nep-upt New Economics Papers
on Utility Models and Prospect Theory
Issue of 2026–05–25
fourteen papers chosen by
Alexander Harin


  1. Process Utility in High-Stakes Competition By Dupuy, Arnaud
  2. Evaluating Allocations of Opportunities By Francesco Andreoli; Mathieu Faure; Nicolas Gravel; Tista Kundu
  3. Optimal investment and Pension policy in Pay-As-You-Go systems under forward utility and ageing population By Jennifer Alonso Garcia; Caroline Hillairet; Sarah Kaakai; Mohamed Mrad
  4. Skill Premia and Pre-Marital Investments in Marriage Markets By Aditya Kuvalekar
  5. On the Possibility of Informationally Inefficient Markets Without Noise By Mattthijs Breugem
  6. Behavioral Factors in Tax Preparer and Tax Compliance Choices By James Alm; Jubo Yan; William D. Schulze; Melissa Vigil; Carrie von Bose
  7. Null player neutrality in TU-games: Egalitarian and Shapley solutions By J. C. Gon\c{c}alves-Dosantos; R. Mart\'inez; J. S\'anchez-Soriano
  8. AlphaGlass: Interpretable Characteristic-Based Portfolio Choice By Sebastian Bell; Ali Kakhbod; Martin Lettau; Abdolreza Nazemi
  9. Approximate Strategyproofness in Approval-based Budget Division By Haris Aziz; Patrick Lederer; Jeremy Vollen
  10. Robust Bayes Acts under Prior Perturbations: Contamination, Stability, and Selection Paths By Christoph Jansen; Georg Schollmeyer
  11. On convergence of the Mayer problems arising in the theory of financial markets with transaction cost By Yuri Kabanov; Artur Sidorenko
  12. Normative aspects in modeling the urgency of climate policy By Guerriero, Arthur Zito; Kapeller, Jakob; Ankel-Peters, Jörg
  13. Trade and Growth with Digital Data By Kyu Yub Lee
  14. Human-AI Productivity Paradoxes: Modeling the Interplay of Skill, Effort, and AI Assistance By Ali Aouad; Thodoris Lykouris; Huiying Zhong

  1. By: Dupuy, Arnaud (University of Luxembourg)
    Abstract: We study how individuals trade off outcome (what) and process (how) utility in high-stakes strategic decisions. We exploit optimality conditions and high-frequency choices in professional tennis to derive nonparametric bounds on process utility and implement a structural approach to estimate player-specific preferences. Under mild shape restrictions, these bounds imply that a large majority of players place positive weight on process utility. Our structural estimates further show that most players systematically sacrifice success probabilities to increase process utility, generating economically meaningful effects on match outcomes and expected earnings.
    Keywords: process utility, intrinsic motivation, outcome utility, salience weight, strategic behavior, nonparametric, structural estimation
    JEL: D91 D81 D01 C57
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:iza:izadps:dp18625
  2. By: Francesco Andreoli (UNIVR - Università degli studi di Verona = University of Verona, LISER - Luxembourg Institute of Socio-Economic Research); Mathieu Faure (EHESS - École des hautes études en sciences sociales, CCJ (UMR8173) - Chine, Corée, Japon (UMR8173) - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - UPCité - Université Paris Cité); Nicolas Gravel (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique); Tista Kundu (Christ University, Bangalore)
    Abstract: This paper provides a robust criterion for comparing lists of probability distributions-interpreted as allocations of opportunitiesfaced by different social groups. We axiomatically argue in favor of comparing those lists of probability distributions on the basis of a uniform-among groups-valuation of their expected utility. We identify an empirically implementable criterion for comparing allocations of opportunities that coincides with the unanimity of all such uniform valuations of expected utility that exhibit aversion to inequality of opportunity. We illustrate our criterion by evaluating allocations of educational opportunities among castes and genders in 14 Indian states.
