scholarly journals Maxmin expected utility with non-unique prior

2010 ◽  
pp. 125-135 ◽  
Author(s):  
Itzhak Gilboa ◽  
David Schmeidler
Keyword(s):  
Expected Utility ◽  
Maxmin Expected Utility

If It Is Surely Better, Do It More? Implications for Preferences Under Ambiguity

2021 ◽  
Author(s):  
Soheil Ghili ◽  
Peter Klibanoff
Keyword(s):  
Expected Utility ◽  
Ambiguity Aversion ◽  
Upper Bounds ◽  
Maxmin Expected Utility ◽  
Weak Dominance ◽  
Choice Under Uncertainty ◽  
Tight Connection ◽  
Sales Agent ◽  
Utility Preferences ◽  
Sensitive Behavior

Consider a canonical problem in choice under uncertainty: choosing from a convex feasible set consisting of all (Anscombe–Aumann) mixtures of two acts f and g, [Formula: see text]. We propose a preference condition, monotonicity in optimal mixtures, which says that surely improving the act f (in the sense of weak dominance) makes the optimal weight(s) on f weakly higher. We use a stylized model of a sales agent reacting to incentives to illustrate the tight connection between monotonicity in optimal mixtures and a monotone comparative static of interest in applications. We then explore more generally the relation between this condition and preferences exhibiting ambiguity-sensitive behavior as in the classic Ellsberg paradoxes. We find that monotonicity in optimal mixtures and ambiguity aversion (even only local to an event) are incompatible for a large and popular class of ambiguity-sensitive preferences (the c-linearly biseparable class. This implies, for example, that maxmin expected utility preferences are consistent with monotonicity in optimal mixtures if and only if they are subjective expected utility preferences. This incompatibility is not between monotonicity in optimal mixtures and ambiguity aversion per se. For example, we show that smooth ambiguity preferences can satisfy both properties as long as they are not too ambiguity averse. Our most general result, applying to an extremely broad universe of preferences, shows a sense in which monotonicity in optimal mixtures places upper bounds on the intensity of ambiguity-averse behavior. This paper was accepted by Manel Baucells, decision analysis.

Full Implementation under Ambiguity

2021 ◽  
Vol 13 (1) ◽  
pp. 148-178
Author(s):  
Huiyi Guo ◽  
Nicholas C. Yannelis
Keyword(s):  
Social Choice ◽  
Expected Utility ◽  
Sufficient Conditions ◽  
Choice Functions ◽  
Maxmin Expected Utility ◽  
Special Cases ◽  
Social Choice Functions ◽  
Bayesian Implementation ◽  
Pareto Efficient ◽  
Choice Set

This paper introduces the maxmin expected utility framework into the problem of fully implementing a social choice set as ambiguous equilibria. Our model incorporates the Bayesian framework and the Wald-type maxmin preferences as special cases and provides insights beyond the Bayesian implementation literature. We establish necessary and almost sufficient conditions for a social choice set to be fully implementable. Under the Wald-type maxmin preferences, we provide easy-to-check sufficient conditions for implementation. As applications, we implement the set of ambiguous Pareto-efficient and individually rational social choice functions, the maxmin core, the maxmin weak core, and the maxmin value. (JEL D71, D81, D82)

scholarly journals Testing Ambiguity Models through the Measurement of Probabilities for Gains and Losses

2015 ◽  
Vol 7 (2) ◽  
pp. 77-100 ◽  
Author(s):  
Aurélien Baillon ◽  
Han Bleichrodt
Keyword(s):  
Expected Utility ◽  
Ambiguity Aversion ◽  
Choquet Expected Utility ◽  
Maxmin Expected Utility ◽  
Stock Indices ◽  
Descriptive Validity ◽  
Utility Models ◽  
Ambiguity Attitudes ◽  
Gains And Losses ◽  
Fourfold Pattern

