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on Utility Models and Prospect Theory |
| By: | Antonio Penta; Larbi Alaoui |
| Abstract: | We revisit the long-lasting debate about the meaning of the utility function used in the standard Expected Utility (EU) model. Despite the common view that EU forces risk aversion and diminishing marginal utility of wealth to be pegged to one another, here we show that this is not the case. Marginal utility for money is an input into risk attitude, but it is not its sole determinant. The attitude towards ‘pure risk’ is also a contributing factor, and it is independent from the former. We discuss several theoretical implications of this result, for the following topics: (i) non-neutral risk attitudes for profit maximizing firms; (ii) risk-aversion over time lotteries in the presence of discounting; (iii) the equity premium puzzle. We also discuss matters of identification: (i) for firms; (ii) via proxies ; (iii) via standard MLE-methods under parametric restrictions; and (iv) cross-context elicitation in multi-dimensional settings, and its relationship with the methods and results from the psychology literature. |
| Keywords: | utility function, risk-aversion, marginal utility |
| JEL: | C72 C91 C92 D80 D91 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:upf:upfgen:1909 |
| By: | Wing-Keung Wong (Department of Finance, Fintech Center, and Big Data Research Center, Asia University; Department of Medical Research, China Medical University Hospital, Taiwan; Business, Economic and Public Policy Research Centre, Hong Kong Shue Yan University; The Economic Growth Centre, Nanyang Technological University); Chenghu Ma (Fudan University); Zhuo Qiao (Faculty of Business Administration, University of Macau); Udo Broll (Dresden University of Technology); Joao Paulo Vieito (Polytechnic Institute of Viana do Castelo) |
| Abstract: | In this paper, we first state some well-known problems including the Friedman-Savage paradox raised by Friedman and Savage (1948) who wonder why individuals would like to buy insurance as well as buy lottery tickets. To provide solutions to the problems, we first use the idea from Fishburn and Kochenberger (1979), Thon and Thorlund-Petersen (1988), and Chew and Tan (2005) to use two-way stochastic dominance to define the j-order risk-averse and risk-seeking utility that consists of both risk-averse and risk-seeking components and we call the utility AD utility and call investors with AD utility AD investors. Thereafter, we develop a new stochastic dominance theory for AD investors and we call the theory ADSD theory. We then develop some properties for the ADSD theory, including properties of expected-utility maximization, hierarchy, transitivity, and diversification, and properties under the additional condition of equal mean so that we can use the theory to get the solutions for all the problems and hypotheses we set in this paper. Applying the ADSD theory, we first get a new solution for the Friedman-Savage paradox. In addition, we find that AD investors could invest in both completely diversified portfolio and individual assets and, in general, buy any pair of both less-risky and more-risky assets. For example, AD investors could invest in both bonds and stocks, both bonds and futures, and both stocks and futures to get higher expected utility. |
| Keywords: | Stochastic Dominance; Risk Aversion; Risk Seeking; Utility Function; riskier Asset; Less Risky Asset |
| JEL: | D81 G11 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:nan:wpaper:2506 |
| By: | Linus Thierry Nana Noumi; Roland Pongou; Bertrand Tchantcho (CY Cergy Paris Université, THEMA) |
| Abstract: | Understanding how individuals and groups differ in their opinions and preferences is central to analyzing disagreement, measuring polarization, designing institutions, and predicting collective outcomes. Yet comparing preferences requires more than observing how each person ranks alternatives—it requires a method for comparing preference orderings themselves. This paper develops a formal framework to infer how individuals might rank different preference orderings based solely on their observed preferences. We introduce a set of natural and behaviorally plausible axioms—Independence (I), Disagreement Aversion (DA), and Symmetry (S)—and show that they uniquely characterize a class of hyperpreference relations and their associated utility representations. We apply this framework to the study of aggregation mechanisms, deriving necessary and sufficient conditions on utility structures that induce truthful preference reporting in equilibrium and guarantee efficiency. Our results yield new insights into strategyproof mechanism design under deep preference heterogeneity and clarify when differences of opinion can be meaningfully and reliably measured. KEYWORDS. Preference, Hyperpreference, Hyperutility, Strategy-proofness, Efficiency |
| Keywords: | Preference, Hyperpreference, Hyperutility, Strategy-proofness, Efficiency |
| JEL: | D01 D04 D71 D78 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ema:worpap:2025-11 |
| By: | Alex Bloedel; Tommaso Denti; Luciano Pomatto |
| Abstract: | We introduce a new cost function over experiments, f-information, based on the theory of multivariate statistical divergences, that generalizes Sims's classic model of rational inattention as well as the class of posterior-separable cost functions. We characterize its behavioral predictions by deriving optimality conditions that extend those of Matejka and McKay (2015) and Caplin, Dean, and Leahy (2019) beyond mutual information. Using these tools, we study the implications of f-information in a number of canonical decision problems. A strength of the framework is that it can be analyzed using familiar methods of microeconomics: convex duality and the Arrow-Pratt approach to expected utility. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.03482 |
