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The literature on optimum currency areas differs from that on other topics in economic theory in a number of notable respects. Most obviously, the theory is framed in verbal rather than mathematical terms. Mundell’s seminal article coining the term and setting out the theory’s basic propositions relied entirely on words rather than equations. The same was true of subsequent contributions focusing on the sectoral composition of activity and the role of fiscal flows. A handful of more recent articles specified and analyzed formal mathematical models of optimum currency areas. But it is safe to say that none of these has “taken off” in the sense of becoming the workhorse framework on which subsequent scholarship builds. The theoretical literature remains heavily qualitative and narrative compared to other areas of economic theory. While Mundell, McKinnon, Kenen, and the other founding fathers of optimum-currency-area theory provided powerful intuition, attempts to further formalize that intuition evidently contributed less to advances in economic understanding than has been the case for other theoretical literatures.
Second, recent contributions to the literature on optimum currency areas are motivated to an unusual extent by a particular case, namely Europe’s monetary union. This was true already in the 1990s, when the EU’s unprecedented decision to proceed with the creation of the euro highlighted the question of whether Europe was an optimum currency area and, if not, how it might become one. That tendency was reinforced when Europe then descended into crisis starting in 2009. With only slight exaggeration it can be said that the literature on optimum currency areas became almost entirely a literature on Europe and on that continent’s failure to satisfy the relevant criteria.
Third, the literature on optimum currency areas remains the product of its age. When the founders wrote, in the 1960s, banks were more strictly regulated, and financial markets were less internationalized than subsequently. Consequently, the connections between monetary integration and financial integration—whether monetary union requires banking union, as the point is now put—were neglected in the earlier literature. The role of cross-border financial flows as a destabilizing mechanism within a currency area did not receive the attention it deserved. Because much of that earlier literature was framed in a North American context—the question was whether the United States or Canada was an optimum currency area—and because it was asked by a trio of scholars, two of whom hailed from Canada and one of whom hailed from the United States, the challenges of reconciling monetary integration with political nationalism and the question of whether monetary requires political union were similarly underplayed. Given the euro area’s descent into crisis, a number of analysts have asked why economists didn’t sound louder warnings in advance. The answer is that their outlooks were shaped by a literature that developed in an earlier era when the risks and context were different.
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.
Detection of outliers is an important explorative step in empirical analysis. Once detected, the investigator will have to decide how to model the outliers depending on the context. Indeed, the outliers may represent noisy observations that are best left out of the analysis or they may be very informative observations that would have a particularly important role in the analysis. For regression analysis in time series a number of outlier algorithms are available, including impulse indicator saturation and methods from robust statistics. The algorithms are complex and their statistical properties are not fully understood. Extensive simulation studies have been made, but the formal theory is lacking. Some progress has been made toward an asymptotic theory of the algorithms. A number of asymptotic results are already available building on empirical process theory.
Jun Li and Edward C. Norton
Pay-for-performance programs have become a prominent supply-side intervention to improve quality and decrease spending in health care, touching upon long-term care, acute care, and outpatient care. Pay-for-performance directly targets long-term care, with programs in nursing homes and home health. Indirectly, pay-for-performance programs targeting acute care settings affect clinical practice for long-term care providers through incentives for collaboration across settings.
As a whole, pay-for-performance programs entail the identification of problems it seeks to solve, measurement of the dimensions it seeks to incentivize, methods to combine and translate performance to incentives, and application of the incentives to reward performance. For the long-term care population, pay-for-performance programs must also heed the unique challenges specific to the sector, such as patients with complex health needs and distinct health trajectories, and be structured to recognize the challenges of incentivizing performance improvement when there are multiple providers and payers involved in the care delivery.
Although empirical results indicate modest effectiveness of pay-for-performance in long-term care on improving targeted measures, some research has provided more clarity on the role of pay-for-performance design on the output of the programs, highlighting room for future research. Further, because health care is interconnected, the indirect effects of pay-for-performance programs on long-term care is an underexplored topic. As the scope of pay-for-performance in long-term care expands, both within the United States and internationally, pay-for-performance offers ample opportunities for future research.
