Family background is a strong determinant of an individual’s educational achievement and labor market success. Using an economics framework, intergenerational persistence in socioeconomic status can be explained by a variety of factors, including parental investment behavior, credit constraints, and the degree of inequality in society. Genetic transmission from parents to children may also play a role. In addition, the skill formation process is governed by dynamics between different stages of a child’s life, such as complementarities between early and late investments or between informal and formal education.
Education policy holds the promise of breaking the strong ties between family background and socioeconomic position by providing publicly accessible education for children of all backgrounds. However, the education system may also perpetuate social inequalities if well-off families are able to protect their children from downward mobility by, for example, moving to neighborhoods with high-quality schools and by providing networks that offer opportunities to succeed.
However, a growing number of studies show that educational interventions can have long-lasting effects on students’ outcomes, in particular for disadvantaged students, and that they can be cost-effective. For example, reducing class size, increasing general education spending, tutoring, and improving teacher quality are policy levers that are shown to be successful in this regard. Shifting from selective to comprehensive school systems is also a policy that enhances equality of opportunity. While the evidence on credit constraints and their role for access to higher education is evolving, but still mostly U.S. focused and largely inconclusive, it is a key domain for shaping social mobility given the life-changing impacts that a university degree can have.
Article
Dominic Hodgkin and Hilary S. Connery
Drug and alcohol use disorders, also called substance use disorders (SUD), are among the major health problems facing many countries, contributing a substantial burden in terms of mortality, morbidity, and economic impact. A considerable body of research is dedicated to reducing the social and individual burden of SUD.
One major focus of research has been the effectiveness of treatment for SUD, with studies examining both medication and behavioral treatments using randomized, controlled clinical trials. For opioid use disorder, there is a strong evidence base for medication treatment, particularly using agonist therapies (i.e., methadone and buprenorphine), but mixed evidence regarding the use of psychosocial interventions. For alcohol use disorder, there is evidence of modest effectiveness for two medications (acamprosate and naltrexone) and for various psychosocial treatments, especially for less severe alcohol use disorder syndromes. An important area for future research is how to make treatment more appealing to clients, given that client reluctance is an important contributor to the low utilization of effective treatments.
A second major focus of research has been the availability of medication treatments, building on existing theories of how innovations diffuse, and on the field of dissemination and implementation research. In the United States, this research identifies serious gaps in both the availability of SUD treatment programs and the availability of effective treatment within those programs. Key barriers include lack of on-site medical staff at many SUD treatment programs; restrictive policies of private insurers, states, and federal authorities; and widespread skepticism toward medication treatment among counseling staff and some administrators. Emerging research is promising for providing medication treatment in settings other than SUD treatment programs, such as community mental health centers, prisons, emergency departments, and homeless shelters.
There is still considerable room to make SUD treatment approaches more effective, more available, and—most importantly—more acceptable to clients.
Article
Titus Galama, Adriana Lleras-Muney, and Hans van Kippersluis
Education is strongly associated with better health and longer lives. However, the extent to which education causes health and longevity is widely debated. We develop a human capital framework to structure the interpretation of the empirical evidence and review evidence on the causal effects of education on mortality and its two most common preventable causes: smoking and obesity. We focus attention on evidence from randomized controlled trials, twin studies, and quasi-experiments. There is no convincing evidence of an effect of education on obesity, and the effects on smoking are only apparent when schooling reforms affect individuals’ track or their peer group, but not when they simply increase the duration of schooling. An effect of education on mortality exists in some contexts but not in others and seems to depend on (i) gender, (ii) the labor market returns to education, (iii) the quality of education, and (iv) whether education affects the quality of individuals’ peers.
Article
Ayman Chit and Paul Grootendorst
Drug companies are profit-maximizing entities, and profit is, by definition, revenue less cost. Here we review the impact of government policies that affect sales revenues earned on newly developed drugs and the impact of policies that affect the cost of drug development. The former policies include intellectual property rights, drug price controls, and the extension of public drug coverage to previously underinsured groups. The latter policies include regulations governing drug safety and efficacy, R&D tax credits, publicly funded basic research, and public funding for open drug discovery consortia.
The latter policy, public funding of research consortia that seek to better understand the cellular pathways through which new drugs can ameliorate disease, appears very promising. In particular, a better understanding of human pathophysiology may be able to address the high failure rate of drugs undergoing clinical testing. Policies that expand market size by extending drug insurance to previously underinsured groups also appear to be effective at increasing drug R&D. Expansions of pharmaceutical intellectual property rights seem to be less effective, given the countervailing monopsony power of large public drug plans.
