nep-upt New Economics Papers
on Utility Models and Prospect Theory
Issue of 2024‒01‒29
four papers chosen by



  1. A Simpler Proof of Gilboa and Schmeidler's (1989) Maxmin Expected Utility Representation By Ian Ball
  2. Real term premia in consumption-based models By Melissinos, Errikos
  3. Least-cost diets to teach optimization and consumer behavior, with applications to health equity, poverty measurement and international development By Jessica K. Wallingford; William A. Masters
  4. Monitoring with Rich Data By Mira Frick; Ryota Iijima; Yuhta Ishii

  1. By: Ian Ball
    Abstract: This note gives a simpler proof of the main representation theorem in Gilboa and Schmeidler (1989).
    Date: 2023–12
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2312.06107&r=upt
  2. By: Melissinos, Errikos
    Abstract: Can consumption-based mechanisms generate positive and time-varying real term premia as we see in the data? I show that only models with time-varying risk aversion or models with high consumption risk can independently produce these patterns. The latter explanation has not been analysed before with respect to real term premia, and it relies on a small group of investors exposed to high consumption risk. Additionally, it can give rise to a "consumption-based arbitrageur" story of term premia. In relation to preferences, I consider models with both time-separable and recursive utility functions. Specifically for recursive utility, I introduce a novel perturbation solution method in terms of the intertemporal elasticity of substitution. This approach has not been used before in such models, it is easy to implement, and it allows a wide range of values for the parameter of intertemporal elasticity of substitution.
    Keywords: term premia, consumption-based models, habit, long-run risk, limited arbitrage, high consumption volatility, recursive utility, solution methods
    JEL: C65 E43 G12
    Date: 2024
    URL: http://d.repec.org/n?u=RePEc:zbw:safewp:281062&r=upt
  3. By: Jessica K. Wallingford; William A. Masters
    Abstract: The least-cost diet problem introduces students to optimization and linear programming, using the health consequences of food choice. We provide a graphical example, Excel workbook and Word template using actual data on item prices, food composition and nutrient requirements for a brief exercise in which students guess at and then solve for nutrient adequacy at lowest cost, before comparing modeled diets to actual consumption which has varying degrees of nutrient adequacy. The graphical example is a 'three sisters' diet of corn, beans and squash, and the full multidimensional model is compared to current food consumption in Ethiopia. This updated Stigler diet shows how cost minimization relates to utility maximization, and links to ongoing research and policy debates about the affordability of healthy diets worldwide.
    Date: 2023–12
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2312.11767&r=upt
  4. By: Mira Frick; Ryota Iijima; Yuhta Ishii
    Abstract: We consider moral hazard problems where a principal has access to rich monitoring data about an agent's action. Rather than focusing on optimal contracts (which are known to in general be complicated), we characterize the optimal rate at which the principal's payoffs can converge to the first-best payoff as the amount of data grows large. Our main result suggests a novel rationale for the widely observed binary wage schemes, by showing that such simple contracts achieve the optimal convergence rate. Notably, in order to attain the optimal convergence rate, the principal must set a lenient cutoff for when the agent receives a high vs. low wage. In contrast, we find that other common contracts where wages vary more finely with observed data (e.g., linear contracts) approximate the first-best at a highly suboptimal rate. Finally, we show that the optimal convergence rate depends only on a simple summary statistic of the monitoring technology. This yields a detail-free ranking over monitoring technologies that quantifies their value for incentive provision in data-rich settings and applies regardless of the agent's specific utility or cost functions.
    Date: 2023–12
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2312.16789&r=upt

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