Search

Complexity of the problem of choosing among uncertain acts is a salient feature of many of the environments in which departures from expected utility theory are observed. I study a class of Generalized Simple Bounds preferences in which acts that are complex from the perspective of the decision maker are bracketed by "simple" acts to which they are related by statewise dominance. I then study a refinement of the model in which the size of the partition with respect to which an act is measurable arises endogenously as a measure of subjective complexity. Finally, I consider choice behavior characterized by a "cautious completion" of Simple Bounds preferences, and discuss the relationship between this model and models of ambiguity aversion. I develop general comparative statics results, and explore applications to portfolio choice and insurance choice. • Problems of choice problems under uncertainty are complex. • From behavioral axioms, I characterize the set of acts that are well-understood. • Decision makers use acts they understand well to bracket those they do not. • The model is tractable, and admits rich comparative statics. • The model helps explain observed choice patterns in applications. [ABSTRACT FROM AUTHOR]

Abstract: We consider a decision maker facing uncertainty which behaves as a subjective expected utility maximizer. The value of information is traditionally captured as a greater expected utility the decision maker can achieve by selecting a best strategy as information arrives. We deal with the limit process of being better informed, and introduce an information density function depending solely on the states that gives an exact least upper bound to being more informed. This information density function is given by a Radon–Nikodym-type theorem for set functions and is explicitly computed for the countable case. [Copyright &y& Elsevier]