Article
Giorgio Brunello
Does a higher share of immigrants affect the school performance of both immigrants and natives? Do desegregation policies improve efficiency? The existing evidence suggests that a higher share of immigrants has a negative (and often sizable) effect on the school performance of immigrants and a negative but probably small effect on the performance of natives. When average school performance is considered, this asymmetry generates concave peer effects, a key condition for the efficiency of desegregating policies. The broad message from the empirical literature is that these policies are not only equitable, in that they provide better opportunities to individuals with relatively low parental background, but also efficient.
Article
Jenifer Ruiz-Valenzuela
Severe economic downturns are typically characterized by a high incidence of job losses. The available evidence suggests that job losers suffer short-run earning losses that persist in the long run, are more likely to remain unemployed, suffer negative health impacts, and experience an increased likelihood of divorce. Job losses have therefore the potential to generate spillover effects for other members of the household, including children. This comes about because most of the negative consequences of job loss have a direct effect on variables that enter both the production function of cognitive achievement and the health production function.
Workers who lose their jobs are likely different from those who remain employed in ways that are unobserved to the researcher and that might, in turn, affect child outcomes. Omitted variable bias poses a challenge to obtaining causal estimates of parental job loss. The way the literature has tried to approximate the ideal experiment has mainly depended on whether the child outcome under analysis could be observed both before and after the shock (i.e., both before and after parental job loss), normally relying on job losses coming from plant closures or downsizes and/or individual fixed effects. A survey of the literature shows that father’s job losses seem to have a detrimental impact on outcomes measuring children’s health and school performance. The impact of mother’s job losses on these same outcomes is mixed (including negative, null, and positive impacts). The impact on more long-term outcomes is less clear, with very mixed findings when it comes to the effect of parental job loss on college enrollment, and small impacts on earnings. In many studies, though, average effects mask important differences across subgroups: the negative impact of parental job loss seems to be mostly concentrated on disadvantaged households.
Article
Hope Corman, Dhaval Dave, and Nancy E. Reichman
Prenatal care, one of the most frequently used forms of healthcare in the United States, involves a series of encounters during the gestational period, educates women about pregnancy, monitors existing medical conditions, tests for gestational health conditions, and refers expectant mothers to services such as support groups and social services. However, an increasingly methodologically rigorous literature suggests that the effects of prenatal care timing and quantity on birth outcomes, particularly low birthweight, are modest at the population level. A review and synthesis of the literature suggests that the questions typically being asked may be too narrow and that more attention should be paid to the characterization of infant health, characterization of the content and quality of prenatal care, potential heterogeneous effects, potential indirect effects on health behaviors that may benefit offspring, potential long-term effects, potential spillover effects (i.e., on mothers and their subsequent children), effects of preconceptional and lifetime care, and intergenerational effects.
Article
Florence Jusot and Sandy Tubeuf
Recent developments in the analysis of inequality in health and healthcare have turned their interest into an explicit normative understanding of the sources of inequalities that calls upon the concept of equality of opportunity. According to this concept, some sources of inequality are more objectionable than others and could represent priorities for policies aiming to reduce inequality in healthcare use, access, or health status.
Equality of opportunity draws a distinction between “legitimate” and “illegitimate” sources of inequality. While legitimate sources of differences can be attributed to the consequences of individual effort (i.e. determinants within the individual’s control), illegitimate sources of differences are related to circumstances (i.e. determinants beyond the individual’s responsibility).
The study of inequality of opportunity is rooted in social justice research, and the last decade has seen a rapid growth in empirical work using this literature at the core of its approach in both developed and developing countries. Empirical research on inequality of opportunity in health and healthcare is mainly driven by data availability. Most studies in adult populations are based on data from European countries, especially from the UK, while studies analyzing inequalities of opportunity among children are usually based on data from low- or middle-income countries and focus on children under five years old.
Regarding the choice of circumstances, most studies have considered social background to be an illegitimate source of inequality in health and healthcare. Geographical dimensions have also been taken into account, but to a lesser extent, and more frequently in studies focusing on children or those based on data from countries outside Europe. Regarding effort variables or legitimate sources of health inequality, there is wide use of smoking-related variables.
Regardless of the population, health outcome, and circumstances considered, scholars have provided evidence of illegitimate inequality in health and healthcare. Studies on inequality of opportunity in healthcare are mainly found in children population; this emphasizes the need to tackle inequality as early as possible.
Article
Martin Knapp
Mental illnesses are highly prevalent and can have considerable, enduring consequences for individuals, families, communities, and economies. Despite these high prevalence rates, mental illnesses have not received as much public policy commitment or funding as might be expected. One result is that mental illness often goes unrecognized and untreated. The resultant costs are felt not only in healthcare systems, but across many other sectors, including housing, social care, criminal justice, welfare benefits, and employment.
