The primary goals of food assistance programs are to alleviate child hunger and reduce food insecurity; if successful, such programs may have the added benefit of improving child academic outcomes (e.g., test scores, attendance, behavioral outcomes). Some U.S. government programs serve children in the home, such as the Supplemental Nutritional Assistance Program (SNAP), others serve them at school, such as the National School Lunch Program (NSLP) and School Breakfast Program (SBP), and still others fall in-between, such as the Summer Food Service Program (SFSP) and the Child and Adult Care Food Program (CACFP). Most empirical research seeking to identify the causal effect of such programs on child academic outcomes addresses the endogeneity of program participation with a reduced form, intent-to-treat approach. Specifically, such studies estimate the effect of a program’s availability, timing, or other specific feature on the academic outcomes of all potentially affected children. While findings of individual studies and interventions are mixed, some general conclusions emerge. First, increasing the availability of these programs typically has beneficial effects on relatively contemporaneous academic and behavioral outcomes. The magnitudes are modest but still likely pass cost-benefit criteria, even ignoring the fact that the primary objective of such programs is alleviating hunger, not improving academic outcomes. Less is known about the dynamics of the effects, for example, whether such effects are temporary boosts that dissipate or instead accumulate and grow over time. Likewise, the effects of recent innovations to these programs, such as breakfast in the classroom or increases in SNAP benefits to compensate for reduced time in school during the pandemic, yield less clear conclusions (the former) and/or have not been studied (the latter). Finally, many smaller programs that likely target the neediest children remain under- or un-examined. Unstudied government-provided programs include SFSP and CACFP. There are also a growing number of understudied programs provided primarily by charitable organizations. Emerging evidence suggests that one such program, Weekend Feeding or “Backpack” programs, confers substantial benefits. There, too, more work needs to be done, both to confirm these early findings and to explore recent innovations such as providing food pantries or “Kids’ Cafés” on school grounds. Especially in light of the uncertain fate of many pandemic-related program expansions and innovations, current empirical evidence establishes that the additional, beneficial spillover effects to academic outcomes—beyond the primary objective of alleviating food insecurity—deserve to be considered as well.
The Academic Effects of United States Child Food Assistance Programs—At Home, School, and In-Between
Michael D. Kurtz, Karen Smith Conway, and Robert D. Mohr
Aging and Healthcare Costs
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.
An Analysis of COVID-19 Student Learning Loss
Harry Patrinos, Emiliana Vegas, and Rohan Carter-Rau
The coronavirus disease 2019 (COVID-19) pandemic led to school closures around the world, affecting almost 1.6 billion students. This caused significant disruption to the global education system. Even short interruptions in a child’s schooling have significant negative effects on their learning and can be long lasting. The capacities of education systems to respond to the crisis by delivering remote learning and support to children and families have been diverse and uneven. In response to this disruption, education researchers are beginning to analyze the impact of these school closures on student learning loss. The term learning loss is commonly used in the literature to describe declines in student knowledge and skills. Early reviews of the first wave of lockdowns and school closures suggested significant learning loss in a few countries. A more recent and thorough analysis of recorded learning loss evidence documented since the beginning of the school closures between March 2020 and March 2022 found even more evidence of learning loss. In 36 identified robust studies, the majority identified learning losses that amount to, on average, 0.17 of a standard deviation (SD), equivalent to roughly a one-half school year’s worth of learning. This confirms that learning loss is real and significant and has continued to grow after the first year of the COVID-19 pandemic. Most studies observed increases in inequality where certain demographics of students experienced more significant learning losses than others. The longer the schools remained closed, the greater were the learning losses. For the 19 countries for which there are robust learning loss data, average school closures were 15 weeks, leading to average learning losses of 0.18 SD. Put another way, for every week that schools were closed, learning declined by an average of 0.01 SD. However, there are also outliers—countries that managed to limit the amount of loss. In Nara City, Japan, for example, the initial closures had brought down test scores, but responsive policies largely overcame this decline. In addition, a decreased summer vacation helped. In Denmark, children received good home support and their reading behavior improved significantly. In Sweden, where primary schools did not close during the pandemic, there were no reported learning losses. Further work is needed to increase the quantity of studies produced, particularly in low- and middle-income countries, and to ascertain the reasons for learning loss. Finally, the few cases where learning loss was mitigated should be further investigated to inform continued and future pandemic responses.
