating the methods that have been used in the literature. In particular, there are advantages of using a two-part model for health care expenditure, in which health care utilization is allowed to have different determinants on the extensive and the intensive margin. This can be seen when this standard modeling approach is compared to alternatives that require weaker assumptions at the cost of possibly inferior fit to the data. Different proxies are evaluated for morbidity affect the estimated end-of-life costs and age profiles in spending. Using a high-quality health insurance dataset from Germany, which includes all relevant determinants of health and long-term care expenditure, the accuracy of popular methods in predictions of future health and long-term care spending are assessed. The basis for this validation exercise is the prediction accuracy within the same dataset. The endogeneity of death is an issue that has not been addressed satisfactorily in the literature, and there is a solution to the problem based on standard approaches to causal inference.
Matteo M. Galizzi and Daniel Wiesen
The state-of-the-art literature at the interface between experimental and behavioral economics and health economics is reviewed by identifying and discussing 10 areas of potential debate about behavioral experiments in health. By doing so, the different streams and areas of applications of the growing field of behavioral experiments in health are reviewed, by discussing which significant questions remain to be discussed, and by highlighting the rationale and the scope for the further development of behavioral experiments in health in the years to come.
Cristina Bellés-Obrero and Judit Vall Castello
The impact of macroeconomic fluctuations on health and mortality rates has been a highly studied topic in the field of economics. Many studies, using fixed-effects models, find that mortality is procyclical in many countries, such as the United States, Germany, Spain, France, Pacific-Asian nations, Mexico, and Canada. On the other hand, a small number of studies find that mortality decreases during economic expansion. Differences in the social insurance systems and labor market institutions across countries may explain some of the disparities found in the literature. Studies examining the effects of more recent recessions are less conclusive, finding mortality to be less procyclical, or even countercyclical. This new finding could be explained by changes over time in the mechanisms behind the association between business cycle conditions and mortality.
A related strand of the literature has focused on understanding the effect of economic fluctuations on infant health at birth and/or child mortality. While infant mortality is found to be procyclical in countries like the United States and Spain, the opposite is found in developing countries.
Even though the association between business cycle conditions and mortality has been extensively documented, a much stronger effort is needed to understand the mechanisms behind the relationship between business cycle conditions and health. Many studies have examined the association between macroeconomic fluctuations and smoking, drinking, weight disorders, eating habits, and physical activity, although results are rather mixed. The only well-established finding is that mental health deteriorates during economic slowdowns.
An important challenge is the fact that the comparison of the main results across studies proves to be complicated due to the variety of empirical methods and time spans used. Furthermore, estimates have been found to be sensitive to the use of different levels of geographic aggregation, model specifications, and proxies of macroeconomic fluctuations.
Diane McIntyre, Amarech G. Obse, Edwine W. Barasa, and John E. Ataguba
Within the context of the Sustainable Development Goals, it is important to critically review research on healthcare financing in sub-Saharan Africa (SSA) from the perspective of the universal health coverage (UHC) goals of financial protection and access to quality health services for all. There is a concerning reliance on direct out-of-pocket payments in many SSA countries, accounting for an average of 36% of current health expenditure compared to only 22% in the rest of the world. Contributions to health insurance schemes, whether voluntary or mandatory, contribute a small share of current health expenditure. While domestic mandatory prepayment mechanisms (tax and mandatory insurance) is the next largest category of healthcare financing in SSA (35%), a relatively large share of funding in SSA (14% compared to <1% in the rest of the world) is attributable to, sometimes unstable, external funding sources. There is a growing recognition of the need to reduce out-of-pocket payments and increase domestic mandatory prepayment financing to move towards UHC. Many SSA countries have declared a preference for achieving this through contributory health insurance schemes, particularly for formal sector workers, with service entitlements tied to contributions. Policy debates about whether a contributory approach is the most efficient, equitable and sustainable means of financing progress to UHC are emotive and infused with “conventional wisdom.” A range of research questions must be addressed to provide a more comprehensive empirical evidence base for these debates and to support progress to UHC.
Michael Drummond, Rosanna Tarricone, and Aleksandra Torbica
There are a number of challenges in the economic evaluation of medical devices (MDs). They are typically less regulated than pharmaceuticals, and the clinical evidence requirements for market authorization are generally lower. There are also specific characteristics of MDs, such as the device–user interaction (learning curve), the incremental nature of innovation, the dynamic nature of pricing, and the broader organizational impact. Therefore, a number of initiatives need to be taken in order to facilitate the economic evaluation of MDs. First, the regulatory processes for MDs need to be strengthened and more closely aligned to the needs of economic evaluation. Second, the methods of economic evaluation need to be enhanced by improving the analysis of the available clinical data, establishing high-quality clinical registries, and better recognizing MDs’ specific characteristics. Third, the market entry and diffusion of MDs need to be better managed by understanding the key influences on MD diffusion and linking diffusion with cost-effectiveness evidence through the use of performance-based risk-sharing arrangements.