Mark F. Grady
Tort law is part of the common law that originated in England after the Norman Conquest and spread throughout the world, including to the United States. It is judge-made law that allows people who have been injured by others to sue those who harmed them and collect damages in proper cases. Since its early origins, tort law has evolved considerably and has become a full-fledged “grown order,” like the economy, and can best be understood by positive theory, also like the economy. Economic theories of tort have developed since the early 1970s, and they too have evolved over time. Their objective is to generate fresh insight about the purposes and the workings of the tort system.
The basic thesis of the economic theory is that tort law creates incentives for people to minimize social cost, which is comprised of the harm produced by torts and the cost of the precautions necessary to prevent torts. This thesis, intentionally simple, generates many fresh insights about the workings and effects of the tort system and even about the actual legal rules that judges have developed. In an evolved grown order, legal rules are far less concrete than most people would expect though often very clear in application. Beginning also in the 1970s, legal philosophers have objected to the economic theory of tort and have devised philosophical theories that compete. The competition, moreover, has been productive because it has spurred both sides to revise and improve their theories and to seek better to understand the law. Tort law is diverse, applicable to many different activities and situations, so developing a positive theory about it is both challenging and rewarding.
James P. Ziliak
The interaction between poverty and social policy is an issue of longstanding interest in academic and policy circles. There are active debates on how to measure poverty, including where to draw the threshold determining whether a family is deemed to be living in poverty and how to measure resources available. These decisions have profound impacts on our understanding of the anti-poverty effectiveness of social welfare programs. In the context of the United States, focusing solely on cash income transfers shows little progress against poverty over the past 50 years, but substantive gains are obtained if the resource concept is expanded to include in-kind transfers and refundable tax credits. Beyond poverty, the research literature has examined the effects of social welfare policy on a host of outcomes such as labor supply, consumption, health, wealth, fertility, and marriage. Most of this work finds the disincentive effects of welfare programs on work, saving, and family structure to be small, but the income and consumption smoothing benefits to be sizable, and some recent work has found positive long-term effects of transfer programs on the health and education of children. More research is needed, however, on how to measure poverty, especially in the face of deteriorating quality of household surveys, on the long-term consequences of transfer programs, and on alternative designs of the welfare state.
Jesús Gonzalo and Jean-Yves Pitarakis
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.
Predictive regressions refer to models whose aim is to assess the predictability of a typically noisy time series, such as stock returns or currency returns with past values of a highly persistent predictor such as valuation ratios, interest rates, or volatilities, among other variables. Obtaining reliable inferences through conventional methods can be challenging in such environments mainly due to the joint interactions of predictor persistence, potential endogeneity, and other econometric complications. Numerous methods have been developed in the literature ranging from adjustments to test statistics used in significance testing to alternative instrumental variable based estimation methods specifically designed to neutralize inferences to the stochastic properties of the predictor(s).
Early developments in this area were mainly confined to linear and single predictor settings, but recent developments have raised the issue of adaptability of existing estimation and inference methods to more general environments so as to extend the use of predictive regressions to a wider range of potential applications.
An important extension involves allowing predictability to enter nonlinearly so as to capture time variation in the role of particular predictors. Economically interesting nonlinearities include, for instance, the use of threshold effects that allow predictability to vanish or strengthen during particular episodes, creating pockets of predictability. Such effects may kick in in the conditional means but also in the variances or both and may help uncover important phenomena such as the countercyclical nature of stock return predictability recently documented in the literature.
Due to the frequent need to consider multiple as opposed to single predictors it also becomes important to evaluate the validity and feasibility of inferences about linear and nonlinear predictability when multiple predictors of potentially different degrees of persistence are allowed to coexist in such settings.
Payment systems based on fixed prices have become the dominant model to finance hospitals across OECD countries. In the early 1980s, Medicare in the United States introduced the Diagnosis Related Groups (DRG) system. The idea was that hospitals should be paid a fixed price for treating a patient within a given diagnosis or treatment. The system then spread to other European countries (e.g., France, Germany, Italy, Norway, Spain, the United Kingdom) and high-income countries (e.g., Canada, Australia). The change in payment system was motivated by concerns over rapid health expenditure growth, and replaced financing arrangements based on reimbursing costs (e.g., in the United States) or fixed annual budgets (e.g., in the United Kingdom).