Anthropometrics: The Intersection of Economics and Human Biology
Anthropometrics is a research program that explores the extent to which economic processes affect human biological processes using height and weight as markers. This agenda differs from health economics in the sense that instead of studying diseases or longevity, macro manifestations of well-being, it focuses on cellular-level processes that determine the extent to which the organism thrives in its socio-economic and epidemiological environment. Thus, anthropometric indicators are used as a proxy measure for the biological standard of living as complements to conventional measures based on monetary units. Using physical stature as a marker, we enabled the profession to learn about the well-being of children and youth for whom market-generated monetary data are not abundant even in contemporary societies. It is now clear that economic transformations such as the onset of the Industrial Revolution and modern economic growth were accompanied by negative externalities that were hitherto unknown. Moreover, there is plenty of evidence to indicate that the Welfare States of Western and Northern Europe take better care of the biological needs of their citizens than the market-oriented health-care system of the United States. Obesity has reached pandemic proportions in the United States affecting 40% of the population. It is fostered by a sedentary and harried lifestyle, by the diminution in self-control, the spread of labor-saving technologies, and the rise of instant gratification characteristic of post-industrial society. The spread of television and a fast-food culture in the 1950s were watershed developments in this regard that accelerated the process. Obesity poses a serious health risk including heart disease, stroke, diabetes, and some types of cancer and its cost reaches $150 billion per annum in the United States or about $1,400 per capita. We conclude that the economy influences not only mortality and health but reaches bone-deep into the cellular level of the human organism. In other words, the economy is inextricably intertwined with human biological processes.
Assessments in Education
Hans Henrik Sievertsen
Assessments like standardized tests and teacher evaluations are central elements of educational systems. Assessments affect the behaviour of students, teachers, parents, schools, and policymakers through at least two channels: The information channel and the incentive channel. Students use the information to adjust study effort and to guide their course selection. Schools and teachers use information from assessments to evaluate teaching quality and the effectiveness of the applied methods. Educational programs use information from assessment results to sort students in educational programs and employers use the results as signals of productivity in their hiring decisions. Finally, policymakers use assessments in accountability systems to reward or penalize schools, and parents use information from assessment results to select schools. The incentive channel is a natural consequence of the information channel: Students are incentivized to work hard and do well in assessments to get access to educational programs and jobs. Teachers and schools are incentivized to do well to receive rewards or avoid punishments in accountability systems. The information channel is important for ensuring the most efficient human capital investments: students learn about the returns and costs of effort investments and about their abilities and comparative advantages. Teachers and schools learn about the most effective teaching methods. However, because of the strong incentives linked to assessments, both students and teachers might focus on optimizing assessment results at the cost of learning. Students might for example select tracks that maximize their grades instead of selecting tracks aligned with their interests and comparative advantages. Understanding the implications of assessments for the behaviour of students, parents, teachers, and schools is therefore necessary to achieve the overall goals of the educational system. Because education affects lifetime earnings, health, and well-being and assessments play an important role in individuals’ educational careers, assessments are also important for efficiency and equity across domains. Biases in assessments and the heterogeneity in access to assessments are sources of inequality in education according to gender, origin, and socioeconomic background. Finally, because assessment results also carry important consequences for individuals’ educational opportunities and in the labor market, they are a source of stress and reduced well-being.
