Ordinal utility models of decision making under uncertainty

This paper studies two models of rational behavior under uncertainty whose predictions are invariant under ordinal transformations of utility. The quantile utility model assumes that the agent maximizes some quantile of the distribution of utility. The utility mass model assumes maximization of the probability of obtaining an outcome whose utility is higher than some fixed critical value. Both models satisfy weak stochastic dominance. Lexicographic refinements satisfy strong dominance.The study of these utility models suggests a significant generalization of traditional ideas of riskiness and risk preference. We define one action to be riskier than another if the utility distribution of the latter crosses that of the former from below. The single crossing property is equivalent to a minmax spread of a random variable. With relative risk defined by the single crossing criterion, the risk preference of a quantile utility maximizer increases with the utility distribution quantile that he maximizes. The risk preference of a utility mass maximizer increases with his critical utility value.     

Choice under risk and the security factor: An axiomatic model

The particular attention paid by decision makers to the security level ensured by each decision under risk, which is responsible for the certainty effect, can be taken into account by weakening the independence and continuity axioms of expected utility theory. In the resulting model, preferences depend on: (i) the security level, (ii) the expected utility, offered by each decision. Choices are partially determined by security level comparison and completed by the maximization of a function, which express the existing tradeoffs between expected utility and security level, and is, at a given security level, an affine function of the expected utility. In the model, risk neutrality at a given security level implies risk aversion.     

Testing between alternative models of choice under uncertainty—Comment

Battaglio, Kagel, and Jiranyakul use experimental tests to compare rank-dependent expected utility (RDEU), regret theory, prospect theory, and Machina's generalized smooth preferences model. They conclude that none of these models consistently organizes the data. The purpose of this note is to point out that RDEU theory was tested in combination with a hypothesis on the choice of functional form that has been explicitly rejected by the original author of the model (Quiggin, 1982, 1987). When the original form of RDEU theory is tested, it performs quite well.     

Testing between alternative models of choice under uncertainty: Some initial results

Experiments have identified a number of well-known violations of expected utility theory, giving rise to alternative models of choice under uncertainty, all of which are able to explain these violations. In this article, predictions of several prominent rival formulations are examined. No single alternative consistently organizes choices. Among the more important inconsistencies, we identify conditions generating systematic fanning in of indifference curves in the unit probability triangle, and find risk-loving over a number of gambles with all positive payoffs, in cases where prospect theory predicts risk aversion.     

Under stochastic dominance Choquet-expected utility and anticipated utility are identical

The aim of this paper is to convince the reader that Choquet-expected utility, as initiated by Schmeidler (1982, 1989) for decision making under uncertainty, when formulated for decision making under risk naturally leads to anticipated utility, as initiated by Quiggin/Yaari. Thus the two generalizations of expected utility in fact are one.     

Expected utility with lower probabilities

An uncertain and not just risky situation may be modeled using so-called belief functions assigning lower probabilities to subsets of outcomes. In this article we extend the von Neumann-Morgenstern expected utility theory from probability measures to belief functions. We use this theory to characterize uncertainty neutrality and different degrees of uncertainty aversion.We are grateful to Birgit Grodal, Salvatore Modica, David Schmeidler, and an anonymous referee for comments, help, and encouragement. Financial support from the Danish Social Sciences Research Council is acknowledged.     

Prospective reference theory: Toward an explanation of the paradoxes

This article develops a variant of the expected utility model termed prospective reference theory. Although the standard model occurs as a limiting case, the general approach is that individuals treat stated experimental probabilities as imperfect information. This model is applied to a wide variety of aberrant phenomena, including the Allais paradox, the overweighting of low-probability events, the existence of premiums for certain elimination of risks, and the representativeness heuristic. The prospective reference theory model predicts most of the observed behavioral patterns rather than being potentially reconcilable with such phenomena.Kenneth Arrow and Robert Viscusi provided helpful comments. A preliminary version of this article was presented at the 1987 AEA meetings.     

Granny Versus Game Theorist: Ambiguity in Experimental Games

We report on an experiment in which subjects choose actions in strategic games with either strategic complements or substitutes against a granny, a game theorist or other subjects. The games are selected in order to test predictions on the comparative statics of equilibrium with respect to changes in strategic ambiguity. We find that subjects face higher ambiguity while playing against the granny than playing against the game theorist if we assume that subjects are ambiguity averse. Moreover, under the same assumption, subjects choose more secure actions in games more prone to ambiguity which is in line with the predictions.      