A more recent policy development is the introduction of pay for performance (P4P) schemes, which, in most cases, pay directly for higher quality. This is also a form of regulated price payment but the unit of payment is a (process or outcome) measure of quality, as opposed to activity, that is admitting a patient with a given diagnosis or a treatment.
Fixed price payment systems, either of the DRG type or the P4P type, affect hospital incentives to provide quality, contain costs, and treat the right patients (allocative efficiency). Quality and efficiency are ubiquitous policy goals across a range of countries.
Fixed price regulation induces providers to contain costs and, under certain conditions (e.g., excess demand), offer some incentives to sustain quality. But payment systems in the health sector are complex. Since its inception, DRG systems have been continuously refined. From their initial (around) 500 tariffs, many DRG codes have been split in two or more finer ones to reflect heterogeneity in costs within each subgroup. In turn, this may give incentives to provide excessive intensive treatments or to code patients in more remunerative tariffs, a practice known as upcoding. Fixed prices also make it financially unprofitable to treat high cost patients. This is particularly problematic when patients with the highest costs have the largest benefits from treatment. Hospitals also differ systematically in costs and other dimensions, and some of these external differences are beyond their control (e.g., higher cost of living, land, or capital). Price regulation can be put in place to address such differences.
The development of information technology has allowed constructing a plethora of quality indicators, mostly process measures of quality and in some cases health outcomes. These have been used both for public reporting, to help patients choose providers, but also for incentive schemes that directly pay for quality. P4P schemes are attractive but raise new issues, such as they might divert provider attention and unincentivized dimensions of quality might suffer as a result.
Pharmaceutical expenditure accounts for approximately 20% of healthcare expenditure across the Organisation for Economic Cooperation and Development (OECD) countries. Pharmaceutical products are regulated in all major global markets primarily to ensure product quality but also to regulate the reimbursed prices of insurance companies and central purchasing authorities that dominate this sector. Price regulation is justified as patent protection, which acts as an incentive to invest in R&D given the difficulties in appropriating the returns to such activity, creates monopoly rights to suppliers. Price regulation does itself reduce the ability of producers’ to recapture the substantial R&D investment costs incurred. Traditional price regulation through Ramsey pricing and yardstick competition is not efficient given the distortionary impact of insurance holdings, which are extensive in this sector and the inherent uncertainties that characterize Research and Development (R&D) activity. A range of other pricing regulations aimed at establishing pharmaceutical reimbursement that covers both dynamic efficiency (tied to R&D incentives) and static efficiency (tied to reducing monopoly rents) have been suggested. These range from cost-plus pricing, to internal and external reference pricing, rate-of-return pricing and, most recently value-based (essential health benefit maximization) pricing. Reimbursed prices reflecting value based pricing are, in some countries, associated with clinical treatment guidelines and cost-effectiveness analysis. Some countries are also requiring or allowing post-launch price regulation thorough a range of patient access agreements based on predefined population health targets and/or financial incentives. There is no simple, single solution to the determination of dynamic and static efficiency in this sector given the uncertainty associated with innovation, the large monopoly interests in the area, the distortionary impact of health insurance and the informational asymmetries that exist across providers and purchasers.
The concept of soft budget constraint, describes a situation where a decision-maker finds it impossible to keep an agent to a fixed budget. In healthcare it may refer to a (nonprofit) hospital that overspends, or to a lower government level that does not balance its accounts. The existence of a soft budget constraint may represent an optimal policy from the regulator point of view only in specific settings. In general, its presence may allow for strategic behavior that changes considerably its nature and its desirability. In this article, soft budget constraint will be analyzed along two lines: from a market perspective and from a fiscal federalism perspective.
The creation of an internal market for healthcare has made hospitals with different objectives and constraints compete together. The literature does not agree on the effects of competition on healthcare or on which type of organizations should compete. Public hospitals are often seen as less efficient providers, but they are also intrinsically motivated and/or altruistic. Competition for quality in a market where costs are sunk and competitors have asymmetric objectives may produce regulatory failures; for this reason, it might be optimal to implement soft budget constraint rules to public hospitals even at the risk of perverse effects. Several authors have attempted to estimate the presence of soft budget constraint, showing that they derive from different strategic behaviors and lead to quite different outcomes.
