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on Utility Models and Prospect Theory |
| By: | Hendrik Rommeswinkel |
| Abstract: | Decision makers may face situations in which they cannot observe the consequences that result from their actions. In such decisions, motivations other than the expected utility of consequences may play a role. The present paper axiomatically characterizes a decision model in which the decision maker cares about whether it can be ex post verified that a good consequence has been achieved. Preferences over acts uniquely characterize a set of events that the decision maker expects to be able to verify in case they occur. The decision maker chooses the act that maximizes the expected utility across verifiable events of the worst possible consequence that may have occurred. For example, a firm choosing between different carbon emission reduction technologies may find some technologies to leave ex post more uncertainty about the level of emission reduction than other technologies. The firm may care about proving to its stakeholders that a certain amount of carbon reduction has been achieved and may employ privately obtained evidence to do so. It may choose in expectation less efficient technologies if the achieved carbon reduction is better verifiable using the expected future evidence. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.19585 |
| By: | Yongheng Hu |
| Abstract: | Big data has exponentially dilated consumption demand and speed, but can they all convert to utility? We argue about the measures of consumption and utility acquisition in CARR utility function under the condition of big data interaction, we indicate its weakness, i.e., irrational consumption does not lead to the acquisition of utility. We consider that big data, which is different from macro and micro economic signals, formed by general information entropy, affects agents' rational cognition, which makes a part of their consumption ineffective. We preliminarily propose the theory that how dilution mechanism driven by big data will affect agents' cognitive resources. Based on theoretical and empirical analysis, we construct the Consumption Adjustment Weight Function (CAWF) of agents interacting with big data and further apply it to a model of firm wealth distribution with financial frictions, we get analytical solutions according to the Mean Field Game (MFG) and find: Lower financial friction increases the average wealth of firms but also leads to greater wealth inequality. When agents convert effective consumption into utility, which is a weight of total consumption, the average wealth of firms increases with the weight increasing. Meanwhile, wealth inequality follows a U-shaped trend, and it will be the lowest level when the weight approaches to 0.5. In conclusion, we try to provide a new complementary hypothesis to refine the 'Lucas Critique' according to the cognitive resources as endowments involved in the decision-making of agents. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.20435 |
| By: | David Lowing (Kyushu University, CRESE - Centre de REcherches sur les Stratégies Economiques (UR 3190) - UFC - Université de Franche-Comté - UBFC - Université Bourgogne Franche-Comté [COMUE], LGI - Laboratoire Génie Industriel - CentraleSupélec - Université Paris-Saclay); Makoto Yokoo (Kyushu University) |
| Abstract: | A Sharing value for transferable utility games distributes the Harsanyi dividend of each coalition among the players in the coalition's support. Such distribution is done according to a certain sharing system that determines the Sharing value. In this paper, we extend Sharing values to multi-choice games. Multi-choice games are a generalization of transferable utility games in which players have several activity levels. Unlike in transferable utility games, there is no straightforward way to interpret the support of a coalition in a multi-choice game. This makes it more tedious to distribute the Harsanyi dividend of a multi-choice coalition. We consider three possible interpretations of the support of a multi-choice coalition. Based on these interpretations, we derive three families of Sharing values for multi-choice games. To conduct this study, we discuss novel and classical axioms for multi-choice games. This allows us to provide an axiomatic foundation for each of these families of values. |
| Keywords: | Harsanyi set, Sharing values, Multi-choice games |
| Date: | 2025–08–06 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04018735 |
| By: | Asen Kochov; Yangwei Song |
| Abstract: | We study infinitely repeated games in which the players’ rates of time preference may evolve endogenously in the course of the game. Our goal is to strengthen the folk theorem of Kochov and Song (2023) by relaxing the assumption of observable mixtures. To that end, we identify and impose a new sufficient condition on preferences. The condition holds automatically in the standard case of time-separable utilities and a common discount factor, while being generic in ours. |
| Keywords: | folk theorem, recursive utility, endogenous discounting, unobserved mixtures |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12066 |
| By: | Yukihiro Nishimura (Osaka University and CESifo) |