    Keywords: caste | education, equalization of opportunity, gender, groups, probability distribution, zonotope
    Date: 2025
    URL: https://d.repec.org/n?u=RePEc:hal:journl:hal-05622181
  3. By: Jennifer Alonso Garcia; Caroline Hillairet; Sarah Kaakai; Mohamed Mrad
    Abstract: This paper investigates optimal investment and pension policies in a Pay-As-You-Go (PAYG) system supplemented by a buffer fund used as an intergenerational risk‑sharing mechanism. The social planner’s preference criterion is represented by non-zero volatility forward Constant Relative Risk Aversion (CRRA) utilities, and explicitly accounts for both sustainability and adequacy constraints. The optimal policies are characterized in closed form, and an in-depth analysis of the impact of preference sensitivities on the pension scheme is conducted. A detailed numerical analysis is performed to evaluate the sustainability and benefit adequacy of this hybrid PAYG–buffer‑fund arrangement under a range of demographic, financial, and macroeconomic scenarios.
    Keywords: Mixed PAYG pension with buffer fund schemes; optimal investment and pension policies; Sustainability and adequacy constraints; Demographic and financial risk sharing; Forward utility preferences
    Date: 2026–05–12
    URL: https://d.repec.org/n?u=RePEc:ulb:ulbeco:2013/406606
  4. By: Aditya Kuvalekar
    Abstract: I study a decentralized marriage market with search frictions, costly pre-marital skill investments, and non-transferable utility. Despite a symmetric environment, the market can exhibit asymmetric equilibria, with one gender investing more in skills than the other; in some environments, the asymmetric equilibrium is unique. A microfounded model of household utility maximization shows that this transition from a unique symmetric equilibrium to a unique asymmetric equilibrium can be driven by rising labor-market wages for high-skilled workers: as the skill premium rises, one gender ends up fully investing while the other invests substantially less.
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.10060
  5. By: Mattthijs Breugem
    Abstract: Noise traders can be dispensed with entirely. Partial revelation of information through prices arises under any non-exponential expected utility preference, including CRRA, without noise traders, random endowments, supply shocks, hedging motives, or behavioral biases. The model contains zero exogenous noise. The mechanism is a mismatch between the space in which market clearing aggregates signals and the Bayesian sufficient statistic. CARA demand is linear in log-odds, so prices aggregate in log-odds space and reveal the statistic exactly. Every other preference aggregates differently; the resulting Jensen gap makes revelation partial. I prove that CARA is the unique fully revealing preference class, characterize the rational expectations equilibrium via a contour integration fixed point, and verify that partial revelation survives learning from prices. The Grossman-Stiglitz paradox is resolved: information acquisition has positive value within the rational class. Numerical solution of the rational expectations fixed point at K = 3 confirms partial revelation, positive trade volume, and positive value of information across the full range of CRRA risk aversion, vanishing only in the CARA limit.
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.09136
  6. By: James Alm (Tulane University); Jubo Yan (Lingnan College, Sun Yat-sen University); William D. Schulze (Cornell University); Melissa Vigil (Internal Revenue Service); Carrie von Bose (Public Company Auditing Oversight Board)
    Abstract: What tax preparer characteristics are most important to taxpayers in their decision to use a tax preparer, and how does this choice of a tax preparer affect subsequent taxpayer compliance? We use laboratory experiments to examine these questions. We find that individuals in this environment simultaneously choose a preparer and their compliance based in part on factors predicted by the standard expected utility theory of individual behavior under uncertainty. However, we find that factors based on psychological considerations –- which we refer to as “behavioral factors” -– also play an important role in this setting: participants prefer tax preparers who are “credentialed, ” even when the cost is high or the credential has no impact on outcomes; participants fear an audit, regardless of its likelihood; participants often choose high-cost preparers even when they are fully compliant; and many participants forego substantial expected earnings rather than underreport income.