Risk,ambiguity, and insurance

In a series of experiments, economically sophisticated subjects, including professional actuaries, priced insurance both as consumers and as firms under conditions of ambiguity. Findings support implications of the Einhorn-Hogarth ambiguity model: (1) For low probability-of-loss events, prices of both consumers and firms indicated aversion to ambiguity; (2) As probabilities of losses increased, aversion to ambiguity decreased, with consumers exhibiting ambiguity preference for high probability-of-loss events; and (3) Firms showed greater aversion to ambiguity than consumers. The results are shown to be incompatible with traditional economic analysis of insurance markets and are discussed with respect to the effects of ambiguity on the supply and demand for insurance.University of Chicago Graduate School of BusinessUniversity of Pennsylvania The Wharton School     

Uncertainty aversion and aversion to increasing uncertainty

According to the original Ellsberg (1961) examples there is uncertainty version if the decision maker prefers to bet on an urn of known composition rather than on an urn of unknown composition. According to another definition (Schmeidler, 1989), there is uncertainty aversion if any convex combination of two acts is preferred to the least favorable of these acts. We show that these two definitions differ: while the first one truly refers to uncertainty aversion, the second one refers to aversion to increasing uncertainty. Besides, with reference to Choquet Expected Utility theory, uncertainty aversion means that there exists the core of a capacity, while aversion to increasing uncertainty means that the capacity is convex. Consequently, aversion to increasing uncertainty implies uncertainty aversion, but the opposite does not hold. We also show that a completely analogous situation holds for the case of risk and we define a set of risk and uncertainty premiums according to the previous analysis.     

Preferences for information on probabilities versus prizes: The role of risk-taking attitudes

Many real-world decisions entail choices between information on either probabilities or payoffs (i.e., prizes). Simplified versions of such decisions are examined to gain insight into preferences for different types of information as a function of risk-attitudes. General and simple decision rules are derived for cases where the utility function is concave (or convex) over the relevant payoff interval.The article further describes several experiments to test business students' intuitions concerning these optimal decision rules. In general, risk-taking attitudes did not correlate significantly with subjects' preferences for information, in violation of theorems regarding mean-preserving spreads of risk. Other tests, e.g., narrowing certain probability ranges, also resulted in preferences contrary to expected utility (EU) theory.     

A variational model of preference under uncertainty

A familiar example devised by Daniel Ellsberg to highlight the effects of event ambiguity on preferences is transformed to separate aleatory uncertainty (chance) from epistemic uncertainty. The transformation leads to a lottery acts model whose states involve epistemic uncertainty; aleatory uncertainty enters into the statedependent lotteries. The model proposes von Neumann-Morgenstern utility for lotteries, additive subjective probability for states, and the use of across-states standard deviation weighted by a coefficient of aversion to variability to account for departures from Anscombe-Aumann subjective expected utility. Properties of the model are investigated and a partial axiomatization is provided.     

A foundation of Bayesian statistics (How to deal with fears)

A rational statistical decision maker whose preferences satisfy Savage's axioms will minimize a Bayesian risk function: the expectation with respect to a revealed (or subjective) probability distribution of a loss (or negative utility) function over the consequences of the statistical decision problem. However, the nice expected utility form of the Bayesian risk criterion is nothing but a representation of special preferences. The subjective probability is defined together with the utility (or loss) function and it is not possible, in general, to use a given loss function - say a quadratic loss - and to elicit independently a subjective distribution.I construct the Bayesian risk criterion with a set of five axioms, each with a simple mathematical implication. This construction clearly shows that the subjective probability that is revealed by a decider's preferences is nothing but a (Radon) measure equivalent to a linear functional (the criterion). The functions on which the criterion operates are expected utilities in the von Neumann-Morgenstern sense. It then becomes clear that the subjective distribution cannot be eliciteda priori, independently of the utility function on consequences.However, if one considers a statistical decision problem by itself, losses, defined by a given loss function, become the consequences of the decisions. It can be imagined that experienced statisticians are used to dealing with different losses and are able to compare them (i.e. have preferences, or fears over a set of possible losses). Using suitable axioms over these preferences, one can represent them by a (linear) criterion: this criterion is the expectation of losses with respect to a (revealed) distribution. It must be noted that such a distribution is a measure and need not be a probability distribution.     

