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on Utility Models and Prospect Theory |
| By: | Franz Dietrich (Centre d'Economie de la Sorbonne, Paris School of Economics, CNRS) |
| Abstract: | Economists routinely measure individual welfare by (von-Neumann-Morgenstern) utility, for instance when analysing welfare intensity, social welfare, or welfare inequality. Is this welfare measure justified? Natural working hypotheses turn out to imply a different measure. It overcomes familiar problems of utility, by faithfully capturing non-ordinal information, such as welfare intensity - despite still resting on purely ordinal evidence, such as revealed preferences or self-reported welfare comparisons. Social welfare analysis changes when based on this new individual welfare measure rather than utility. For instance, Harsanyi's 'utilitarian theorem' now supports prioritarianism. We compare the standard utility-based versions of utilitarianism and prioritarianism with new versions based on our welfare measure. We show that utility is a hybrid object determined by two rival influences: welfare and the attitude to intrinsic risk, i.e., to risk in welfare. A new version of Harsanyi's theorem shows that Harsanyi makes the questionable implicit assumption that society is neutral to intrinsic risk, overruling people's risk attitudes. We thus propose risk-impartial utilitarianism, which adopts people's (average) risk attitude |
| Keywords: | welfare; utility; risk attitude; social welfare; utilitarianism; Harsanyi-Sen debate; Harsanyi's Theorem; Bernoulli's hypothesis |
| JEL: | D00 D60 D63 D69 D70 D80 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:mse:cesdoc:25003rrr |
| By: | Martyna Kobus; Radoslaw Kurek; Thomas Parker |
| Keywords: | Loss aversion; inequality aversion; stochastic dominance; bootstrap inference |
| JEL: | D04 C14 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:cxu:wpaper:59 |
| By: | Xinyu Chen; Zuo Quan Xu |
| Abstract: | This paper studies an $\alpha$-robust utility maximization problem where an investor faces an intractable claim -- an exogenous contingent claim with known marginal distribution but unspecified dependence structure with financial market returns. The $\alpha$-robust criterion interpolates between worst-case ($\alpha=0$) and best-case ($\alpha=1$) evaluations, generalizing both extremes through a continuous ambiguity attitude parameter. For weighted exponential utilities, we establish via rearrangement inequalities and comonotonicity theory that the $\alpha$-robust risk measure is law-invariant, depending only on marginal distributions. This transforms the dynamic stochastic control problem into a concave static quantile optimization over a convex domain. We derive optimality conditions via calculus of variations and characterize the optimal quantile as the solution to a two-dimensional first-order ordinary differential equation system, which is a system of variational inequalities with mixed boundary conditions, enabling numerical solution. Our framework naturally accommodates additional risk constraints such as Value-at-Risk and Expected Shortfall. Numerical experiments reveal how ambiguity attitude, market conditions, and claim characteristics interact to shape optimal payoffs. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.04649 |
| By: | Federico Echenique; Gerelt Tserenjigmid |
| Abstract: | McGranaghan, Nielsen, O'Donoghue, Somerville, and Sprenger [2024] argue that standard paired choice tests for the common ratio effect are structurally biased when choice is stochastic, proposing valuation tests as a robust alternative. Using valuation tests, they find no systematic evidence for the common ratio effect, seemingly overturning much of the extant literature. We evaluate this conclusion in light of stochastic choice theory. We demonstrate that valuation tests are inherently biased and lack predictive power under standard expected utility assumptions. In contrast, we advocate for a ``strong'' paired choice test, proving it remains robustly unbiased across standard models of stochastic choice. Applying this strong test to existing experimental data, we find that the common ratio effect remains highly prevalent. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.06050 |
| By: | Alessandro Doldi; Marco Frittelli; Marco Maggis |
| Abstract: | Within a general semimartingale framework, we study the relationship between collective market efficiency and individual rationality. We derive a necessary and sufficient condition for the existence of (possibly zero-sum) exchanges among agents that strictly increase their indirect utilities and characterize this condition in terms of the compatibility between agents' preferences and collective pricing measures. The framework applies to both continuous- and discrete-time models and clarifies when cooperation leads to a strict improvement in each participating agent's indirect utility. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.02862 |