Bayesian Statistical Economic Evaluation Methods for Health Technology Assessment
Andrea Gabrio, Gianluca Baio, and Andrea Manca
The evidence produced by healthcare economic evaluation studies is a key component of any Health Technology Assessment (HTA) process designed to inform resource allocation decisions in a budget-limited context. To improve the quality (and harmonize the generation process) of such evidence, many HTA agencies have established methodological guidelines describing the normative framework inspiring their decision-making process. The information requirements that economic evaluation analyses for HTA must satisfy typically involve the use of complex quantitative syntheses of multiple available datasets, handling mixtures of aggregate and patient-level information, and the use of sophisticated statistical models for the analysis of non-Normal data (e.g., time-to-event, quality of life and costs). Much of the recent methodological research in economic evaluation for healthcare has developed in response to these needs, in terms of sound statistical decision-theoretic foundations, and is increasingly being formulated within a Bayesian paradigm. The rationale for this preference lies in the fact that by taking a probabilistic approach, based on decision rules and available information, a Bayesian economic evaluation study can explicitly account for relevant sources of uncertainty in the decision process and produce information to identify an “optimal” course of actions. Moreover, the Bayesian approach naturally allows the incorporation of an element of judgment or evidence from different sources (e.g., expert opinion or multiple studies) into the analysis. This is particularly important when, as often occurs in economic evaluation for HTA, the evidence base is sparse and requires some inevitable mathematical modeling to bridge the gaps in the available data. The availability of free and open source software in the last two decades has greatly reduced the computational costs and facilitated the application of Bayesian methods and has the potential to improve the work of modelers and regulators alike, thus advancing the fields of economic evaluation of healthcare interventions. This chapter provides an overview of the areas where Bayesian methods have contributed to the address the methodological needs that stem from the normative framework adopted by a number of HTA agencies.
Behavioral Experiments in Health Economics
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 application 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.
The Business Cycle and Health
Cristina Bellés-Obrero and Judit Vall Castelló
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.
Business Cycles and Apprenticeships
Samuel Muehlemann and Stefan Wolter
The economic reasons why firms engage in apprenticeship training are twofold. First, apprenticeship training is a potentially cost-effective strategy for filling a firm’s future vacancies, particularly if skilled labor on the external labor market is scarce. Second, apprentices can be cost-effective substitutes for other types of labor in the current production process. As current and expected business and labor market conditions determine a firm’s expected work volume and thus its future demand for skilled labor, they are potentially important drivers of a firm’s training decisions. Empirical studies have found that the business cycle affects apprenticeship markets. However, while the economic magnitude of these effects is moderate on average, there is substantial heterogeneity across countries, even among those that at first sight seem very similar in terms of their apprenticeship systems. Moreover, identification of business cycle effects is a difficult task. First, statistics on apprenticeship markets are often less developed than labor market statistics, making empirical analyses of demand and supply impossible in many cases. In particular, data about unfilled apprenticeship vacancies and unsuccessful applicants are paramount for assessing potential market failures and analyzing the extent to which business cycle fluctuations may amplify imbalances in apprenticeship markets. Second, the intensity of business cycle effects on apprenticeship markets is not completely exogenous, as governments typically undertake a variety of measures, which differ across countries and may change over time, to reduce the adverse effects of economic downturns on apprenticeship markets. During the economic crisis related to the COVID-19 global pandemic, many countries took unprecedented actions to support their economies in general and reacted swiftly to introduce measures such as the provision of financial subsidies for training firms or the establishment of apprenticeship task forces. As statistics on apprenticeship markets improve over time, such heterogeneity in policy measures should be exploited to improve our understanding of the business cycle and its relationship with apprenticeships.
Challenges in Financing Universal Health Coverage in Sub-Saharan Africa
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.
