Choice of health insurance plans has become a key element of many healthcare systems around the world along with a general expansion of patient choice under the label of “Consumer-Directed Healthcare.” Allowing consumers to choose their insurance plan was commonly associated with the aim of enhancing competition between insurers and thus to contribute to the efficient delivery of healthcare. However, the evidence is accruing that consumers have difficulties in making health insurance decisions in their best interest. For example, many consumers choose plans with which they spend more in terms of premiums and out-of-pocket costs than in other available options. This has consequences for the individual consumer’s budget as well as for the functioning of the insurance market. The literature puts forward several possible reasons for consumers’ difficulties in making health insurance choices in their best interest. First, consumers may not have a sufficient level of knowledge of insurance products; for example, they might not understand insurance terminology. Second, the environment or architecture in which consumers make their decision may be too complicated. Health insurance products vary in a large number of features that consumers have to evaluate when comparing options, introducing search or hassle costs. Third, consumers may be prone to psychological biases and employ decision-making heuristics that impede good choices. For example, they might choose the plan with the cheapest premium, ignoring other important plan features that determine total cost, such as copayments. There is also evidence that consumer education programs, simplification of the choice environment, or introducing nudges such as setting smart defaults facilitate consumer decision making. Despite recent progress in our understanding of consumer choices in health insurance markets, important challenges remain. Evidence-based healthcare policy should be based on an evaluation of whether different interventions aimed at facilitating consumer choices result in welfare improvements. Ultimately, this requires measuring consumer utility, an issue that is vividly debated in the literature. Furthermore, welfare calculations necessitate an understanding of how interventions will affect the supply of health insurance, including supply reactions to changes in demand. This depends on the specific regulatory setting and characteristics of the specific market.
Joachim Winter and Amelie Wuppermann
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.
Denzil G. Fiebig and Hong Il Yoo
Stated preference methods are used to collect individual-level data on what respondents say they would do when faced with a hypothetical but realistic situation. The hypothetical nature of the data has long been a source of concern among researchers as such data stand in contrast to revealed preference data, which record the choices made by individuals in actual market situations. But there is considerable support for stated preference methods as they are a cost-effective means of generating data that can be specifically tailored to a research question and, in some cases, such as gauging preferences for a new product or non-market good, there may be no practical alternative source of data. While stated preference data come in many forms, the primary focus in this article is data generated by discrete choice experiments, and thus the econometric methods will be those associated with modeling binary and multinomial choices with panel data.
Ehsan U. Choudhri
Exchange rates often display sudden and large changes. There is considerable interest in examining how these changes affect prices, especially import and consumer prices. Exchange rate pass-through measures the responsiveness of the price of a basket of goods to changes in the exchange rate and is defined as the elasticity of the price of the basket (expressed in home currency) with respect to the exchange rate (defined as the price of foreign currency). The pass-through estimates vary across product groups, countries, and time periods, but a general finding is that pass-through tends to be significantly less than one, which implies that prices do not fully respond to a foreign currency appreciation. Pass-through to export prices tends to be smaller than pass-through to import prices. Pass-through to consumer prices is lower than both import and export price pass-through and is generally very small. One explanation of pass-through evidence focuses on the role of nominal rigidities (infrequent changes in prices set in home or foreign currency). Another explanation emphasizes the importance of markup variation in response to exchange rate changes. In models with nominal rigidities, one important issue is whether exporting firms set prices in their country’s currency (producer’s currency) or importing country’s currency (consumer’s currency). If prices are sticky in producer’s currency, flexible exchange rates are preferable as they allow for desirable relative price adjustment. On the other hand, if prices are sticky in consumer’s currency, exchange rate flexibility is not as helpful in adjusting prices and fixed exchange rates are superior. The standard model where markup is constant and all firms (at home and abroad) use either producer or consumer currency pricing is not consistent with typical estimates of pass-through to import and export prices. To explain this evidence, the standard model needs to be modified to allow for variable markup and/or a hybrid model of currency choice where some firms set prices in producer’s and others in consumer’s currency. In the case of the hybrid model, the welfare difference between fixed and flexible exchange rates is not as stark as in the pure cases of currency choice and is likely to be small. Another issue of much interest is whether inflationary environment can affect pass-through, especially to consumer prices. Inflationary environment can influence pass-through to import and consumer prices through several channels, such as persistence of costs and frequency of price change. Empirical evidence shows that pass-through to consumer prices is related to the level and variability of inflation across countries and time periods and is lower in an environment with low and stable inflation. This evidence suggests that a monetary policy regime that targets low inflation will produce a low pass-through environment, which would dampen the price effects of exchange rate changes.
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.
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.
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.
Keith N. Hylton
Criminal law consists of substantive and procedural parts. Substantive law is the set of rules defining conduct that violates the law. Procedural criminal law is the set of rules regulating the process of punishment. Substantive rules apply mostly to individual actors, and procedural rules apply to public enforcement agencies and adjudicators. Economic theory of criminal law consists of normative and positive parts. Normative economic theory, which began with writings by Beccaria and Bentham, aims to recommend an ideal criminal punishment scheme. Positive economic theory, which appeared later in writings by Holmes and Posner, aims to justify and to better understand the criminal law rules that exist. Since the purpose of criminal law is to deter socially undesirable conduct, economic theory, which emphasizes incentives, would appear to be an important perspective from which to examine criminal law. Positive economic theory, applied to substantive criminal law, seeks to explain and to justify criminal law doctrine in economic terms—that is, in terms that emphasize the incentive effects created by the law. The positive economic theory of criminal law literature can be divided into three phases: Classical deterrence theory, neoclassical deterrence, and modern synthesis. The modern synthesis provides a rationale for fundamental criminal law doctrines and also more puzzling portions of the law such as the doctrines of intent and necessity. Positive economic theory also provides a rationale for the allocation of enforcement responsibilities.