| By: | Costa, Carlos Eugênio da; Berriel, Rafael |
| Abstract: | Should workers or retirees bear the risk of economic growth? We show that efficient risk-sharing depends on how incentive provision – through consumption dispersion – affects the marginal value of resources, and how retirement promises back-load incentive provision. We use statistics for these two forces to show that perfect risk-sharing is optimal when the utility from consumption is logarithmic or when aggregate productivity growth is i.i.d. When neither condition holds, deviations from perfect risk sharing increase welfare. These deviations are, however, small due to the failure of a consumption-based stochastic discount factor (SDF) to price consumption growth. An augmented model that matches asset price behavior yields quantitatively relevant deviations from perfect risk-sharing. |
| Date: | 2026–03–24 |
| URL: | https://d.repec.org/n?u=RePEc:fgv:epgewp:851 |
| By: | Easton K. Huch; Michael P. Keane |
| Abstract: | Discrete choice models are fundamental tools in management science, economics, and marketing for understanding and predicting decision-making. Logit-based models are dominant in applied work, largely due to their convenient closed-form expressions for choice probabilities. However, these models entail restrictive assumptions on the stochastic utility component, constraining our ability to capture realistic and theoretically grounded choice behavior—most notably, substitution patterns. In this work, we propose an amortized inference approach using a neural network emulator to approximate choice probabilities for general error distributions, including those with correlated errors. Our proposal includes a specialized neural network architecture and accompanying training procedures designed to respect the invariance properties of discrete choice models. We provide group-theoretic foundations for the architecture, including a proof of universal approximation given a minimal set of invariant features. Once trained, the emulator enables rapid likelihood evaluation and gradient computation. We use Sobolev training, augmenting the likelihood loss with a gradient-matching penalty so that the emulator learns both choice probabilities and their derivatives. We show that emulator-based maximum likelihood estimators are consistent and asymptotically normal under mild approximation conditions, and we provide sandwich standard errors that remain valid even with imperfect likelihood approximation. Simulations show significant gains over the GHK simulator in accuracy and speed. |
| JEL: | C10 C13 C15 C25 C35 C45 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35037 |
| By: | Takashi Kamihigashi (Center for Computational Social Science (CCSS) and Research Institute for Economics & Business Administration, Kobe University, JAPAN); Corrado Di Guilimi (Economic Discipline Group, University of Technology Sydney, AUSTRALIA, Department of Economics and ManagementUniversity of Florence, ITALY, Center for Computational Social Science, Kobe University, JAPAN and Centre for Applied Macroeconomic Analysis, Australian National University, AUSTRALIA) |
| Abstract: | The paper introduces forward-looking intertemporal optimization in an agent-based model. Optimization is implemented considering, on the one hand that revision of economic behavior do not occur continuosly over time but only when circumstances suggest or impose it, and, on the other hand, that, given the inherent uncertainty and complexity of the economic system, the planning horizon is finite. We propose a macroeco nomic model with a large population of household agents. Each period a random sample of them will reset their propensities to consume and invest by maximizing their intertemporal utility. The study is a primer in considering the joint effect of heterogeneous agents’ interaction and forward-looking behavior, and provides novel insights into the mechanism of transmission of individual choices to the macroeconomy. The heavy computational tasks are managed through the development of new programming tools. The oexistence of interaction and forward looking be havior generates interesting coordination dynamics. The results suggest that even a tiny fraction of optimizing agents over the whole population has a significant effect of aggregate output, but this effect is nonlinear and conditional on the length of the panning horizon. |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:kob:dpaper:dp2026-13 |