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Complexity of the problem of choosing among uncertain acts is a salient feature of many of the environments in which departures from expected utility theory are observed. I study a class of Generalized Simple Bounds preferences in which acts that are complex from the perspective of the decision maker are bracketed by "simple" acts to which they are related by statewise dominance. I then study a refinement of the model in which the size of the partition with respect to which an act is measurable arises endogenously as a measure of subjective complexity. Finally, I consider choice behavior characterized by a "cautious completion" of Simple Bounds preferences, and discuss the relationship between this model and models of ambiguity aversion. I develop general comparative statics results, and explore applications to portfolio choice and insurance choice. • Problems of choice problems under uncertainty are complex. • From behavioral axioms, I characterize the set of acts that are well-understood. • Decision makers use acts they understand well to bracket those they do not. • The model is tractable, and admits rich comparative statics. • The model helps explain observed choice patterns in applications. [ABSTRACT FROM AUTHOR]

A central tenet of behavioral economics is that the axioms producing expected utility maximization by consumers are too strong to be descriptive of rational behavior. The existing theory of monetary services aggregation under risk assume expected utility maximization. We extend those results to uncertainty under weaker axiomatic assumptions by using Choquet expectations. Choquet integration reduces to Riemann integration as a special case under the stronger assumption of additive probability measure, not accepted in the literature on behavioral economics. Our theoretical results on monetary services aggregation are generalizations of prior results, nested as special cases of our results under stronger behavioral assumptions. [ABSTRACT FROM AUTHOR]

We report the results of an experiment eliciting individuals' attitudes toward risk and model uncertainty. Using a joint elicitation procedure, we then precisely quantify the strength of individuals' attitude toward ambiguity in the context of the smooth model and characterize its main properties. Our results provide empirical evidence of decreasing absolute ambiguity aversion (DAAA) and constant relative ambiguity aversion (CRAA). These results shed new light on the way ambiguity attitudes may affect important decisions, such as the choice of health insurance policies or the optimal investment strategy in the face of climate change. [ABSTRACT FROM AUTHOR]

• Subjects respond in a pessimistic/averse manner to the uncertainty surrounding climate change and climate change catastrophes, with 67% of subjects successfully purchasing the climate change insurance in the base treatment. • When subjects have more information about the growing frequency of such events, 79% successfully ensure themselves. • A lemons problem may arise with only high-risk individuals/regions subscribing towards climate change insurance and suggests that government intervention may be required to ensure market failures do not arise. • When the strategic uncertainty of coordination with another person is removed, 81% of subjects are successful in buying the insurance. • An indirect intervention in the form of a nudge was unsuccessful, with only 58% of subjects successfully buying the insurance. This paper attempts to study how individuals respond to the availability of an insurance that would safeguard their interests if a climate change catastrophe occurred. If such an insurance is available to them, do individuals insure themselves sufficiently? Further, the study investigates if information regarding the past occurrence of the catastrophic event leads to an increase in insurance subscriptions and/or the emergence of a lemons market. Finally, policy implications are investigated - Can an indirect intervention in the form of a "nudge" ensure a better outcome? [ABSTRACT FROM AUTHOR]

• We derive the value of travel time information in very general setting. • Value increases with information quality. • Predictable travel time variability may be costly. • Examples show analytic calculation of value of travel time information. • Results facilitate design and analysis of information policies. In this paper, we derive the value of a signal obtained by a traveller prior to the choice of departure time. The signal does not have to be a perfect prediction of the travel time. It is sufficient that it carries information about the travel time. The traveller may then consider the distribution of travel time conditional on the signal to increase her expected utility by making a better informed choice of departure time. We show that a signal always increases the expected utility compared to the situation without any signal. For a broad class of signals, the expected utility is monotone with respect to signal strength. Furthermore, we demonstrate that even perfect travel time information does not necessarily eliminate the cost of travel time variability and we establish necessary and sufficient conditions for when it does. We find that the predictable part of travel time variability may or may not be costly, depending on the shape of the traveller's scheduling utility at the origin of the trip. Using estimates of scheduling preferences from the literature, we show that the cost of predictable travel time variability may constitute a substantial part of the total cost of travel time variability. In a particular case of scheduling preferences, travel time distribution and noise distribution, we establish an analytic relationship between the strength of the signal and the expected utility of the trip and evaluate the marginal cost of signal weakness. This knowledge may facilitate design and cost-benefit analysis of traveller information systems and policies decreasing travel time variability. [ABSTRACT FROM AUTHOR]

The predictive power of cumulative prospect theory and expected utility theory is typically compared using decisions from description, where lotteries' outcome values and probabilities are explicitly stated. In decisions from experience, individuals sample (in the sampling paradigm without cost) from the return distributions to learn outcome values and their relative frequencies; here cumulative prospect theory and expected utility theory require the calculation of probabilities from experience. Individuals, however, may be more attuned to the experienced moments of outcome distributions, rather than the probabilities. We therefore test the mean-variance-skewness model, and retrieve the proportion of expected utility theory (over income), cumulative prospect theory, and mean-variance-skewness populations using a latent-class hierarchical Bayesian model across six large datasets. For simple lotteries (with 1-2 outcomes), we find a mixture of cumulative prospect theory and mean-variance-skewness populations in decisions from both description and experience. For more complex lotteries (with 2-3 outcomes), all participants are classified as cumulative prospect theory types in decisions from description, but as mean-variance-skewness types in decisions from experience. This suggests that in decisions from experience with more complex return distributions, preferences for skewness are more predictive than nonlinear probability weighting. [ABSTRACT FROM AUTHOR]