The Firm Under Uncertainty with General Risk-Averse Preferences: A State-Contingent Approach

This paper summarizes and synthesizes recent developments in the state-contingent theory of production under uncertainty presented by Chambers and Quiggin (2000) with a particular focus on the case of generalized expected utility preferences. The problem of the risk-averse firm under price and production uncertainty is analyzed using a state-contingent production technology and general risk-averse preferences. The concept of an efficient frontier, which identifies all potentially optimal production plans for weakly risk-averse decisionmakers, is introduced and used to develop comparative static results. For constant absolute risky technologies, the efficient frontier is shown to correspond to a unique isocost contour.     

Utility Functions for Wealth

We specify all utility functions on wealth implied by four special conditions on preferences between risky prospects in four theories of utility, under the presumption that preference increases in wealth. The theories are von Neumann-Morgenstern expected utility (EU), rank dependent utility (RDU), weighted linear utility (WLU), and skew-symmetric bilinear utility (SSBU). The special conditions are a weak version of risk neutrality, Pfanzagl's consistency axiom, Bell's one-switch condition, and a contextual uncertainty condition. Previous research has identified the functional forms for utility of wealth for all four conditions under EU, and for risk neutrality and Pfanzagl's consistency axiom under WLU and SSBU. The functional forms for the other condition-theory combinations are derived in this paper.     

A Method for Eliciting Utilities and its Application to Collective Choice

Designing a mechanism that provides a direct incentive for an individual to report her utility function over several alternatives is a difficult task. A framework for such mechanism design is the following: an individual (a decision maker) is faced with an optimization problem (e.g., maximization of expected utility), and a mechanism designer observes the decision maker’s action. The mechanism does reveal the individual’s utility truthfully if the mechanism designer, having observed the decision maker’s action, infers the decision maker’s utilities over several alternatives. This paper studies an example of such a mechanism and discusses its application to the problem of optimal social choice. Under certain simplifying assumptions about individuals’ utility functions and about how voters choose their voting strategies, this mechanism selects the alternative that maximizes Harsanyi’s social utility function and is Pareto-efficient.     

Decision problems under uncertainty based on entropy functionals

This essay intends to define the role of entropy, in particular, the role of the maximum entropy criterion with respect to decision analysis and information economics. By considering the average opportunity loss interpretation, the basic hypothesis for Shannon's derivation can be derived from properties of decision problems. Using the representation Bayes Boundary it is possible to show that selecting a single probability from a set by the Maximum Entropy Criterion corresponds to a minimax criterion for decision-making. Since problems of randomly accessing and storing information as well as communicating information can often be stated in terms of coding problems, this result might be used to develop strategies for minimizing retrieval time or communication costs.     

Preference for gradual resolution of uncertainty

Analyses of preference for the timing of uncertainty resolution usually assumes all uncertainty to resolve in one point in time. More realistically, uncertainty should be modelled to resolve gradually over time. Kreps and Porteus (1978) have introduced an axiomatically based model of time preference which can explain preferences for gradual uncertainty resolution. This paper presents an experimental test of the Kreps-Porteus model. We derive implications of the model relating preferences for gradual and one-time resolving lotteries. Our data do not support the Kreps-Porteus model but show that some of the behaviour observed may be explained by similarity heuristics.     

Preference Reversals and Induced Risk Preferences: Evidence for Noisy Maximization

We combine two research lines: preference reversal research (Lichtenstein and Slovic, 1971) and research on lottery-based risk preference induction (Roth and Malouf, 1979). Our results are informative for both research lines. We show that inducing risk preferences in preference reversal experiments has dramatic effects. First, while our subjects still display reversals, they do not display the usual pattern of predicted reversals suggested by the compatibility hypothesis. By inducing risk averse and risk loving preferences, we can dramatically reduce reversal rates and even produce the opposite pattern of reversals. Our results are consistent with the assumption that subjects maximize expected utility with error. This provides evidence that Camerer and Hogarth's (1999) framework for incentive effects can be extended to include the risk preference induction reward scheme.     

The Aversion to the Sequential Resolution of Uncertainty

This paper sets forth and offers an explanation for preferences for the form of the timing of resolution of uncertainty; namely for uncertainty to be resolved all at one time rather than sequentially. The explanation is based on a weakening of the independence axiom, in particular on the notion of disappointment aversion developed in Gul's (1991) axiomatic model of preferences. Implications of this aversion are discussed for issues in finance, intertemporal decision making under uncertainty, high stakes risky situations and consumer self-regulation. The analysis encourages a formulation of preferences over all attributes of interest to the decision maker, including psychological satisfaction.