    Keywords: tax compliance; tax preparer; experimental economics; expected utility theory; behavioral economics
    JEL: H2 H26 C91
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:tul:wpaper:2606
  7. By: J. C. Gon\c{c}alves-Dosantos; R. Mart\'inez; J. S\'anchez-Soriano
    Abstract: We introduce and study the axiom of null player neutrality in the context of cooperative games with transferable utility (TU-games). This axiom weakens the classical coalitional strategic equivalence: rather than requiring that augmenting a game by a null-player game leaves that player's payoff unchanged, it only requires that any change in payoff be independent of the specific augmenting game, provided both the null-player condition and the grand-coalition value are preserved. We show that efficiency, linearity, symmetry, and null player neutrality together characterize the family of all real linear combinations of the Shapley value and the equal division solution, a family that strictly extends the well-known class of $\alpha$-egalitarian Shapley values (convex combinations, $\alpha \in [0, 1]$) to arbitrary $\alpha \in \mathbb{R}$. Replacing null player neutrality by its natural analogue for nullifying players uniquely pins down the equal division solution.
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.20113
  8. By: Sebastian Bell; Ali Kakhbod; Martin Lettau; Abdolreza Nazemi
    Abstract: We propose AlphaGlass, an inherently interpretable machine-learning framework for constructing portfolios that directly optimize investment objectives. AlphaGlass maps stock characteristics into additive signals with sparse interactions and converts these signals into long-short portfolios through a differentiable rank-and-mask layer. This end-to-end design allows the model to optimize objectives such as the Sharpe ratio or mean-variance utility while keeping portfolio weights interpretable and traceable to specific characteristics and interactions. We show theoretically that in-sample objective maximization consistently estimates the population objective and that the differentiable rank-and-mask layer is a faithful smooth proxy for the corresponding conventional long-short quantile portfolio. In U.S. equities, AlphaGlass delivers strong out-of-sample performance and reveals economically interpretable drivers of long and short positions.
    JEL: C14 C45 G10 G11 G12
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:nbr:nberwo:35186
  9. By: Haris Aziz; Patrick Lederer; Jeremy Vollen
    Abstract: In approval-based budget division, the task is to allocate a divisible resource to the candidates based on the voters' approval preferences over the candidates. For this setting, Brandl et al. [2021] have shown that no distribution rule can be strategyproof, efficient, and fair at the same time. In this paper, we aim to circumvent this impossibility theorem by focusing on approximate strategyproofness. To this end, we analyze the incentive ratio of distribution rules, which quantifies the maximum multiplicative utility gain of a voter by manipulating. While it turns out that several classical rules have a large incentive ratio, we prove that the Nash product rule ($\mathsf{NASH}$) has an incentive ratio of $2$, thereby demonstrating that we can bypass the impossibility of Brandl et al. by relaxing strategyproofness. Moreover, we show that an incentive ratio of $2$ is optimal subject to some of the fairness and efficiency properties of $\mathsf{NASH}$, and that the positive result for the Nash product rule even holds when voters may report arbitrary concave utility functions. Finally, we complement our results with an experimental analysis.
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.11736
  10. By: Christoph Jansen (Lancaster University Leipzig, Germany); Georg Schollmeyer (Ludwig-Maximilians-Universit\"at M\"unchen, Germany)
    Abstract: This paper develops a quantitative framework to assess the robustness of Bayes-optimal decisions in finite decision problems under model uncertainty. We introduce two complementary stability notions for acts: the robustness radius, measuring the largest perturbation of a reference prior under which an act remains Bayes-optimal, and the contamination need, quantifying the minimal perturbation required for an act to become Bayes-optimal under some nearby prior. Both concepts are characterized via linear programming formulations and computed efficiently using bisection methods exploiting monotonicity properties. Building on these stability measures, we propose a cost-adjusted stability criterion that integrates robustness considerations with act-specific selection costs, yielding a parametric family of decision rules indexed by a regularization parameter. We analyze how optimal act selection evolves along this parameter and derive selection paths that reveal structural transitions between stability-driven and cost-driven regimes. The framework is applied to a portfolio choice problem under uncertainty between different economic regimes. Concretely, using data on historical ETF returns, we compute robustness and contamination profiles for six portfolio strategies and analyze their behavior under heterogeneous belief specifications. The results illustrate that robustness-based selection refines classical expected utility by accounting for prior misspecification.
