Expected Utility Research Articles

Traumatic stress, active engagement and resilience in first responders and civilians in the outbreak of war.

Background: The outbreak of war in Israel on 7 October and the unique events of that day have presented unprecedented challenges to first responders (FRs), who are professionally trained to engage in providing assistance in such circumstances. Moreover, while research demonstrates the long-term psychological consequences of FRs, little is known regarding how FR's engagement in providing assistance relates to stress and resilience levels as events continue to unfold.Objective: The current study examined the relationship between traumatic stress symptoms (TSS) and resilience levels among FRs and controls during the first weeks of the Iron Swords war, while focusing on the moderating role of active engagement in providing assistance.Method: Data were collected during the first month of the Iron Swords war from 374 participants living in Southern Israel, of whom 77 (20.6%) were FRs. All participants filled out scales assessing TSS and resilience and provided relevant background information.Results: High TSS levels were associated with reduced resilience in FRs and non-FRs. Moreover, both the study group and active engagement were significant moderators for the TSS-resilience link, which was insignificant among FRs who provided assistance and for civilians who did not provide assistance. However, the TSS-resilience association remained significant for FRs who did not engage in providing assistance and for civilians who did.Conclusions: Our findings highlight the importance of examining the extent to which FRs act in line with their duties during times of adverse stress. Clinical interventions aimed towards FRs who did not engage in providing assistance are needed and should focus on the extent to which their moral values, beliefs and expectations are met, as these appear critical parameters in preserving resilience.

Western Safflower Contracting Strategies

AbstractSafflower grown in the western U.S. is often produced for birdseed mixes. Increasing demand for birdseed products, combined with regional drought, has shrunk western safflower availability. To satisfy the growing demand, processors may look to contracting strategies to incentivize production. We compare expected risk and corresponding certainty equivalents both from the processor and producer viewpoints under various contracting mechanisms and risk aversion levels. Results suggest that contracts containing a combination of lump sum acreage payments and fixed price performance payments would incentivize producer adoption of safflower while maintaining processor profitability and limiting the risk exposure of both parties.

Can Climate Shocks Make Vulnerable Subjects More Willing to Take Risks?

While economists in the past tended to assume that individual preferences, including risk preferences, are stable over time, a recent literature has developed and indicates that risk preferences respond to shocks, with mixed evidence on the direction of the responses. This paper utilizes a natural experiment with covariate (drought) and idiosyncratic shocks in combination with an independent field risk experiment. The risk experiment uses a Certainty Equivalent-Multiple Choice List approach and is played 1–2 years after the subjects were (to a varying degree) exposed to a covariate drought shock or idiosyncratic shocks for a sample of resource-poor young adults living in a risky semi-arid rural environment in Sub-Saharan Africa. The experimental approach facilitates a comprehensive assessment of shock effects on experimental risk premiums for risky prospects with varying probabilities of good and bad outcomes. The experiment also facilitates the estimation of the utility curvature in an Expected Utility (EU) model and, alternatively, separate estimation of probability weighting and utility curvature in three different Rank Dependent Utility models with a two-parameter Prelec probability weighting function. Our study is the first to comprehensively test the theoretical predictions of Gollier and Pratt (Econom J Econom Soc 64:1109–1123, 1996) versus Quiggin (Econ Theor 22(3):607–611, 2003). Gollier and Pratt (1996) build on EU theory and state that an increase in background risk will make subjects more risk averse while Quiggin (2003) states that an increase in background risk can enhance risk-taking in certain types of non-EU models. We find strong evidence that such non-EU preferences dominate in our sample.

The effects of task difficulty and presentation format on eye movements in risky choice

This study investigates the process of risky choice using eye tracking. We manipulate the complexity and presentation of lottery choices while measuring eye movements. In particular, we measure the frequencies of information collection procedures associated with established theories of risky choice, namely, expected utility theory and component comparison theory. These choice process patterns are sensitive to the difficulty of calculations and the presentation format of lotteries. Participants appear to transition between decision-making procedures depending on how lottery choices are presented and their complexity. They also attend to payoffs as the primary feature considered during component comparisons. Our findings emphasize the influence of information presentation on decision-making processes and decisions.

A parsimonious analytically specified general equilibrium structure that spans discount rates

This study arrives at an analytical structure that spans cross-sections of discount rates. The structure is not tainted by an endogeneity that is characteristic of alternate approaches, namely the necessity of assumptions in respect of firms’ expected returns. The structure is ‘general equilibrium’, because it is facilitated by a ‘no arbitrage’ condition which serves to induce indifference between comparable assets that ought to have positive demand, but that differ with respect to the certainty equivalents of their cash flows. The finding that the structure spans discount rates that are increasing strictly convex functions of cash flow risk evinces it’s robustness.