Changes in Hospital Financing and Organization and Their Impact on Hospital Performance
Since the 1980s policymakers have identified a wide range of policy interventions to improve hospital performance. Some of these have been initiated at the level of government, whereas others have taken the form of decisions made by individual hospitals but have been guided by regulatory or financial incentives. Studies investigating the impact that some of the most important of these interventions have had on hospital performance can be grouped into four different research streams. Among the research streams, the strongest evidence exists for the effects of privatization. Studies on this topic use longitudinal designs with control groups and have found robust increases in efficiency and financial performance. Evidence on the entry of hospitals into health systems and the effects of this on efficiency is similarly strong. Although the other three streams of research also contain well-conducted studies with valuable findings, they are predominantly cross-sectional in design and therefore cannot establish causation. While the effects of introducing DRG-based hospital payments and of specialization are largely unclear, vertical and horizontal cooperation probably have a positive effect on efficiency and financial performance. Lastly, the drivers of improved efficiency or financial performance are very different depending on the reform or intervention being investigated; however, reductions in the number of staff and improved bargaining power in purchasing stand out as being of particular importance. Several promising avenues for future investigation are identified. One of these is situated within a new area of research examining the link between changes in the prices of treatments and hospitals’ responses. As there is evidence of unintended effects, future studies should attempt to distinguish between changes in hospitals’ responses at the intensive margin (e.g., upcoding) versus the extensive margin (e.g., increase in admissions). When looking at the effects of entering into a health system and of privatizations, there is still considerable need for research. With privatizations, in particular, the underlying processes are not yet fully understood, and the potential trade-offs between increases in performance and changes in the quality of care have not been sufficiently examined. Lastly, there is substantial need for further papers in the areas of multi-institutional arrangements and cooperation, as well as specialization. In both research streams, natural experiments carried out using program evaluation design are lacking. One of the main challenges here, however, is that cooperation and specialization cannot be directly observed but rather must be constructed based on survey or administrative data.
Charter Schools’ Effectiveness, Mechanisms, and Competitive Influence
Sarah R. Cohodes and Katharine S. Parham
Across the United States, charter schools—publicly funded and regulated, but privately run schools—appear to perform, on average, at about the same level as their district counterparts. The broadest studies of charter school effectiveness use observational methods, which may not fully account for selection of students into charter schools. However, this finding is confirmed by lottery-based evidence from a few broad samples that again presents a varied picture of charter impact and little average difference across sectors. Underlying the similarity in performance across sectors is one of the most consistent findings from both observational and lottery-based evidence of charter schools’ impact on student achievement: Charters located in urban areas boost student test scores, particularly for Black, Latinx, and students from lower-income households. The test score gains appear to be largest in urban charters that employ “No Excuses” practices. Attending some urban charter schools also increases college enrollment and voting and reduces risky behavior. However, evidence on such long-term outcomes is limited to a few samples, and evidence on college graduation and adult earnings is even rarer, making it difficult to draw conclusions beyond test scores about the overall effectiveness of the charter sector. Research on the mechanisms underlying charter successes, when they occur, is growing. No Excuses charter schools—which employ high expectations, strict disciplinary codes, and intense academic focus—generate consistent test score gains, but their controversial disciplinary practices are not necessarily a condition for academic success. Charter school teachers tend to be less qualified and more likely to leave the profession than traditional public school teachers, though the impact of these challenges for the labor market is understudied. Similarly, the influence of charter authorizers and related accountability structures is limited and would benefit from examination using more rigorous methodologies. The competitive impact of charter schools on traditional public schools typically suggests a small, beneficial influence on neighboring schools’ student achievement, though there is variation across contexts. Additionally, while some local analyses suggest charters reduce funding in nearby districts, at least in the short term, a larger scale study finds charter entry generates more revenue per pupil for district schools. There is competing evidence on charters’ contribution to school racial segregation, and little evidence on the impact of newer, intentionally diverse school models. In all, more research, in more contexts, is needed to further understand where, for whom, and why charters are most effective.