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.
Obesity is widely recognized as a chronic disease characterized by an elevated risk of adverse health conditions in association with excess body fat accumulation. Obesity prevalence reached epidemic proportions among adults in the developed world during the second half of the 20th century, and it has since become a major public health concern around the world, particularly among children and adolescents. The economics of childhood and adolescent obesity is a multi-faceted field of study that considers the numerous determinants, consequences, and interventions related to obesity in those populations.
The central economic framework for studying obesity is a life-cycle decision-making model of health investment. Health-promoting investments, such as nutritional food, health care, and physical activity, interact with genetic structure and risky health behaviors, such as unhealthy food consumption, to generate an accumulation or decumulation of excess body fat over time. Childhood and adolescence are the primary phases of physical and cognitive growth, so researchers study how obesity contributes to, and is affected by, the growth processes. The subdiscipline of behavioral economics offers an important complementary perspective on health investment decision processes, particularly for children and adolescents, because health investments and participation in risky health behaviors are not always undertaken rationally or consistently over time.
In addition to examining the proximate causes of obesity over the life cycle, economists study obesity’s economic context and resulting economic burden. For example, economists study how educational attainment, income, and labor market features, such as wage and work hours, affect childhood and adolescent obesity in a household. Once obesity has developed, its economic burden is typically measured in terms of excess health-care costs associated with increased health risks due to higher obesity prevalence, such as earlier onset of, and more severe, diabetes. Obesity among children and adolescents can lead to even higher health-care costs because of its early influence on the lifetime trajectory of health and its potential disruption of healthy development.
The formulation of effective policy responses to the obesity epidemic is informed by economic research. Economists evaluate whether steps to address childhood and adolescent obesity represent investments in health and well-being that yield private and social benefits, and they study whether existing market structures fail to appropriately motivate such investments. Potential policy interventions include taxation of, or restricting access to, obesogenic foods and other products, subsidization of educational programs about healthy foods and physical activity inside and outside of schools, ensuring health insurance coverage for obesity-related preventive and curative health-care services, and investment in the development of new treatments and medical technologies.
Fabrizio Mazzonna and Franco Peracchi
Population aging, the combined effect of declining fertility and rising life expectancy, is one of the fundamental trends observed in developed counties and, increasingly, in developing countries as well. A key aspect of the aging process is the decline of cognitive ability. Cognitive aging is an important and complex phenomenon, and its risk factors and economic consequences are still not well understood. For instance, the relationship between cognitive aging and productivity matters for long-term economic growth. Cognitive functioning is also crucial for decision-making because it influences individuals’ ability to process information and to make the right choices, and older individuals are increasingly required to make complex financial, health, and long-term-care decisions that might affect their health, resources, and welfare. This article presents evidence from economics and other fields that have investigated this phenomenon from different perspectives.
A common empirical finding is the hump-shaped profile of cognitive performance over the life cycle. Another is the large variability of observed age profiles, not only at the individual level but also across sociodemographic groups and countries. The age profiles of cognitive performance also vary depending on the cognitive task considered, reflecting the different combinations of cognitive skills that they require. The literature usually distinguishes between two main types of cognitive skills: fluid intelligence and crystallized intelligence. The first consists of the basic mechanisms of processing new information, while the second reflects acquired knowledge. Unlike fluid intelligence, which declines rapidly as people get older, crystallized intelligence tends to be maintained at older ages. Differences in the age profiles of cognitive performance across tasks partly reflect differences in the importance of these two types of intelligence. For instance, tasks where learning, problem-solving, and processing speed are essential tend to be associated with a faster decline, while tasks where experience matters more tend to be associated with a slower decline. Various life events and behaviors over the life cycle also contribute to the large heterogeneity in the observed age profiles of cognitive performance. This source of variation includes not only early-life events and investments (e.g., formal education), but also midlife and later-life events (e.g., health shocks) and individual choices (e.g., health behaviors or retirement).
From an economic viewpoint, cognitive abilities may be regarded as one dimension of human capital, along with education, health, and noncognitive abilities. Economists have mainly focused their attention on human capital accumulation, and much less so on human capital deterioration. One explanation is that early-life investments appears to be more profitable than investments later in life. However, recent evidence from neuropsychology suggests that the human brain is malleable and open to enhancement even later in adulthood. Therefore, more economic research is needed to study how human capital depreciates over the life cycle and whether cognitive decline can be controlled.
Hans Olav Melberg
End-of-life spending is commonly defined as all health costs in the 12 months before death. Typically, the costs represent about 10% of all health expenses in many countries, and there is a large debate about the effectiveness of the spending and whether it should be increased or decreased. Assuming that health spending is effective in improving health, and using a wide definition of benefits from end-of-life spending, several economists have argued for increased spending in the last years of life. Others remain skeptical about the effectiveness of such spending based on both experimental evidence and the observation that geographic within-country variations in spending are not correlated with variations in mortality.
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.