The reforms that have reshaped public healthcare systems across Europe have often been accompanied by a process of devolution; in some countries it has often been accompanied by widespread soft budget constraint policies. Medicaid expenditure in the United States is becoming a serious concern for the Federal Government and the evidence from other states is not reassuring. Several explanations have been proposed: (a) local governments may use spillovers to induce neighbors to pay for their local public goods; (b) size matters: if the local authority is sufficiently big, the center will bail it out; equalization grants and fiscal competition may be responsible for the rise of soft budget constraint policies. Soft budget policies may also derive from strategic agreements among lower tiers, or as a consequence of fiscal imbalances. In this context the optimal use of soft budget constraint as a policy instrument may not be desirable.
Joanna Coast and Manuela De Allegri
Qualitative methods are being used increasingly by health economists, but most health economists are not trained in these methods and may need to develop expertise in this area. This article discusses important issues of ontology, epistemology, and research design, before addressing the key issues of sampling, data collection, and data analysis in qualitative research. Understanding differences in the purpose of sampling between qualitative and quantitative methods is important for health economists, and the key notion of purposeful sampling is described. The section on data collection covers in-depth and semistructured interviews, focus-group discussions, and observation. Methods for data analysis are then discussed, with a particular focus on the use of inductive methods that are appropriate for economic purposes. Presentation and publication are briefly considered, before three areas that have seen substantial use of qualitative methods are explored: attribute development for discrete choice experiment, priority-setting research, and health financing initiatives.
Matteo Lippi Bruni, Irene Mammi, and Rossella Verzulli
In developed countries, the role of public authorities as financing bodies and regulators of the long-term care sector is pervasive and calls for well-planned and informed policy actions. Poor quality in nursing homes has been a recurrent concern at least since the 1980s and has triggered a heated policy and scholarly debate. The economic literature on nursing home quality has thoroughly investigated the impact of regulatory interventions and of market characteristics on an array of input-, process-, and outcome-based quality measures. Most existing studies refer to the U.S. context, even though important insights can be drawn also from the smaller set of works that covers European countries.
The major contribution of health economics to the empirical analysis of the nursing home industry is represented by the introduction of important methodological advances applying rigorous policy evaluation techniques with the purpose of properly identifying the causal effects of interest. In addition, the increased availability of rich datasets covering either process or outcome measures has allowed to investigate changes in nursing home quality properly accounting for its multidimensional features.
The use of up-to-date econometric methods that, in most cases, exploit policy shocks and longitudinal data has given researchers the possibility to achieve a causal identification and an accurate quantification of the impact of a wide range of policy initiatives, including the introduction of nurse staffing thresholds, price regulation, and public reporting of quality indicators. This has helped to counteract part of the contradictory evidence highlighted by the strand of works based on more descriptive evidence. Possible lines for future research can be identified in further exploration of the consequences of policy interventions in terms of equity and accessibility to nursing home care.
Ana Balsa and Carlos Díaz
Health behaviors are a major source of morbidity and mortality in the developed and much of the developing world. The social nature of many of these behaviors, such as eating or using alcohol, and the normative connotations that accompany others (i.e., sexual behavior, illegal drug use) make them quite susceptible to peer influence. This chapter assesses the role of social interactions in the determination of health behaviors. It highlights the methodological progress of the past two decades in addressing the multiple challenges inherent in the estimation of peer effects, and notes methodological issues that still need to be confronted. A comprehensive review of the economics empirical literature—mostly for developed countries—shows strong and robust peer effects across a wide set of health behaviors, including alcohol use, body weight, food intake, body fitness, teen pregnancy, and sexual behaviors. The evidence is mixed when assessing tobacco use, illicit drug use, and mental health. The article also explores the as yet incipient literature on the mechanisms behind peer influence and on new developments in the study of social networks that are shedding light on the dynamics of social influence. There is suggestive evidence that social norms and social conformism lie behind peer effects in substance use, obesity, and teen pregnancy, while social learning has been pointed out as a channel behind fertility decisions, mental health utilization, and uptake of medication. Future research needs to deepen the understanding of the mechanisms behind peer influence in health behaviors in order to design more targeted welfare-enhancing policies.