Exploring the Commuting Decision-Making Behavior of Low-Income Groups Based on Cumulative Prospect Theory

Based on cumulative prospect theory, this study proposes a decision-making model to reveal the commuting behavior of low-income groups under uncertain conditions. Considering the commuting characteristics of this group, travel economic cost is incorporated into the model. The decision-making behavior of low-income groups under different travel scenarios is analyzed to acquire the priority of commuting plans. Based on a stated preference survey of residents in Beijing, the commuting behavior of low-income groups is empirically analyzed. The results show that low-income groups will be affected by individual risk preference and characterized by bounded rational characteristics when making commuting decisions under uncertain conditions. Moreover, travel economic cost is a crucial factor for the decision-making of this group. When the travel budget time is less than the perceived time, they tend to seek risks and take punctual arrival as their primary goal. On the contrary, they tend to avoid risks. On the basis of ensuring the travel time meets their needs, low-income commuters always seek the economy and reliability of their travel plans. The empirical results further verify that the proposed model effectively describes the commuting decision-making behavior of low-income groups, and it is superior to the expected utility theory with respect to performance and behavior disclosure. This study provides a reference for improving the commuting efficiency and experience of low-income groups.

Evaluation of Weather Yield Index Insurance Exposed to Deluge Risk: The Case of Sugarcane in Thailand

Insurance serves as a mechanism to effectively manage and transfer revenue-related risks. We conducted a study to explore the potential financial advantages of index insurance, which protects agricultural producers, specifically sugarcane, against excessive rainfall. Creation of the index involved utilizing generalized additive regression models, allowing for consideration of non-linear effects and handling complex data by adjusting the complexity of the model through the addition or reduction of terms. Moreover, quantile generalized additive regression was deliberated to evaluate relationships with lower quantiles, such as low-yield events. To quantify the financial benefits for farmers, should they opt for excessive rainfall index insurance, we employed efficiency analysis based on metrics such as conditional tail expectation (CTE), certainty equivalence of revenue (CER), and mean root square loss (MRSL). The results of the regression model demonstrate its accuracy in predicting sugar cane yields, with a split testing R2 of 0.691. MRSL should be taken into consideration initially, as it is a farmer’s revenue assessment that distinguishes between those with and those without insurance. As a result, the GAM model indicates the least fluctuation in farmer income at the 90th percentile. Additionally, our study suggests that this type of insurance could apply to sugarcane farmers and other crop producers in regions where extreme rainfall threatens the financial sustainability of agricultural production.

Moral Injury Post-COVID-19: More Than Military? A Theological Perspective.

The author of this article considers moral distress theologically, as a potential shattering of core sustaining belief systems, hope, securities, self-identities, and organizing principles of one's existence. Shattering of individual moral expectations can occur in both medical and military moral injury.

A risk-based maintenance decision model for subsea pipeline considering pitting corrosion growth

Pitting corrosion growth of subsea pipeline can cause pipeline leak, resulting in the huge economic losses. This study presents a risk-based model to implement the optimal maintenance decision-making of subsea pipelines subject to pitting corrosion. Firstly, a pitting corrosion growth prediction model is built using DeWaard 95 model and dynamic Bayesian network (DBN). Subsequently, the probability of failure, i.e., PoF and consequence of failure, i.e., CoF for pipeline are estimated to obtain the risk profile of corroded pipeline. The maintenance cycle of pipeline is estimated based on total utility function and the acceptable risk. Eventually, a Bayesian influence diagram (BID) model and expected utility theory (EEU) are implemented to determine maintenance decision of corroded pipelines. The methodology is illustrated by a case study, which indicates that it can be a useful tool for maintenance decisions for subsea pipeline subject to pitting corrosion growth.

A framework to demonstrate the utility and safety of the observational method

AbstractUnderground engineering projects are often characterised by significant uncertainties, leading to complex decision‐making when selecting appropriate design methods. Traditional approaches, such as the observational method (OM), have been widely used but rarely explicitly account for the integration of risk, costs, construction timeframes and engineering judgement. Successfully reaching a consensus to implement the OM on tunnelling projects can be challenging and requires ensuring stakeholders understand how the method impacts structural safety. Fostering such understanding can be an arduous process. A risk‐based decision framework is introduced using expected utility theory to aid the decision to choose the OM, or not. The framework integrates risk, cost, construction timelines and engineering judgement within an economic decision model using a probabilistic approach. It is tested on a Sydney, Australia case study. A Monte Carlo model analysis examines contingency actions and structural failure probability when applying the OM. The case study highlights the significance of considering indirect costs in complex decisions and harnesses experienced professionals’ insights for a comprehensive risk and cost assessment. We conclude that merging probabilistic‐based design with OM enhances the ability to demonstrate structural safety and economic factors within a unified model.