| Abstract: | Given that the incentive consideration reduces the scope for redistribution, Mirrlees (1976, Optimal tax theory: a synthesis. Journal of Public Economics 6, 327‒358) emphasized the redistributive effects of commodity taxes (which include capital income tax), which reduces the effective tax wedge on labor income. We revert to the unidimensional case to show that the optimal labor wedge can become higher after the introduction of the optimal commodity taxes/subsidies when labor complements are subsidized. This is partly because supplementary commodity taxes are not increasing in ability as Mirrlees (1976) thought. Among the classic results, decreasing marginal taxes on the middle class, including the mode of the income distribution, remains valid with commodity taxes and without separability in the utility function. |
| Keywords: | Commodity tax, Income tax, Marginal income tax rates |
| JEL: | H21 H24 D63 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:osk:wpaper:2508 |
| By: | Esteban M. Aucejo; Jacob French; Paola Ugalde Araya; Basit Zafar |
| Abstract: | Information frictions significantly shape students' academic trajectories, but their differential impact across student backgrounds remains understudied. Using a novel panel survey capturing incoming students' subjective expectations and anonymized transcript data from Arizona State University, we first show that parental education strongly predicts educational success, even after controlling for demographics and measurable college preparation. First-generation students enter college less informed and with more uncertain beliefs, facing substantial challenges stemming from limited understanding and uncertainty about the higher education setting. A Bayesian expected utility maximization model demonstrates that higher uncertainty alone can sustain persistent achievement gaps. Empirically, students update their beliefs and make academic decisions consistent with the model’s predictions. Finally, leveraging a natural experiment involving a targeted first-year experience program for academically marginal students, we demonstrate that cost-effective interventions can successfully reduce knowledge frictions, improve retention, and encourage beneficial early major switching. |
| JEL: | D83 I23 I24 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34129 |
| By: | Zizhe Xia |
| Abstract: | I use a novel geometric approach to compare information in moral hazard problems. I study three nested geometric orders on information, namely the column space, the conic span, and the zonotope orders. The orders are defined by the inclusion of the column space, the conic span, and the zonotope of the matrices representing the experiments. For each order, I establish four equivalent characterizations, (i) inclusion of polyhedral sets of feasible state dependent utilities, (ii) matrix factorization, (iii) posterior belief distributions, and (iv) classes of moral hazard problems. The column space order characterizes the comparison of feasibility in all moral hazard problems. The conic span order characterizes the comparison of costs in all moral hazard problems with a risk neutral agent and limited liability. The zonotope order characterizes the comparison of costs in all moral hazard problems when the agent can have any utility exhibiting risk aversion. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.12476 |
| By: | Yuichiro Kamada; Fuhito Kojima; Akira Matsushita |
| Abstract: | Fragmentation of matching markets is a ubiquitous problem across countries and across applications. In order to study the implications of fragmentation and possibilities for integration, we first document and discuss a variety of fragmentation cases in practice such as school choice, medical residency matching, and so forth. Using the real-life dataset of daycare matching markets in Japan, we then empirically evaluate the impact of interregional transfer of students by estimating student utility functions under a variety of specifications and then using them for counterfactual simulation. Our simulation compares a fully integrated market and a partially integrated one with a "balancedness" constraint -- for each region, the inflow of students from the other regions must be equal to the outflow to the other areas. We find that partial integration achieves 39.2 to 59.6% of the increase in the child welfare that can be attained under full integration, which is equivalent to a 3.3 to 4.9% reduction of travel time. The percentage decrease in the unmatch rate is 40.0 to 52.8% under partial integration compared to the case of full integration. The results suggest that even in environments where full integration is not a realistic option, partial integration, i.e., integration that respects the balancedness constraint, has a potential to recover a nontrivial portion of the loss from fragmentation. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.19628 |
| By: | Hoang Giang Pham; Tien Mai; Minh Ha Hoang |