Elisa Tosetti, Rita Santos, Francesco Moscone, and Giuseppe Arbia
The spatial dimension of supply and demand factors is a very important feature of healthcare systems. Differences in health and behavior across individuals are due not only to personal characteristics but also to external forces, such as contextual factors, social interaction processes, and global health shocks. These factors are responsible for various forms of spatial patterns and correlation often observed in the data, which are desirable to include in health econometrics models.
This article describes a set of exploratory techniques and econometric methods to visualize, summarize, test, and model spatial patterns of health economics phenomena, showing their scientific and policy power when addressing health economics issues characterized by a strong spatial dimension. Exploring and modeling the spatial dimension of the two-sided healthcare provision may help reduce inequalities in access to healthcare services and support policymakers in the design of financially sustainable healthcare systems.
Alessandro Casini and Pierre Perron
This article covers methodological issues related to estimation, testing, and computation for models involving structural changes. Our aim is to review developments as they relate to econometric applications based on linear models. Substantial advances have been made to cover models at a level of generality that allow a host of interesting practical applications. These include models with general stationary regressors and errors that can exhibit temporal dependence and heteroskedasticity, models with trending variables and possible unit roots and cointegrated models, among others. Advances have been made pertaining to computational aspects of constructing estimates, their limit distributions, tests for structural changes, and methods to determine the number of changes present. A variety of topics are covered including recent developments: testing for common breaks, models with endogenous regressors (emphasizing that simply using least-squares is preferable over instrumental variables methods), quantile regressions, methods based on Lasso, panel data models, testing for changes in forecast accuracy, factors models, and methods of inference based on a continuous records asymptotic framework. Our focus is on the so-called off-line methods whereby one wants to retrospectively test for breaks in a given sample of data and form confidence intervals about the break dates. The aim is to provide the readers with an overview of methods that are of direct use in practice as opposed to issues mostly of theoretical interest.
Albert A. Okunade and Ahmad Reshad Osmani
Healthcare cost encompasses expenditures on the totality of scarce resources (implicit and explicit) given up (or allocated) to produce healthcare goods (e.g., drugs and medical devices) and services (e.g., hospital care and physician office services are major components). Healthcare cost accounting components (sources and uses of funds) tend to differ but can be similar enough across most of the world countries. The healthcare cost concept usually differs for consumers, politicians and health policy decision-makers, health insurers, employers, and the government. All else given, inefficient healthcare production implies higher economic cost and lower productivity of the resources deployed in the process. Healthcare productivity varies across health systems of the world countries, the production technologies used, regulatory instruments, and institutional settings. Healthcare production often involves some specific (e.g., drugs and medical devices, information and communication technologies) or general technology for diagnosing, treating, or curing diseases in order to improve or restore human health conditions.
In the last half century, the different healthcare systems of the world countries have undergone fundamental transformations in the structural designs, institutional regulations, and socio-economic and demographic dimensions. The nations have allocated a rising share of total economic resources or incomes (i.e., Gross National Product, or GDP) to the healthcare sector and are consequently enjoying substantial increases in population health status and life expectancies. There are complex and interacting linkages among escalating healthcare costs, longer life expectancies, technological progress (or “the march of science”), and sectoral productivities in the health services sectors of the advanced economies. Healthcare policy debates often concentrate on cost-containment strategies and search for improved efficient resource allocation and equitable distribution of the sector’s outputs. Consequently, this contribution is a broad review of the body of literature on technological progress, productivity, and cost: three important dimensions of the evolving modern healthcare systems. It provides a logical integration of three strands of work linking healthcare cost to technology and research evidence on sectoral productivity measurements. Finally, some important aspects of the existing study limitations are noted to motivate new research directions for future investigations to explore in the growing health sector economies.