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.10495
  11. By: Yuri Kabanov; Artur Sidorenko
    Abstract: The geometric approach to financial markets with proportional transaction cost prescribes to imbed a specific model (of stock market, of currency market etc.), usually given in a parametric form, into a natural framework defined by the two random processes, S and K. The first one, d-dimensional, models the price evolution of basic securities while the second one, cone-valued, describes the evolution of the solvency set. It happened that the fundamental questions -- no-arbitrage criteria, hedging problems, portfolio optimization -- can be studied in this general setting opening the door to set-valued techniques. In this note we explore, in such a general framework, the stochastic Mayer control problem, consisting in the maximization of the expected utility of the portfolio terminal wealth. We get results on continuity of the optimal value and the optimal control under price approximations in a general multi-asset framework described by the geometric formalism.
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.11717
  12. By: Guerriero, Arthur Zito; Kapeller, Jakob; Ankel-Peters, Jörg
    Abstract: The social cost of carbon (SCC) isthe central concept of benefit-cost analysis in climate economics. The SCC provides guidance on the urgency of climate policy as it expresses the present value of expected future damages associated with the emission of one additional ton of CO2. This paper summarizes key normative assumptions underlying the calculation of the SCC and illustrates how these crucially affect the magnitude of final estimates. Building on a social welfare framework, we discuss the treatment of risk, time (discounting), and inequality (equity weights). Moreover, we present the normative choices related to how SCC estimates monetize non-market damage, in particular the loss of human lives. Based on a database of 515 studies with original SCC estimates (Tol, 2026), we document how the literature deals with these normative issues. In doing so, we find significant variation in the treatment of normative aspects across studies, but also across different normative dimensions. For instance, while the literature justifies the use of a time discount rate based on the assumption of diminishing marginal utility, equity aspects between countries or regions are often ignored. We conclude by stressing that while the SCC can help structuring societal deliberation about climate policy, greater clarity and transparency on the underlying normative assumptions is necessary.
    Abstract: Die sozialen Kosten von Kohlenstoff (SCC) sind das zentrale Konzept der Kosten-Nutzen-Analyse in der Klimawirtschaft. Die SCC geben Aufschluss über die Dringlichkeit klimapolitischer Maßnahmen, da sie den Barwert der erwarteten zukünftigen Schäden ausdrücken, die mit der Emission einer zusätzlichen Tonne CO2 verbunden sind. Dieser Beitrag fasst die wichtigsten normativen Annahmen zusammen, die der Berechnung der SCC zugrunde liegen, und veranschaulicht, wie diese die Höhe der endgültigen Schätzungen entscheidend beeinflussen. Aufbauend auf einem Rahmenkonzept der sozialen Wohlfahrt diskutieren wir die Behandlung von Risiko, Zeit (Diskontierung) und Ungleichheit (Gerechtigkeitsgewichte). Darüber hinaus stellen wir die normativen Entscheidungen vor, die damit zusammenhängen, wie SCC-Schätzungen nichtmarktbezogene Schäden, insbesondere den Verlust von Menschenleben, monetarisieren. Basierend auf einer Datenbank mit 515 Studien mit originären SCC-Schätzungen (Tol, 2026) dokumentieren wir, wie die Literatur mit diesen normativen Fragen umgeht. Dabei stellen wir erhebliche Unterschiede in der Behandlung normativer Aspekte nicht nur zwischen den Studien, sondern auch zwischen verschiedenen normativen Dimensionen fest. Während die Literatur beispielsweise die Verwendung eines zeitlichen Diskontsatzes auf der Grundlage der Annahme abnehmender Grenznutzen rechtfertigt, werden Gerechtigkeitsaspekte zwischen Ländern oder Regionen oft ignoriert. Abschließend betonen wir, dass die GSK zwar dazu beitragen kann, die gesellschaftliche Debatte über Klimapolitik zu strukturieren, jedoch mehr Klarheit und Transparenz hinsichtlich der zugrunde liegenden normativen Annahmen erforderlich ist.