| Abstract: | In this paper, we revisit parameter estimation for multinomial logit (MNL), nested logit (NL), and tree-nested logit (TNL) models through the framework of convex conic optimization. Traditional approaches typically solve the maximum likelihood estimation (MLE) problem using gradient-based methods, which are sensitive to step-size selection and initialization, and may therefore suffer from slow or unstable convergence. In contrast, we propose a novel estimation strategy that reformulates these models as conic optimization problems, enabling more robust and reliable estimation procedures. Specifically, we show that the MLE for MNL admits an equivalent exponential cone program (ECP). For NL and TNL, we prove that when the dissimilarity (scale) parameters are fixed, the estimation problem is convex and likewise reducible to an ECP. Leveraging these results, we design a two-stage procedure: an outer loop that updates the scale parameters and an inner loop that solves the ECP to update the utility coefficients. The inner problems are handled by interior-point methods with iteration counts that grow only logarithmically in the target accuracy, as implemented in off-the-shelf solvers (e.g., MOSEK). Extensive experiments across estimation instances of varying size show that our conic approach attains better MLE solutions, greater robustness to initialization, and substantial speedups compared to standard gradient-based MLE, particularly on large-scale instances with high-dimensional specifications and large choice sets. Our findings establish exponential cone programming as a practical and scalable alternative for estimating a broad class of discrete choice models. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.01562 |
| By: | Dong Yan; Nanyi Zhang; Junyi Guo |
| Abstract: | In this paper, we first conduct a study of the portfolio selection problem, incorporating both exogenous (proportional) and endogenous (resulting from liquidity risk, characterized by a stochastic process) transaction costs through the utility-based approach. We also consider the intrinsic relationship between these two types of costs. To address the associated nonlinear two-dimensional Hamilton-Jacobi-Bellman (HJB) equation, we propose an innovative deep learning-driven policy iteration scheme with three key advantages: i) it has the potential to address the curse of dimensionality; ii) it is adaptable to problems involving high-dimensional control spaces; iii) it eliminates truncation errors. The numerical analysis of the proposed scheme, including convergence analysis in a general setting, is also discussed. To illustrate the impact of these two types of transaction costs on portfolio choice, we conduct through numerical experiments using three typical utility functions. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.02267 |
| By: | David Baqaee; Ariel Burstein |
| Abstract: | We study aggregate efficiency when households have heterogeneous preferences and outcomes. We generalize the consumption-equivalent variation of Lucas (1987) to a multi-agent setting, asking: how much can the consumption-possibility set shrink while keeping every agent at least as well off as in their status-quo allocation? The resulting scalar — resources left over after compensating everyone — is our measure of aggregate efficiency. Efficiency rises whenever the same status-quo welfare can be achieved with fewer resources. We show how to convert this problem into an equivalent utility-maximization problem, enabling the use of tools and results normally applicable only in representative agent settings. We characterize changes in aggregate efficiency in terms of observables, like expenditures and price elasticities, and apply our results to study, among other things, the effects of productivity shocks, the costs of misallocation, and the gains from trade, both with and without costly redistribution. |
| JEL: | A10 C0 D0 D3 D50 D60 E0 F0 H0 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34176 |
| By: | David Axelrod (Montclair State University, Montclair, NJ, USA); Arnaud Kurze (Montclair State University, Montclair, NJ, USA); Ethne Swartz (Montclair State University, Montclair, NJ, USA) |
| Abstract: | This paper considers how competing worldviews, rooted in an underlying schism between business and humanities understanding of economics, increasingly shape AI advancements, their use, and the implications for the experiences of justice in society. The schism emerged during the mid-19th century as classical economics (originating around Adam Smith’s The Wealth of Nations) developed into the utility-based, ahistorical Marginalist Revolution, which prioritized efficiency and quantitative models (now dominant in business and management education), and the dialectical-based, historical Marxist Revolution (underlying the assumptions of theorists in the Humanities and many social sciences). These reflect deeper ideological tensions: a focus on objective optimization and AI-driven decision-making versus a commitment to subjective autonomy and the preservation of human agency. We discuss “justice experiences†, a wide range of events ranging from actions in the judicial/legal system to personal and social impressions of, and expressions for, what is just. While AI promises to reduce costs and accelerate resolutions across civil disputes, criminal cases, and broader social justice concerns, automation risks deepening economic and legal inequalities. Further, the issue of alienation from the production of justice suggests another bifurcation: those who have lower incomes and few assets might only be provided with AI-generated resolutions, with traditional lawyers and court proceedings available only to the wealthiest. Beyond supply, this may increase demand for justice experiences, potentially widening the gap between what justice people receive and what they believe they deserve, and lead to exacerbating, and not reducing, social justice issues. |
| Keywords: | Justice Experiences, Economic Schism, AI Entrepreneurship, Social Justice |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0494 |