This article sets out the basic principles of economic evaluation, with illustrations in this mental health context. It also discusses the main practical challenges when conducting and interpreting evidence from such evaluations.
Decisions about whether to spend resources on a treatment or prevention strategy are based on whether it is likely to be effective in avoiding, reducing, or curing symptoms, improving quality of life, or achieving other individual-level outcomes. The economic evaluation question is whether the outcomes achieved are sufficient to justify the cost that is incurred in delivering the intervention.
An economic evaluation has five elements: clarification of the question to be addressed; specification of the intervention to be evaluated and with what alternative it is being compared; the outcomes to be measured; the costs to be measured (including the cost of implementing the intervention and any savings that might accrue); and finally, how outcome and cost findings are to be blended to make a recommendation to the decision-maker. Sometimes, if an evaluation finds that one intervention has better outcomes but higher costs, then the evaluation should also how one (the outcomes) might be trade-off for the other (the costs).
The article illustrates how economic evaluations have been undertaken and employed to address a range of questions, from the very strategic issue to the more specific clinical question. The purpose of the study can, to some extent, determine the type of evaluation that is needed.
Examples of evaluations are given in a number of areas: perinatal maternal mental illness; parenting programs for conduct disorder; anti-bullying programs in schools; early intervention services for psychosis; individual placement and support; collaborative care for physical health problems; and suicide prevention. The challenges of economic evaluation are discussed, specifically in the mental health field.
Article
Sherry Glied and Richard Frank
Mental health economics addresses problems that are common to all of health economics, but that occur with greater severity in this context. Several characteristics of mental health conditions—age of onset, chronicity, observability, and external effects—make them particularly economically challenging, and a range of policies have evolved to address these problems. The need for insurance—and for social insurance—to address mental health problems has grown. There is an expanding number of effective treatments available for mental health conditions, and these treatments can be relatively costly. The particular characteristics of mental health conditions exacerbate the usual problems of moral hazard, adverse selection, and agency. There is increased recognition, in both the policy and economics literatures, of the array of services and supports required to enable people with severe mental illnesses to function in society’s mainstream. The need for such non-medical services, generates economic problems of cross-system coordination and opportunism. Moreover, the impairments imposed by mental disorders have become more disruptive to the labor market because the nature of work is changing in a manner that creates special disadvantages to people with these conditions. New directions for mental health economics would address these effects.
Article
Gerard J. van den Berg and Maarten Lindeboom
Modern-day famines are caused by unusual impediments or interventions in society, effectively imposing severe market restrictions and preventing the free movement of people and goods. Long-run health effects of exposure to famine are commonly studied to obtain insights into the long-run effects of malnutrition at early ages. This line of research has faced major methodological and data challenges. Recent research in various disciplines, such as economics, epidemiology, and demography, has made great progress in dealing with these issues. Malnutrition around birth affects a range of later-life individual outcomes, including health, educational, and economic outcomes.
Article
Owen O'Donnell
Financial protection is claimed to be an important objective of health policy. Yet there is a lack of clarity about what it is and no consensus on how to measure it. This impedes the design of efficient and equitable health financing. Arguably, the objective of financial protection is to shield nonmedical consumption from the cost of healthcare. The instruments are formal health insurance and public finances, as well as informal and self-insurance mechanisms that do not impair earnings potential. There are four main approaches to the measurement of financial protection: the extent of consumption smoothing over health shocks, the risk premium (willingness to pay in excess of a fair premium) to cover uninsured medical expenses, catastrophic healthcare payments, and impoverishing healthcare payments. The first of these does not restrict attention to medical expenses, which limits its relevance to health financing policy. The second rests on assumptions about risk preferences. No measure treats medical expenses that are financed through informal insurance and self-insurance instruments in an entirely satisfactory way. By ignoring these sources of imperfect insurance, the catastrophic payments measure overstates the impact of out-of-pocket medical expenses on living standards, while the impoverishment measure does not credibly identify poverty caused by them. It is better thought of as a correction to the measurement of poverty.
Article
Irina Grafova
One of the most fundamental results in health economics is that a greater socio-economic status is associated with better health outcomes. However, the experience of financial pressure and lack of resources transcends the notion of low income and poverty. Families of all income categories can experience financial pressure and lack of resources. This article reviews the literature examining the relationship between financial strain and various health outcomes. There are three main approaches to the measurement of financial strain found in the research literature, each one capturing a slightly different aspect: the family’s debt position, the availability of emergency funds, and inability to meet current financial obligations.