Childcare and Children’s Development: Features of Effective Programs
Jo Blanden and Birgitta Rabe
Governments around the world are increasingly investing resources for young children, and universal provision of early childhood education and care (ECEC) has become widespread. Children’s development is affected by the investments they receive both within and outside the household. A simple theoretical framework predicts that the provision of public childcare will improve children’s development if it offers more stimulation than the care it replaces. Generally, carefully designed studies show that the provision of early childcare is beneficial, especially for children from disadvantaged backgrounds. This is in line with expectations that the alternative care experienced by children from less affluent, less educated, and immigrant backgrounds is likely to be of lower quality. Interestingly, however, studies show that the children who would benefit the most are least likely to receive care, providing a challenge for policy makers. Some programs, such as the $5-per-day childcare in Quebec, have negative effects and therefore may be of poor quality. However, comparing results across programs that vary in several dimensions makes it difficult to separate out the ingredients that are most important for success. Studies that focus on identifying the factors in ECEC that lead to the greatest benefit indicate that some standard measures such as staff qualifications are weakly linked to children’s outcomes, whereas larger staff–child ratios and researcher-measured process quality are beneficial. Spending more time in high-quality childcare from around age 3 has proved to be beneficial, whereas the effect of an increase in childcare for younger children is particularly sensitive to each program’s features and context.
Choice Inconsistencies in the Demand for Private Health Insurance
In many countries of the world, consumers choose their health insurance coverage from a large menu of often complex options supplied by private insurance companies. Economic benefits of the wide choice of health insurance options depend on the extent to which the consumers are active, well informed, and sophisticated decision makers capable of choosing plans that are well-suited to their individual circumstances. There are many possible ways how consumers’ actual decision making in the health insurance domain can depart from the standard model of health insurance demand of a rational risk-averse consumer. For example, consumers can have inaccurate subjective beliefs about characteristics of alternative plans in their choice set or about the distribution of health expenditure risk because of cognitive or informational constraints; or they can prefer to rely on heuristics when the plan choice problem features a large number of options with complex cost-sharing design. The second decade of the 21st century has seen a burgeoning number of studies assessing the quality of consumer choices of health insurance, both in the lab and in the field, and financial and welfare consequences of poor choices in this context. These studies demonstrate that consumers often find it difficult to make efficient choices of private health insurance due to reasons such as inertia, misinformation, and the lack of basic insurance literacy. These findings challenge the conventional rationality assumptions of the standard economic model of insurance choice and call for policies that can enhance the quality of consumer choices in the health insurance domain.
Competition and Quality in Healthcare
Peter Sivey and Yijuan Chen
Quality competition between alternative providers is an increasingly important topic in the health economics literature. This literature includes theoretical and empirical studies that have been developed in parallel to 21st-century policies to increase competition between doctors or hospitals. Theoretical studies have clarified how competitive markets can give healthcare providers the incentive to improve quality. Broadly speaking, if providers have an incentive to attract more patients and patients value quality, providers will raise quality until the costs of raising quality are equal to the additional revenue from patients attracted by the rise in quality. The theoretical literature has also investigated how institutional and policy parameters determine quality levels in equilibrium. Important parameters in models of quality competition include the degree of horizontal differentiation, the level of information about provider quality, the costs of switching between providers, and the time-horizon of quality investment decisions. Empirical studies have focused on the prerequisites of quality competition (e.g., do patients choose higher quality providers?) and the impact of pro-competition policies on quality levels. The most influential studies have used modern econometric approaches, including difference-in differences and instrumental variables, to identify plausibly causal effects. The evidence suggests that in most contexts, quality is a determinant of patient choice of provider, especially after greater patient choice is made available or information is published about provider quality. The evidence that increases in competition improve quality in healthcare is less clear cut. Perhaps reflecting the economic theory of quality competition, showing that different parameter combinations or assumptions can produce different outcomes, empirical results are also mixed. While a series of high-quality studies in the United Kingdom appear to show strong improvements in quality in more competitive areas following pro-competition reforms introducing more choice and competition, other studies showed that these quality improvements do not extend to all types of healthcare or alternative measures of quality. The most promising areas for future research include investigating the “black box” of quality improvement under competition, and behavioral studies investigating financial and nonfinancial motivations for quality improvements in competitive markets.