    Keywords: climate change, social welfare, normativity, discounting, distribution, risk, value-neutrality
    JEL: D61 D63 Q54
    Date: 2026
    URL: https://d.repec.org/n?u=RePEc:zbw:rwirep:341095
  13. By: Kyu Yub Lee (KOREA INSTITUTE FOR INTERNATIONAL ECONOMIC POLICY (KIEP))
    Abstract: This paper introduces a newly developed model that examines the interplay between trade, growth, and digital data, emphasizing data’s dual role as both a driver of growth and a source of privacy concerns. Departing from existing trade and growth models that have largely overlooked digital data’s unique characteristics, this paper provides the first comprehensive analysis of how data influences growth through data flows and knowledge diffusion, while simultaneously introducing associated privacy trade-offs.<p> A key novelty of this model lies in its clear distinction between digital data and traditional “ideas.” Both concepts share the characteristics of non-rivalry and stocklike accumulation, meaning they are cumulative and can be used by multiple entities with negligible additional cost. However, ideas are generally understood to produce only positive externalities, whereas digital data uniquely generates both positive and negative externalities simultaneously, including privacy and cybersecurity concerns for consumers.<p> The model is built within a dynamic general equilibrium framework that incorporates international trade and endogenous technological change, extending the work of Rivera-Batiz and Romer (1991) by integrating the evolution of digital data. Consumption activities, both domestic and a portion of foreign consumption, actively contribute to a country’s evolving data stock. This generated data then acts as a negative externality in the utility function of privacy-conscious consumers, reducing their welfare, even as it serves as a primary input for the R&D sector, fueling the growth engine.<p> Key findings from this new model highlight significant impacts: First, (economic growth) the model shows that unrestricted cross-border data flows are a significant stimulant for economic growth. This positive effect is further magnified by stronger knowledge spillovers and an increased number of trading partners. Conversely, stricter restrictions on data flows directly impede economic growth. The paper notes that trade liberalization alone, without the diffusion of ideas or data flows, only generates a level effect and does not affect long-term economic growth.<p> Second, (trade-off with individual welfare) another central finding is the inherent trade-off between economic growth and individual welfare. While open data flows promote economic expansion, they simultaneously intensify privacy concerns, leading to a reduction in individual welfare. This conflict is particularly pronounced in scenarios with limited or inefficient knowledge diffusion. Conversely, the model indicates that stricter data regulations, while hindering growth, can enhance individual welfare by mitigating these privacy risks. To navigate the identified trade-off between growth and privacy, the paper advocates against data localization and strongly supports the implementation of deep digital trade agreements. These agreements are proposed as crucial mechanisms to facilitate freer data flows and knowledge sharing, thereby mitigating the inherent conflict and unlocking the full potential of the digital economy.
    Keywords: digital data; privacy; trade; endogenous growth; welfare
    JEL: D33 E00 J23 O41
    Date: 2025–11–07
    URL: https://d.repec.org/n?u=RePEc:ris:kiepwp:022487
  14. By: Ali Aouad; Thodoris Lykouris; Huiying Zhong
    Abstract: Generative Artificial Intelligence (AI) tools are rapidly adopted in the workplace and in education, yet the empirical evidence on AI's impact remains mixed. We propose a model of human-AI interaction to better understand and analyze several mechanisms by which AI affects productivity. In our setup, human agents with varying skill levels exert utility-maximizing effort to produce certain task outcomes with AI assistance. We find that incorporating either endogeneity in skill development or in AI unreliability can induce a productivity paradox: increased levels of AI assistance may degrade productivity, leading to potentially significant shortfalls. Moreover, we examine the long-term distributional effect of AI on skill, and demonstrate that skill polarization can emerge in steady state when accounting for heterogeneity in AI literacy -- the agent's capability to identify and adapt to inaccurate AI outputs. Our results elucidate several mechanisms that may explain the emergence of human-AI productivity paradoxes and skill polarization, and identify simple measures that characterize when they arise.
    Date: 2026–05
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.11350

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