This paper studies n -player games where players' beliefs about their opponents' behavior are capacities (fuzzy measures, non-additive probabilities). The concept of an equilibrium under uncertainty was introduced by J. Dow and S. Werlang [5] for two players and was extended to n -player games by J. Eichberger and D. Kelsey [8] . Expected utility was expressed by Choquet integral. We consider the concept of an equilibrium under uncertainty in this paper but with expected utility expressed by Sugeno integral. Existence of such an equilibrium expressed by possibility (or necessity) capacities is demonstrated using some abstract non-linear convexity on the space of capacities. [ABSTRACT FROM AUTHOR]

In many parts of the world, conservation successes or global anthropogenic changes have led to increasing native species populations that then compete with human resource use. In the Orkney Islands, Scotland, a 60-fold increase in Greylag Goose Anser anser numbers over 24 years has led to agricultural damages and culling attempts that have failed to prevent population increase. To address uncertainty about why populations have increased, we combined empirical modelling of possible drivers of Greylag Goose population change with expert-elicited benefits of alternative management actions to identify whether to learn versus act immediately to reduce damages by geese. We built linear mixed-effects models relating annual goose densities on farms to land-use and environmental covariates and estimated AICc model weights to indicate relative support for six hypotheses of change. We elicited from experts the expected likelihood that one of six actions would achieve an objective of halting goose population growth, given each hypothesis for population change. Model weights and expected effects of actions were combined in Value of Information analysis (VoI) to quantify the utility of resolving uncertainty in each hypothesis through adaptive management and monitoring. The action with the highest expected value under existing uncertainty was to increase the extent of low quality habitats, whereas assuming equal hypothesis weights changed the best action to culling. VoI analysis showed that the value of learning to resolve uncertainty in any individual hypothesis for goose population change was low, due to high support for a single hypothesis of change. Our study demonstrates a two-step framework that learns about the most likely drivers of change for an over-abundant species, and uses this knowledge to weight the utility of alternative management actions. Our approach helps inform which strategies might best be implemented to resolve uncertainty when there are competing hypotheses for change and competing management choices. [ABSTRACT FROM AUTHOR]

Risk is caused by the uncertainty of state of nature and a decision maker's selection, and the result may appear to be an unfavorable outcome. Therefore, a decision maker wants to maximize an expected return with minimal risk exposures. In this paper, we propose an expected utility and uncertainty risk (EU-UR) model based on the reference prior, which extends the classical decision model under uncertainty. The EU-UR model is made by making a compromise between measures of expected utility and uncertainty. The model is empirically validated by applying to the Levy's case and the Allais paradox. [ABSTRACT FROM AUTHOR]

This article examines the role of risk aversion on the sustainable management of mixed fisheries. We consider a bio-economic model of multiple species harvested by a single fleet with uncertain costs of effort. We assume that the regulatory agency aims at reaching MMEY (Multispecies Maximum Economic Yield) by maximizing the expected utility of total profits, where the utility function captures risk aversion. We show analytically that such a risk-averse MMEY mitigates the risk of biological and economic overexploitation of the different species and thus of biodiversity loss. However excessively high risk aversion also may also lessen food production at MMEY. Thus, risk aversion implies a trade-off between different bio-economic goals. These findings are illustrated with the case study of the Australian South East Fishery, where intermediate risk aversion levels allow for balanced bio-economic management objectives, therefore fostering sustainability. [ABSTRACT FROM AUTHOR]

Abstract: We add some elements of prospect theory to an analytically tractable version of Lucas''s “islands” model and show that the inclusion of reference dependence, declining sensitivity and loss aversion into the agents’ utility function leads to four main results. First, the presence of behavioral elements negatively affects the natural level of output. Second, loss aversion reduces output variance. Third, the expected utility of a representative agent is generally lower than that obtained when loss aversion is absent. Fourth, the presence of loss aversion eliminates the paradoxical increase in expected utility that may be generated, in the standard model, by an increase in monetary policy uncertainty. [Copyright &y& Elsevier]

Abstract: Recent changes in the assessment and management of risks has had the effect that greater importance has been placed on relationships between individuals and within groups to inform decision making. In this paper, we provide the theoretical underpinning for an expected utility approach to decision-making. The approach, which is presented using established evidence support logic (TESLA™), integrating the expected utilities in the forming of group decisions. The rationale and basis are described and illustrated through a hypothetical decision context of options for the disposal of animal carcasses that accumulate during disease outbreaks. The approach forms the basis for exploring the richness of risk-based decisions, and representing individual beliefs about the sufficiency of evidence they may advance in support of hypotheses. [Copyright &y& Elsevier]

Abstract: We consider a decision maker facing uncertainty which behaves as a subjective expected utility maximizer. The value of information is traditionally captured as a greater expected utility the decision maker can achieve by selecting a best strategy as information arrives. We deal with the limit process of being better informed, and introduce an information density function depending solely on the states that gives an exact least upper bound to being more informed. This information density function is given by a Radon–Nikodym-type theorem for set functions and is explicitly computed for the countable case. [Copyright &y& Elsevier]

Abstract: Although the expected effects of environmental policies and interventions are rarely known with certainty, stated preference surveys rarely elicit preferences over uncertain environmental outcomes. This article presents empirical results challenging the view that ignoring such uncertainty during preference elicitation is of no consequence so long as people only care about final environmental states. We show that measured preferences for final environmental states, water quality in this case, depend on whether people choose between final states or between lotteries over final states. In contrast to the typical finding for monetary lotteries, we find significant under-weighting of low probability events related to water quality. [Copyright &y& Elsevier]