Abstract
First, this paper introduces and axiomatizes range-dependent utility as a new conceptual framework for decision making under risk. It is a simple and well-defined generalization of expected utility theory in which utility depends on the range of lottery outcomes. Second, a special case of this framework is proposed for prediction. It is based on applying a single utility function (decision utility) to every normalized lottery range. The resultant decision utility model predicts well-known expected utility paradoxes without recourse to probability weighting. Necessary and sufficient conditions for the model to satisfy monotonicity with respect to first-order stochastic dominance are identified. The typical decision utility function, which is confirmed by both experimental data and normative considerations, is S shaped. This paper was accepted by Manel Baucells, decision analysis.
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