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Article

The Economics of Identity and Conflict  

Subhasish M. Chowdhury

Conflicts are a ubiquitous part of our life. One of the main reasons behind the initiation and escalation of conflict is the identity, or the sense of self, of the engaged parties. It is hence not surprising that there is a consistent area of academic literature that focuses on identity, conflict, and their interaction. This area models conflicts as contests and focuses on the theoretical, experimental, and empirical literature from economics, political science, and psychology. The theoretical literature investigates the behavioral aspects—such as preference and beliefs—to explain the reasons for and the effects of identity on human behavior. The theoretical literature also analyzes issues such as identity-dependent externality, endogenous choice of joining a group, and so on. The applied literature consists of laboratory and field experiments as well as empirical studies from the field. The experimental studies find that the salience of an identity can increase conflict in a field setting. Laboratory experiments show that whereas real identity indeed increases conflict, a mere classification does not do so. It is also observed that priming a majority–minority identity affects the conflict behavior of the majority, but not of the minority. Further investigations explain these results in terms of parochial altruism. The empirical literature in this area focuses on the various measures of identity, identity distribution, and other economic variables on conflict behavior. Religious polarization can explain conflict behavior better than linguistic differences. Moreover, polarization is a more significant determinants of conflict when the winners of the conflict enjoy a public good reward; but fractionalization is a better determinant when the winners enjoy a private good reward. As a whole, this area of literature is still emerging, and the theoretical literature can be extended to various avenues such as sabotage, affirmative action, intra-group conflict, and endogenous group formation. For empirical and experimental research, exploring new conflict resolution mechanisms, endogeneity between identity and conflict, and evaluating biological mechanisms for identity-related conflict will be of interest.

Article

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.

Article

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.

Article

Improving on Simple Majority Voting by Alternative Voting Mechanisms  

Jacob K. Goeree, Philippos Louis, and Jingjing Zhang

Majority voting is the predominant mechanism for collective decision making. It is used in a broad range of applications, spanning from national referenda to small group decision making. It is simple, transparent, and induces voters to vote sincerely. However, it is increasingly recognized that it has some weaknesses. First of all, majority voting may lead to inefficient outcomes. This happens because it does not allow voters to express the intensity of their preferences. As a result, an indifferent majority may win over an intense minority. In addition, majority voting suffers from the “tyranny of the majority,” i.e., the risk of repeatedly excluding minority groups from representation. A final drawback is the “winner-take-all” nature of majority voting, i.e., it offers no compensation for losing voters. Economists have recently proposed various alternative mechanisms that aim to produce more efficient and more equitable outcomes. These can be classified into three different approaches. With storable votes, voters allocate a budget of votes across several issues. Under vote trading, voters can exchange votes for money. Under linear voting or quadratic voting, voters can buy votes at a linear or quadratic cost respectively. The properties of different alternative mechanisms can be characterized using theoretical modeling and game theoretic analysis. Lab experiments are used to test theoretical predictions and evaluate their fitness for actual use in applications. Overall, these alternative mechanisms hold the promise to improve on majority voting but have their own shortcomings. Additional theoretical analysis and empirical testing is needed to produce a mechanism that robustly delivers efficient and equitable outcomes.

Article

The Behavioral Consequences of Conflict Exposure on Risk Preferences  

Enrique Fatas, Nathaly Jiménez, Lina Restrepo-Plaza, and Gustavo Rincón

Violent conflict is a polyhedric phenomenon. Beyond the destruction of physical and human capital and the economic, political, and social costs war generates, there is an additional burden carried by victims: persistent changes in the way they make decisions. Exposure to violence generates changes in how individuals perceive other individuals from their group and other groups, how they discount the future, and how they assess and tolerate risk. The behavioral consequences of violence exposure can be documented using experiments in which participants make decisions in a controlled, incentive-compatible scenario. The external validity of experiments is reinforced when the studies are run in postconflict scenarios, for example, in Colombia, with real victims of conflict. The experimental tasks, therefore, may map risk attitudes among victims and nonvictims of the conflict who share a common background, and distinguish between different types of exposure (direct versus indirect) and different sources of violence (conflict-related versus criminal violence). The experimental evidence collected in Colombia is consistent with a long-lasting and substantial effect of conflict exposure on risk attitudes. Victims are more likely to take risks and less likely to make safe choices than nonvictims, controlling for demographic, socioeconomic, and attitudinal factors. The effect is significant only when the source of violence is conflict (exerted by guerrilla or paramilitary militias) and when violence is experienced directly by individuals. Indirect conflict exposure (suffered by close relatives) and criminal violence leave no significant mark on participants’ risk attitudes in the study.

Article

Happiness and Productivity in the Workplace  

Mahnaz Nazneen and Daniel Sgroi

Happiness has become an important concept in economics as a target for government policy at the national level. This is mirrored in an increasing understanding of the microeconomic effects of increased happiness. While correlational studies have for many years documented a relationship between individual-level happiness and productivity, more recent work provides causal evidence that a positive shock to happiness can boost productivity significantly. These studies include three strands of research. The first provides a number of longitudinal surveys that have generated evidence linking happiness to productivity but run the risk of confounding happiness with other related variables that may be driving the relationship. The second includes laboratory experiments that simulate a workplace under tightly controlled conditions, and this strand has established a clear relationship between positive happiness shocks and rises in productivity. The third involves examining experimental field data, which sacrifices the control of laboratory experiments but offers greater realism. However, there is still work to be done generalizing these findings to more complex work environments, especially those that involve cooperative and team-based tasks where increases in happiness may have other consequences.

Article

Behavioral Development Economics  

Karla Hoff and Allison Demeritt

Economics, like all behavioral sciences, incorporates premises about how people think. Behavioral economics emerged in reaction to the extreme assumption in neoclassical economics that agents have unbounded cognitive capacity and exogenous, fixed preferences. There have been two waves of behavioral economics, and both have enriched development economics. The first wave takes into account that cognitive capacity is bounded and that individuals in many situations act predictably irrationally: there are universal human biases. Behavioral development economics in this first wave has shown that low-cost interventions can be “small miracles” that increase productivity and well-being by making it easier for people to make the rational choice. The second wave of behavioral economics explicitly takes into account that humans are products of culture as well as nature. From their experience and exposure to communities, humans adopt beliefs that shape their perception, construals, and behavior. This second wave helps explain why long-run paths of economic development may diverge across countries with different histories. The second wave also suggests a new kind of intervention: Policies that give individuals new experiences or new role models may change their perceptions and preferences. New perceptions and preferences change behavior. This is a very different perspective than that of neoclassical economics, in which changing behavior requires ongoing interventions.

Article

Valuation of Health Risks  

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.

Article

Econometrics of Stated Preferences  

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.