The rise in obesity and other food-related chronic diseases has prompted public-health officials of local communities, national governments, and international institutions to pay attention to the regulation of food supply and consumer behavior. A wide range of policy interventions has been proposed and tested since the early 21st century in various countries. The most prominent are food taxation, health education, nutritional labeling, behavioral interventions at point-of-decision, advertising, and regulations of food quality and trade. While the standard neoclassical approach to consumer rationality provides limited arguments in favor of public regulations, the recent development of behavioral economics research extends the scope of regulation to many marketing practices of the food industry. In addition, behavioral economics provides arguments in favor of taxation, easy-to-use front-of-pack labels, and the use of nudges for altering consumer choices. A selective but careful review of the empirical literature on taxation, labeling, and nudges suggests that a policy mixing these tools may produce some health benefits. More specifically, soft-drink taxation, front-of-pack labeling policies, regulations of marketing practices, and eating nudges based on affect or behavior manipulations are often effective methods for reducing unhealthy eating.
The economic research faces important challenges. First, the lack of a proper control group and exogenous sources of variations in policy variables make evaluation very difficult. Identification is challenging as well, with data covering short time periods over which markets are observed around slowly moving equilibrium. In addition, truly exogenous supply or demand shocks are rare events. Second, structural models of consumer choices cannot provide accurate assessment of the welfare benefits of public policies because they consider perfectly rational agents and often ignore the dynamic aspects of food decisions, especially consumer concerns over health. Being able to obtain better welfare evaluation of policies is a priority. Third, there is a lack of research on the food industry response to public policies. Some studies implement empirical industrial organization models to infer the industry strategic reactions from market data. A fruitful avenue is to extend this approach to analyze other key dimensions of industrial strategies, especially decisions regarding the nutritional quality of food. Finally, the implementation of nutritional policies yields systemic consequences that may be underestimated. They give rise to conflicts between public health and trade objectives and alter the business models of the food sector. This may greatly limit the external validity of ex-ante empirical approaches. Future works may benefit from household-, firm-, and product-level data collected in rapidly developing economies where food markets are characterized by rapid transitions, the supply is often more volatile, and exogenous shocks occur more frequently.
Fabrice Etilé and Lisa Oberlander
In the last several decades obesity rates have risen significantly. In 2014, 10.8% and 14.9% of the world’s men and women, respectively, were obese as compared with 3.2% and 6.4% in 1975. The obesity “epidemic” has spread from high-income countries to emerging and developing ones in every region of the world. The rising obesity rates are essentially explained by a rise in total calorie intake associated with long-term global changes in the food supply. Food has become more abundant, available, and cheaper, but food affluence is associated with profound changes in the nutritional quality of supply. While calories have become richer in fats, sugar, and sodium, they are now lower in fiber. The nutrition transition from starvation to abundance and high-fat/sugar/salt food is thus accompanied by an epidemiological transition from infectious diseases and premature death to chronic diseases and longer lives. Food-related chronic diseases have important economic consequences in terms of human capital and medical care costs borne by public and private insurances and health systems.
Technological innovations, trade globalization, and retailing expansion are associated with these substantial changes in the quantity and quality of food supply and diet in developed as well as in emerging and rapidly growing economies. Food variety has significantly increased due to innovations in the food production process. Raw food is broken down to obtain elementary substances that are subsequently assembled for producing final food products. This new approach, as well as improvements in cold chain and packaging, has contributed to a globalization of food chains and spurred an increase of trade in food products, which, jointly with foreign direct investments, alters the domestic food supply. Finally, technological advancements have also favored the emergence of large supermarkets and retailers, which have transformed the industrial organization of consumer markets.
How do these developments affect population diets and diet-related diseases? Identifying the contribution of supply factors to long-term changes in diet and obesity is important because it can help to design innovative, effective, and evidence-based policies, such as regulations on trade, retailing, and quality or incentives for product reformulation. Yet this requires a correct evaluation of the importance and causal effects of supply-side factors on the obesity pandemic. Among others, the economic literature analyzes the effect of changes in food prices, food availability, trade, and marketing on the nutrition and epidemiological transitions. There is a lack of causal robust evidence on their long-term effects. The empirical identification of causal effects is de facto challenging because the dynamics of food supply is partly driven by demand-side factors and dynamics, like a growing female labor force, habit formation, and the social dynamics of preferences.