There are two main hypotheses explaining how financial strain may affect health. First, financial strain indicates a lower amount of financial resources available to individuals and families. This may have a dual impact on health. On the one hand, lower financial resources may lead to a decrease in consumption of substances such as tobacco that are harmful to health. On the other hand, lower financial resources may also negatively affect healthcare access, healthcare utilization, and adherence to treatment, with each contributing to a decline in health. Second, financial strain may produce greater uncertainty with regard to the availability of financial resources at present as well as in the future, thereby resulting in elevated stress, which may, in turn, result in poorer health outcomes. Examining the relationship between financial strain and health is complicated because it appears to be bidirectional. It is not only the case that financial strain may impact health but that health may impact financial strain.
The research literature consistently finds that financial strain has a detrimental impact on a variety of mental health outcomes. This relationship has been documented for a variety of financial strain indicators, including non-collateralized (unsecure) debt, mortgage debt, and the inability to meet current financial obligations. The research on the association between financial strain and health behavior outcomes is more ambiguous. As one example, there are mixed results concerning whether financial strain results in a higher likelihood of obesity. This research has considered various indicators of financial strain, including credit card debt and the inability to meet current financial obligations. It appears that both among adults and children there is no consistent evidence on the impact of financial strain on body weight. Similarly, the results on the impact of financial strain on alcohol use and substance abuse are mixed.
A number of significant questions regarding the relationship between financial strain and health remain unresolved. The majority of the existing studies focus on health outcomes among adults. There is a lack of understanding regarding how family exposure to financial strain can affect children. Additionally, very little is known about the implications of long-term exposure to financial strain. There are also some very important methodological challenges in this area of research related to establishing causality. Establishing causality and learning more about the implications of the exposure to financial strain could have important policy implications for a variety of safety net programs.
Article
Alexandrina Stoyanova and David Cantarero-Prieto
Long-term care (LTC) systems entitle frail and disabled people, who experience declines in physical and mental capacities, to quality care and support from an appropriately trained workforce and aim to preserve individual health and promote personal well-being for people of all ages. Myriad social factors pose significant challenges to LTC services and systems worldwide. Leading among these factors is the aging population—that is, the growing proportion of older people, the main recipients of LTC, in the population—and the implications not only for the health and social protection sectors, but almost all other segments of society. The number of elderly citizens has increased significantly in recent years in most countries and regions, and the pace of that growth is expected to accelerate in the forthcoming decades. The rapid demographic evolution has been accompanied by substantial social changes that have modified the traditional pattern of delivery LTC. Although families (and friends) still provide most of the help and care to relatives with functional limitations, changes in the population structure, such as weakened family ties, increased participation of women in the labor market, and withdrawal of early retirement policies, have resulted in a decrease in the provision of informal care. Thus, the growing demands for care, together with a lower potential supply of informal care, is likely to put pressure on the provision of formal care services in terms of both quantity and quality. Other related concerns include the sustainable financing of LTC services, which has declined significantly in recent years, and the pursuit of equity.
The current institutional background regarding LTC differs substantially across countries, but they all face similar challenges. Addressing these challenges requires a comprehensive approach that allows for the adoption of the “right” mix of policies between those aiming at informal care and those focusing on the provision and financing of formal LTC services.
Article
Bruce Chapman and Lorraine Dearden
The rapid worldwide growth in higher education undergraduate enrollments since around 1990 has meant that governments have had to rethink provision and funding arrangements to help ensure both cost-effective and equitable outcomes. It is important to understand in detail the fundamental financial conceptual building blocks that are necessary for an efficacious and socially just higher education financing system. In response to the critical question of who should pay for higher education and student income support, the case for the sharing of the costs between students, graduates, and taxpayers is overwhelming from the perspectives of both efficiency and equity. Further, there is a consensus that governments should intervene with respect to the underwriting of student loans, but there are very important and quite different implications for borrowers with respect to loan collection arrangements. The most equitable and effective higher education financing instrument involves loans that are repaid only when and if debtors can afford to do so, known as income-contingent loans. The less desirable form of student loans, defined by time-based collection, is internationally still the most common approach, but recent advances in economic theory and econometric methodology provide both conceptual bases and exciting and innovative ways for governments to understand why traditional student loan approaches are inferior to income-contingent collection. When the effects of student loans on access and welfare become more properly understood, the case for targeted assistance for all disadvantaged prospective students for reasons of social justice remains compelling. The importance of the attainment of the right financing system was highlighted by the economic trauma associated with the COVID-19 pandemic, an ordeal that caused many universities to experience an entirely unexpected financial crisis and led millions of students to struggle with unanticipated loan repayment difficulties.