Considering Health-Systems Constraints in Economic Evaluation in Low- and Middle-Income Settings
Anna Vassall, Fiammetta Bozzani, and Kara Hanson
In order to secure effective service access, coverage, and impact, it is increasingly recognized that the introduction of novel health technologies such as diagnostics, drugs, and vaccines may require additional investment to address the constraints under which many health systems operate. Health-system constraints include a shortage of health workers, ineffective supply chains, or inadequate information systems, or organizational constraints such as weak incentives and poor service integration. Decision makers may be faced with the question of whether to invest in a new technology, including the specific health system strengthening needed to ensure effective implementation; or they may be seeking to optimize resource allocation across a range of interventions including investment in broad health system functions or platforms. Investment in measures to address health-system constraints therefore increasingly need to undergo economic evaluation, but this poses several methodological challenges for health economists, particularly in the context of low- and middle-income countries. Designing the appropriate analysis to inform investment decisions concerning new technologies incorporating health systems investment can be broken down into several steps. First, the analysis needs to comprehensively outline the interface between the new intervention and the system through which it is to be delivered, in order to identify the relevant constraints and the measures needed to relax them. Second, the analysis needs to be rooted in a theoretical approach to appropriately characterize constraints and consider joint investment in the health system and technology. Third, the analysis needs to consider how the overarching priority- setting process influences the scope and output of the analysis informing the way in which complex evidence is used to support the decision, including how to represent and manage system wide trade-offs. Finally, there are several ways in which decision analytical models can be structured, and parameterized, in a context of data scarcity around constraints. This article draws together current approaches to health system thinking with the emerging literature on analytical approaches to integrating health-system constraints into economic evaluation to guide economists through these four issues. It aims to contribute to a more health-system-informed approach to both appraising the cost-effectiveness of new technologies and setting priorities across a range of program activities.
Contracts and Working Conditions in Medicine
Helen Hayes and Matt Sutton
Contracts and working conditions are important influences on the medical workforce that must be carefully constructed and considered by policymakers. Contracts involve an enforceable agreement of the rights and responsibilities of both employer and employee. The principal–agent relationship and presence of asymmetric information in healthcare means that contracts must be incentive compatible and create sufficient incentive for doctors to act in the payer’s best interests. Within medicine, there are special characteristics that are believed to be particularly pertinent to doctors, who act as agents to both the patient and the payer. These include intrinsic motivation, professionalism, altruism, and multitasking, and they influence the success of these contracts. The three most popular methods of payment are fee-for-service, capitation, and salaries. In most contexts a blend of each of these three payment methods is used; however, guidance on the most appropriate blend is unclear and the evidence on the special nature of doctors is insubstantial. The role of skill mix and teamwork in a healthcare setting is an important consideration as it impacts the success of incentives and payment systems and the efficiency of workers. Additionally, with increasing demand for healthcare, changing skill mix is one response to problems with recruitment and retention in health services. Health systems in many settings depend on a large proportion of foreign-born workers and so migration is a key consideration in retention and recruitment of health workers. Finally, forms of external regulation such as accreditation, inspection, and revalidation are widely used in healthcare systems; however, robust evidence of their effectiveness is lacking.