There are several important limitations to the literature from the early 21st century. Existing studies cover mostly well-developed countries, use static economic and econometric specifications, and employ data that cover short periods of time unmarked by profound shifts in food supply. In contrast, empirical research on the long-term dynamics of consumer behavior is much more limited, and comparative studies across diverse cultural and institutional backgrounds are almost nonexistent. Studies on consumers in emerging countries could exploit the rapid time changes and large spatial heterogeneity, both to identify the causal impacts of shocks on supply factors and to document how local culture and institutions shape diet and nutritional outcomes.
Marjon van der Pol and Alastair Irvine
The interest in eliciting time preferences for health has increased rapidly since the early 1990s. It has two main sources: a concern over the appropriate methods for taking timing into account in economics evaluations, and a desire to obtain a better understanding of individual health and healthcare behaviors. The literature on empirical time preferences for health has developed innovative elicitation methods in response to specific challenges that are due to the special nature of health. The health domain has also shown a willingness to explore a wider range of underlying models compared to the monetary domain. Consideration of time preferences for health raises a number of questions. Are time preferences for health similar to those for money? What are the additional challenges when measuring time preferences for health? How do individuals in time preference for health experiments make decisions? Is it possible or necessary to incentivize time preference for health experiments?
Henrik Andersson, Arne Risa Hole, and Mikael Svensson
Many public policies and individual actions have consequences for population health. To understand whether a (costly) policy undertaken to improve population health is a wise use of resources, analysts can use economic evaluation methods to assess the costs and benefits. To do this, it is necessary to evaluate the costs and benefits using the same metric, and for convenience, a monetary measure is commonly used. It is well established that money measures of a reduction in health risks can be theoretically derived using the willingness-to-pay concept. However, because a market price for health risks is not available, analysts have to rely on analytical techniques to estimate the willingness to pay using revealed- or stated-preference methods. Revealed-preference methods infer willingness to pay based on individuals’ actual behavior in markets related to health risks, and they include such approaches as hedonic pricing techniques. Stated-preference methods use a hypothetical market scenario in which respondents make trade-offs between wealth and health risks. Using, for example, a random utility framework, it is possible to directly estimate individuals’ willingness to pay by analyzing the trade-offs they make in the hypothetical scenario. Stated-preference methods are commonly applied using contingent valuation or discrete choice experiment techniques. Despite criticism and the shortcomings of both the revealed- and stated-preference methods, substantial progress has been made since the 1990s in using both approaches to estimate the willingness to pay for health-risk reductions.
Marisa Miraldo, Katharina Hauck, Antoine Vernet, and Ana Wheelock
Major medical innovations have greatly increased the efficacy of treatments, improved patient outcomes, and often reduced the cost of medical care. However, innovations do not diffuse uniformly across and within health systems. Due to the high complexity of medical treatment decisions, variations in clinical practice are inherent to healthcare delivery, regardless of technological advances, new ways of working, funding, and burden of disease. In this chapter we conduct a narrative literature review to identify and discuss peer-reviewed articles presenting a theoretical framework or empirical evidence of the factors associated with the adoption of innovation and clinical practice.
We find that variation in innovation adoption and medical practice is associated with multiple factors. First, patients’ characteristics, including medical needs and genetic factors, can crucially affect clinical outcomes and the efficacy of treatments. Moreover, differences in patients’ preferences can be an important source of variation. Medical treatments may need to take such patient characteristics into account if they are to deliver optimal outcomes, and consequently, resulting practice variations should be considered warranted and in the best interests of patients. However, socioeconomic or demographic characteristics, such as ethnicity, income, or gender are often not considered legitimate grounds for differential treatment. Second, physician characteristics—such as socioeconomic profile, training, and work-related characteristics—are equally an influential component of practice variation. In particular, so-called “practice style” and physicians’ attitudes toward risk and innovation adoption are considered a major source of practice variation, but have proven difficult to investigate empirically. Lastly, features of healthcare systems—notably, public coverage of healthcare expenditure, cost-based reimbursement of providers, and service-delivery organization, are generally associated with higher utilization rates and adoption of innovation.
Research shows some successful strategies aimed at reducing variation in medical decision-making, such as the use of decision aids, data feedback, benchmarking, clinical practice guidelines, blinded report cards, and pay for performance. But despite these advances, there is uneven diffusion of new technologies and procedures, with potentially severe adverse efficiency and equity implications.