Research on the Dispatching of Electric Vehicles Participating in Vehicle-to-Grid Interaction: Considering Grid Stability and User Benefits

As the prevalence of electric vehicles (EVs) continues to grow, their charging and discharging behaviors pose a challenge to the stable operation of power systems. Therefore, this paper analyzes the charging demand of EV users through GPS trajectory data and proposes an EV-discharging-optimization model based on vehicle-to-grid interaction (V2G). Firstly, the spatial–temporal distribution of EV-charging demand is obtained by cleaning and mining the big data of traveling vehicles, considering dynamic energy consumption theory and users’ willingness; secondly, a probabilistic model of EV users’ participation in V2G-demand response is constructed based on expected utility theory, which both considers the heterogeneity of users and reflects the interactive influence of users’ decisions; finally, a scheduling model of EV discharging in the regional grid is established. The results show that the proposed model can explore the potential of user participation in V2G in the study area, and the V2G response resources can reduce the grid fluctuation and enable users to obtain certain benefits, which achieves a win–win situation between the grid side and the user side.

Stochastic Adaptive Linear Quadratic Differential Games

Game theory is playing more and more important roles in understanding complex systems and in investigating intelligent machines with various uncertainties. As a starting point, we consider the classical two-player zero-sum linear-quadratic stochastic differential games, but in contrast to most of the existing studies, the coefficient matrices of the systems are assumed to be unknown to both players, and consequently it is necessary to study adaptive strategies of the players, which may be termed as adaptive games and which has rarely been explored in the literature. In this paper, by introducing a suitable information structure for adaptive games, we will show that a theory can be established on adaptive strategies that are designed based on both the certainty equivalence principle and the diminishing excitation technique. Under almost the same physical structure conditions as those in the traditional known parameters case, it is shown that the closed-loop adaptive game systems will be globally stable and asymptotically reach the Nash equilibrium.

Sampled-Data Cooperative Output Regulation: An Adaptive Distributed Continuous-Discrete Observer Approach

This paper studies the sampled-data cooperative output regulation problem for linear multi-agent systems. Firstly, a novel adaptive distributed continuous-discrete observer is established to recover the leader's state, which, on one hand, only relies on the sampling output of the leader, and on the other hand, does not need to store the sampled message from neighbors. Secondly, by solely making use of the digital states of both the agent and the distributed observer, a certainty equivalence control law is synthesized featuring a time-varying feedforward gain. It is rigorously proven that, with this time-varying feedforward gain, the proposed control approach can achieve exponential convergence of the tracking errors given arbitrary time-varying leader's signal, and the upper bound for the sampling intervals is explicitly given. Thirdly, for the class of chain-integrator multi-agent systems, the proposed control approach does not need any restriction on the upper bound of the sampling intervals, and thus would be more practical in certain application scenarios from the perspective of energy saving. The performance of the proposed control approach is validated by the simulation results of inverter-based distributed generation systems.

Risk preferences, newsvendor orders and supply chain coordination using the Mean-CVaR model

The standard newsvendor model assumes that decision-makers in the supply chain are risk-neutral. This paper explores the newsvendor problem using risk measures building on the classical normative definition of risk preferences by certainty equivalents to model risk-averse, risk-neutral, and risk-taking decision-makers. We suggest the Mean-CVaR model based on the popular risk measures Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). The objective function is characterized by a tolerance level differentiating between low and high profits and by a pessimism level representing the weight of low profits. For the first time, we prove that the optimal order quantity is higher (lower) than the risk-neutral order quantity if and only if the newsvendor is risk-taking (risk-averse). The equivalence of product-specific risk preferences and the size of the order quantity enables the determination of the Mean-CVaR parameters from given order quantities or from a target profit. Further, based on supply chain’s objective maximization criterion, we discuss supply chain coordination with Mean-CVaR decision-makers. We show that a simple wholesale price contract can coordinate the supplier–buyer supply chain and completely characterize the decision makers’ risk preferences under supply chain coordination. For example, if the coordinator (supplier) is risk-averse, a coordinating wholesale price exists for a less risk-averse buyer as well as for a risk-neutral and risk-taking buyer. We also determine the Mean-CVaR parameters if the coordinator specifies a target for the supply chain profit and the buyer communicates a target profit. In this case, the coordinating wholesale price depends on the ratio of the target profits and we show the impact on supply chain efficiency.