Article
Mónica Hernández Alava
The assessment of health-related quality of life is crucially important in the evaluation of healthcare technologies and services. In many countries, economic evaluation plays a prominent role in informing decision making often requiring preference-based measures (PBMs) to assess quality of life. These measures comprise two aspects: a descriptive system where patients can indicate the impact of ill health, and a value set based on the preferences of individuals for each of the health states that can be described. These values are required for the calculation of quality adjusted life years (QALYs), the measure for health benefit used in the vast majority of economic evaluations. The National Institute for Health and Care Excellence (NICE) has used cost per QALY as its preferred framework for economic evaluation of healthcare technologies since its inception in 1999.
However, there is often an evidence gap between the clinical measures that are available from clinical studies on the effect of a specific health technology and the PBMs needed to construct QALY measures. Instruments such as the EQ-5D have preference-based scoring systems and are favored by organizations such as NICE but are frequently absent from clinical studies of treatment effect. Even where a PBM is included this may still be insufficient for the needs of the economic evaluation. Trials may have insufficient follow-up, be underpowered to detect relevant events, or include the wrong PBM for the decision- making body.
Often this gap is bridged by “mapping”—estimating a relationship between observed clinical outcomes and PBMs, using data from a reference dataset containing both types of information. The estimated statistical model can then be used to predict what the PBM would have been in the clinical study given the available information.
There are two approaches to mapping linked to the structure of a PBM. The indirect approach (or response mapping) models the responses to the descriptive system using discrete data models. The expected health utility is calculated as a subsequent step using the estimated probability distribution of health states. The second approach (the direct approach) models the health state utility values directly.
Statistical models routinely used in the past for mapping are unable to consider the idiosyncrasies of health utility data. Often they do not work well in practice and can give seriously biased estimates of the value of treatments. Although the bias could, in principle, go in any direction, in practice it tends to result in underestimation of cost effectiveness and consequently distorted funding decisions. This has real effects on patients, clinicians, industry, and the general public.
These problems have led some analysts to mistakenly conclude that mapping always induces biases and should be avoided. However, the development and use of more appropriate models has refuted this claim. The need to improve the quality of mapping studies led to the formation of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Mapping to Estimate Health State Utility values from Non-Preference-Based Outcome Measures Task Force to develop good practice guidance in mapping.
Article
Rita Dias Pereira, Pietro Biroli, Titus Galama, Stephanie von Hinke, Hans van Kippersluis, Cornelius A. Rietveld, and Kevin Thom
Nature (one’s genes) and nurture (one’s environment) jointly contribute to the formation and evolution of health and human capital over the life cycle. This complex interplay between genes and environment can be estimated and quantified using genetic information readily available in a growing number of social science data sets. Using genetic data to improve our understanding of individual decision making, inequality, and to guide public policy is possible and promising, but requires a grounding in essential genetic terminology, knowledge of the literature in economics and social-science genetics, and a careful discussion of the policy implications and prospects of the use of genetic data in the social sciences and economics.
Article
Richard Smith and Johanna Hanefeld
Global trade—the movement of goods, services, people, and capital between countries—is at the center of modern globalization. Since the late 20th century trade has also become established as a critical determinant of public health. As the raison d’être of trade is to increase both wealth and the availability of goods and services, changing trade patterns will inevitably impact many of the known determinants of health, including employment, nutrition, environmental factors, social capital, and education. Trade will also impact the health sector itself, most clearly through direct trade in health-related goods and services (such as pharmaceuticals, health workers, foreign direct investment in health services, and mobile patients), but also more broadly in determining tax receipts and thus overall public expenditures. It is also the case that trade—especially rapid and widespread movement of people, animals, and goods—may facilitate the rapid and widespread spread of disease. Trade, and associated policies governing and responding to that trade, has thus become increasingly recognized as a critical driver of health issues.
The design of trade policies that reduce the potential health risks associated with freer trade while maximizing the positive impact of trade liberalization on the social determinants of health is still in its infancy. There remains a lack of sound empirical evidence demonstrating how trade liberalization links directly and indirectly to health. Even though the positive link between increased trade, poverty reduction, and economic growth is widely accepted, evidence regarding the impact of trade liberalization on the social determinants of health varies from one national context to another. Hence, adapting trade liberalization to national conditions is important in ensuring desired outcomes. Yet although evidence is necessary, it is not sufficient to ensure that health is more integrated in trade negotiations and decision-making. There is a substantive requirement for those with a health remit to engage in negotiation with those from other sectors and from other geographic locations.
Article
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.
Article
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.