This paper reports on two experiments that test the descriptive validity of ambiguity models using a natural source of uncertainty (the evolution of stock indices) and both gains and losses. We observed violations of probabilistic sophistication, violations that imply a fourfold pattern of ambiguity attitudes: ambiguity aversion for likely gains and unlikely losses and ambiguity seeking for unlikely gains and likely losses. Our data are most consistent with prospect theory and, to a lesser extent, α-maxmin expected utility and Choquet expected utility. Models with uniform ambiguity attitudes are inconsistent with most of the observed behavioral patterns. (JEL D81, D83, G11, G12, G14)

scholarly journals Optimal Insurance under Maxmin Expected Utility

2020 ◽  
Author(s):  
Corina Birghila ◽  
Tim J. Boonen ◽  
Mario Ghossoub
Keyword(s):  
Expected Utility ◽  
Maxmin Expected Utility ◽  
Optimal Insurance

Purely subjective Maxmin Expected Utility

2014 ◽  
Vol 152 ◽  
pp. 382-412 ◽  
Author(s):  
Shiri Alon ◽  
David Schmeidler
Keyword(s):  
Expected Utility ◽  
Maxmin Expected Utility

scholarly journals Maxmin expected utility with non-unique prior

1989 ◽  
Vol 18 (2) ◽  
pp. 141-153 ◽  
Author(s):  
Itzhak Gilboa ◽  
David Schmeidler
Keyword(s):  
Expected Utility ◽  
Maxmin Expected Utility

scholarly journals Discriminating Between Models of Ambiguity Attitude: a Qualitative Test

2019 ◽  
Vol 18 (2) ◽  
pp. 708-749 ◽  
Author(s):  
Robin Cubitt ◽  
Gijs van de Kuilen ◽  
Sujoy Mukerji
Keyword(s):  
Economic Theory ◽  
Expected Utility ◽  
Maxmin Expected Utility ◽  
Smooth Ambiguity Model ◽  
New Models ◽  
Qualitative Test ◽  
Behavioral Issue ◽  
Ambiguity Attitude

AbstractDuring recent decades, many new models have emerged in pure and applied economic theory according to which agents’ choices may be sensitive to ambiguity in the uncertainty that faces them. The exchange between Epstein (2010) and Klibanoff et al. (2012) identified a notable behavioral issue that distinguishes sharply between two classes of models of ambiguity sensitivity that are importantly different. The two classes are exemplified by the α-maxmin expected utility (MEU) model and the smooth ambiguity model, respectively; and the issue is whether or not a desire to hedge independently resolving ambiguities contributes to an ambiguity-averse agent's preference for a randomized act. Building on this insight, we implement an experiment whose design provides a qualitative test that discriminates between the two classes of models. Among subjects identified as ambiguity sensitive, we find greater support for the class exemplified by the smooth ambiguity model; the relative support is stronger among subjects identified as ambiguity averse. This finding has implications for applications that rely on specific models of ambiguity preference.

Ambiguity Models and the Machina Paradoxes

2011 ◽  
Vol 101 (4) ◽  
pp. 1547-1560 ◽  
Author(s):  
AurÉlien Baillon ◽  
Olivier L'Haridon ◽  
Laetitia Placido
Keyword(s):  
Expected Utility ◽  
Ambiguity Aversion ◽  
Choquet Expected Utility ◽  
Maxmin Expected Utility ◽  
Alternative Representation ◽  
Smooth Model ◽  
Variational Preferences

Machina (2009) introduced two examples that falsify Choquet expected utility, presently one of the most popular models of ambiguity. This article shows that Machina's examples falsify not only the model mentioned, but also four other popular models for ambiguity of the literature, namely maxmin expected utility, variational preferences, α-maxmin, and the smooth model of ambiguity aversion. Thus, Machina's examples pose a challenge to most of the present field of ambiguity. Finally, the paper discusses how an alternative representation of ambiguity-averse preferences works to accommodate the Machina paradoxes and what drives the results. (JEL D81)

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