| By: | Mohammad Ghaderi; Kamel Jedidi; Miłosz Kadziński; Bas Donkers |
| Abstract: | We introduce the Random Preference Model (RPM), a non-parametric and flexible discrete choice model. RPM is a rank-based stochastic choice model where choice options have multi-attribute representations. It takes preference orderings as the main primitive and models choices directly based on a distribution over partial or complete preference orderings over a ï¬ nite set of alternatives. This enables it to capture context-dependent behaviors while maintaining adherence to the regularity axiom. In its output, it provides a full distribution over the entire preference parameter space, accounting for inferential uncertainty due to limited data. Each ranking is associated with a subspace of utility functions and assigned a probability mass based on the expected log-likelihood of those functions in explaining the observed choices. We propose a two-stage estimation method that separates the estimation of ranking-level probabilities from the inference of preference parameters variation for a given ranking, employing Monte Carlo integration with subspace-based sampling. To address the factorial complexity of the ranking space, we introduce scalable approximation strategies: restricting the support of RPM to a randomly sampled or orthogonal basis subset of rankings and using partial permutations (top-k lists). We demonstrate that RPM can effectively recover underlying preferences, even in the presence of data inconsistencies. The experimental evaluation based on real data conï¬ rms RPM variants consistently outperform multinomial logit (MNL) in both in-sample ï¬ t and holdout predictions across different training sizes, with support-restricted and basis-based variants achieving the best results under data scarcity. Overall, our ï¬ ndings demonstrate RPM’s flexibility, robustness, and practical relevance for both predictive and explanatory modeling. |
| Keywords: | choice models, nonparametric modeling, rankings, context-dependent preference, random utility |
| JEL: | C35 C14 C15 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:upf:upfgen:1913 |
| By: | Shawn Berry |
| Abstract: | Traffic congestion represents a complex urban phenomenon that has been the subject of extensive research employing various modeling techniques grounded in the principles of physics and molecular theory. Although factors such as road design, accidents, weather conditions, and construction activities contribute to traffic congestion, driver behavior and decision-making are primary determinants of traffic flow efficiency. This study introduces a driver behavior archetype model that quantifies the relationship between individual driver behavior and system-level traffic outcomes through game-theoretic modeling and simulation (N = 500, 000) of a three-lane roadway. Mann-Whitney U tests revealed statistically significant differences across all utility measures (p 2.0). In homogeneous populations, responsible drivers achieved substantially higher expected utility (M = -0.090) than irresponsible drivers (M = -1.470). However, in mixed environments (50/50), irresponsible drivers paradoxically outperformed responsible drivers (M = 0.128 vs. M = -0.127), illustrating a social dilemma wherein defection exploits cooperation. Pairwise comparisons across the six driver archetypes indicated that all irresponsible types achieved equivalent utilities while consistently surpassing responsible drivers. Lane-specific analyses revealed differential capacity patterns, with lane 1 exhibiting a more pronounced cumulative utility decline. These findings offer a robust framework for traffic management interventions, congestion prediction, and policy design that aligns individual incentives with collective efficiency. Directions for future research were also proposed. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.04740 |
| By: | Pauline Corblet; Jeremy Fox; Alfred Galichon |
| Abstract: | We introduce a model of dynamic matching with transferable utility, extending the static model of Shapley and Shubik (1971). Forward-looking agents have individual states that evolve with current matches. Each period, a matching market with market-clearing prices takes place. We prove the existence of an equilibrium with time-varying distributions of agent types and show it is the solution to a social planner's problem. We also prove that a stationary equilibrium exists. We introduce econometric shocks to account for unobserved heterogeneity in match formation. We propose two algorithms to compute a stationary equilibrium. We adapt both algorithms for estimation. We estimate a model of accumulation of job-specific human capital using data on Swedish engineers. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.02737 |
| By: | Xin Tong; Thi Thu Uyen Hoang; Xue-Xin Wei; Michael Hahn |
| Abstract: | Understanding the representation of probability in the human mind has been of great interest to understanding human decision making. Classical paradoxes in decision making suggest that human perception distorts probability magnitudes. Previous accounts postulate a Probability Weighting Function that transforms perceived probabilities; however, its motivation has been debated. Recent work has sought to motivate this function in terms of noisy representations of probabilities in the human mind. Here, we present an account of the Probability Weighting Function grounded in rational inference over optimal decoding from noisy neural encoding of quantities. We show that our model accurately accounts for behavior in a lottery task and a dot counting task. It further accounts for adaptation to a bimodal short-term prior. Taken together, our results provide a unifying account grounding the human representation of probability in rational inference. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.04698 |