Generalized expected utility is adecision-making metric based on any of a variety of theories that attempt to resolve some discrepancies betweenexpected utility theory andempirical observations, concerning choice underrisky (probabilistic) or uncertain circumstances. Given its motivations and approach, generalized expected utility theory may properly be regarded as a subfield ofbehavioral economics, but it is more frequently located within mainstreameconomic theory.
The expected utility model developed byJohn von Neumann andOskar Morgenstern dominated decision theory from its formulation in 1944 until the late 1970s, not only as aprescriptive, but also as adescriptive model, despite powerful criticism fromMaurice Allais andDaniel Ellsberg who showed that, in certain choice problems, decisions were usually inconsistent with the axioms of expected utility theory. These problems are usually referred to as theAllais paradox andEllsberg paradox.
Beginning in 1979 with the publication of theprospect theory ofDaniel Kahneman andAmos Tversky, a range of generalized expected utility models were developed with the aim of resolving the Allais and Ellsberg paradoxes, while maintaining many of the attractive properties of expected utility theory. Important examples were anticipated utility theory, later referred to asrank-dependent utility theory,[1] weighted utility (Chew 1982), and expected uncertain utility theory.[2] A general representation, using the concept of the local utility function was presented byMark J. Machina.[3] Since then, generalizations of expected utility theory have proliferated, but the probably most frequently used model is nowadayscumulative prospect theory, a rank-dependent development of prospect theory, introduced in 1992 byDaniel Kahneman andAmos Tversky.