The Contribution of Vocational Education and Training to Innovation and Growth
Uschi Backes-Gellner and Patrick Lehnert
Despite the common view that innovation requires academically educated workers, some countries that strongly emphasize vocational education and training (VET) in their education systems—such as Switzerland and Germany—are highly competitive internationally in terms of innovation. These countries have dual VET programs, that is, upper-secondary-level apprenticeship programs, that combine about three quarters of workplace training with about one quarter of vocational schooling, and design them in such a way that their graduates (i.e., dual apprenticeship-graduates) play crucial roles in innovation processes. Regular updates of VET curricula incorporate the latest technological developments into these curricula, thereby ensuring that dual apprenticeship-graduates possess up-to-date, high-level skills in their chosen occupation. This process allows these graduates to contribute to innovation in firms. Moreover, these graduates acquire broad sets of technical and soft skills that enhance their job mobility and flexibility. Therefore, conventional wisdom notwithstanding, dual apprenticeship-graduates in such countries not only have broad skill sets that accelerate innovation in firms, but also willingly participate in innovation because of their high flexibility and employability. Moreover, Switzerland and Germany have tertiary-level VET institutions that foster innovation. These are universities of applied sciences (UASs), which teach and conduct applied research, thereby helping build a bridge between different types of knowledge (vocational and academic). UAS students have prior vocational knowledge through their dual apprenticeship and acquire applied research skills from UAS professors who usually have both work experience and a doctoral degree from an academic university. Thus UAS graduates combine sound occupational knowledge with applied research knowledge inspired by input from the academic research frontier and from practical research and development (R & D) in firms. Firms employ UAS graduates with their knowledge combination as an important input for R & D. Consequently, regions with a UAS have higher levels of innovation than regions without one. This effect is particularly strong for regions outside major innovation centers and for regions with larger percentages of smaller firms.
COVID-19 and Mental Health: Natural Experiments of the Costs of Lockdowns
Climent Quintana-Domeque and Jingya Zeng
The global impact of the COVID-19 pandemic has been profound, leaving a significant imprint on physical health, the economy, and mental well-being. Researchers have undertaken empirical investigations across different countries, with a primary focus on understanding the association between lockdown measures—an essential public health intervention—and mental health. These studies aim to discern the causal effect of lockdowns on mental well-being. Three notable studies have adopted natural experiments to explore the causal effect of lockdowns on mental health in diverse countries. Despite variations in their research methodologies, these studies collectively support the conclusion that lockdowns have had detrimental consequences on mental health. Furthermore, they reveal that the intensity of these negative effects varies among distinct population groups. Certain segments of the population, such as women, have borne a more profound burden of the mental health costs associated with lockdown measures. In light of these findings, it becomes imperative to consider the implications for mental health when implementing public health interventions, especially during crises like the COVID-19 pandemic. While rigorous measures like lockdowns are essential for safeguarding public health, striking a balance with robust mental health support policies becomes crucial to mitigating the adverse impacts on mental well-being.
Design of Discrete Choice Experiments
Deborah J. Street and Rosalie Viney
Discrete choice experiments are a popular stated preference tool in health economics and have been used to address policy questions, establish consumer preferences for health and healthcare, and value health states, among other applications. They are particularly useful when revealed preference data are not available. Most commonly in choice experiments respondents are presented with a situation in which a choice must be made and with a a set of possible options. The options are described by a number of attributes, each of which takes a particular level for each option. The set of possible options is called a “choice set,” and a set of choice sets comprises the choice experiment. The attributes and levels are chosen by the analyst to allow modeling of the underlying preferences of respondents. Respondents are assumed to make utility-maximizing decisions, and the goal of the choice experiment is to estimate how the attribute levels affect the utility of the individual. Utility is assumed to have a systematic component (related to the attributes and levels) and a random component (which may relate to unobserved determinants of utility, individual characteristics or random variation in choices), and an assumption must be made about the distribution of the random component. The structure of the set of choice sets, from the universe of possible choice sets represented by the attributes and levels, that is shown to respondents determines which models can be fitted to the observed choice data and how accurately the effect of the attribute levels can be estimated. Important structural issues include the number of options in each choice set and whether or not options in the same choice set have common attribute levels. Two broad approaches to constructing the set of choice sets that make up a DCE exist—theoretical and algorithmic—and no consensus exists about which approach consistently delivers better designs, although simulation studies and in-field comparisons of designs constructed by both approaches exist.