On entropy martingale optimal transport theory

In this paper, we give an overview of (nonlinear) pricing-hedging duality and of its connection with the theory of entropy martingale optimal transport (EMOT), recently developed, and that of convex risk measures. Similarly to Doldi and Frittelli (Finance Stoch 27(2):255–304, 2023), we here establish a duality result between a convex optimal transport and a utility maximization problem. Differently from Doldi and Frittelli (Finance Stoch 27(2):255–304, 2023), we provide here an alternative proof that is based on a compactness assumption. Subhedging and superhedging can be obtained as applications of the duality discussed above. Furthermore, we provide a dual representation of the generalized optimized certainty equivalent associated with indirect utility.

A trilemma for the lexical utility model of the precautionary principle

AbstractBartha and DesRoches (Synthese 199(3–4):8701–8740, 2021) and Steel and Bartha (Risk Analysis 43(2):260–268, 2023) argue that we should understand the precautionary principle as the injunction to maximise lexical utilities. They show that the lexical utility model has important pragmatic advantages. Moreover, the model has the theoretical advantage of satisfying all axioms of expected utility theory except continuity. In this paper I raise a trilemma for any attempt at modelling the precautionary principle with lexical utilities: it permits choice cycles or leads to paralysis or implies that the smallest value difference that is possible in a context has extreme axiological implications.

Optimal investment in ambiguous financial markets with learning

We consider the classical multi-asset Merton investment problem under drift uncertainty, i.e. the asset price dynamics are given by geometric Brownian motions with constant but unknown drift coefficients. The investor assumes a prior drift distribution and is able to learn by observing the asset prize realizations during the investment horizon. While the solution of an expected utility maximizing investor with constant relative risk aversion (CRRA) is well known, we consider the optimization problem under risk and ambiguity preferences by means of the KMM (Klibanoff et al., 2005) approach. Here, the investor maximizes a double certainty equivalent. The inner certainty equivalent is for given drift coefficient, the outer is based on a drift distribution. Assuming also a CRRA type ambiguity function, it turns out that the optimal strategy can be stated in terms of the solution without ambiguity preferences but an adjusted drift distribution. To the best of our knowledge an explicit solution method in this setting is new. We rely on some duality theorems to prove our statements.Based on our theoretical results, we are able to shed light on the impact of the prior drift distribution as well as the consequences of ambiguity preferences via the transfer to an adjusted drift distribution, i.e. we are able to explain the interaction of risk and ambiguity preferences. We compare our results with the ones in a pre-commitment setup where the investor is restricted to deterministic strategies. It turns out that (under risk and ambiguity aversion) an infinite investment horizon implies in both cases a maximin decision rule, i.e. the investor follows the worst (best) Merton fraction (over all realizations of it) if she is more (less) risk averse than a log-investor. We illustrate our findings with an extensive numerical study.

A behavioral definition of loss aversion

Loss aversion is one of the most important concepts in behavioral economics overcoming descriptive limitations of neoclassical risk aversion. Initially defined as disliking of symmetric 50%-50% bets, loss aversion implies that losses loom larger than gains under original prospect theory as well as many other decision theories but not under cumulative prospect theory (where probabilities of gains and losses are weighted differently). This paper proposes a minor modification of the definition of loss aversion as disliking of mixed lotteries that have symmetric certainty equivalents of their gain and loss parts. This behavioral definition works under cumulative prospect theory and ambiguity.

Fluctuation theorems and expected utility hypothesis.

The expected utility hypothesis is a popular concept in economics that is useful for making decisions when the payoff is uncertain. In this paper, we investigate the implications of a fluctuation theorem in the theory of expected utility. In particular, we wonder whether entropy could serve as a guideline for gambling. We prove the existence of a bound involving the certainty equivalent which depends on the entropy produced. Then, we examine the dependence of the certainty equivalent on the entropy by looking at specific situations, in particular, the work extraction from a nonequilibrium initial state.

Adaptive Control of Unmanned Aerial Vehicles with Varying Payload and Full Parametric Uncertainties

This article investigates an adaptive tracking control problem for a six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV) with a variable payload mass. The changing payload introduces time-varying parametric uncertainties into the dynamical model, rendering a static control strategy no longer effective. To handle this issue, two adaptive schemes are developed to maintain the uncertainties in the translational and rotational dynamics. Initially, a virtual proportional derivative (PD) is designed to stabilize the horizontal position; however, due to an unknown and time-varying mass, an adaptive controller is proposed to generate the total thrust of the UAV. Furthermore, an adaptive controller is designed for the rotational dynamics, to handle parametric uncertainties, such as inertia and external disturbance parameters. In both schemes, a standard adaptive scheme using the certainty equivalence principle is extended and designed. A stability analysis was conducted with rigorous analytical proofs to show the performance of our proposed controllers, and simulations were implemented to assess the performance against other existing methods. Tracking fitness and total control efforts were calculated and compared with closed-loop adaptive tracking control (CLATC) and adaptive sliding mode control (ASMC). The results indicated that the proposed design better maintained UAV stability.