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14 - Extensions of the Subjective Expected Utility Model

Published online by Cambridge University Press:  05 June 2012

By
Robert F. Nau
Edited by
Ward Edwards ,
Ralph F. Miles Jr.  and
Detlof von Winterfeldt
Robert F. Nau
Affiliation:
Fuqua School of Business, Duke University
Ralph F. Miles Jr.
Affiliation:
California Institute of Technology
Detlof von Winterfeldt
Affiliation:
University of Southern California
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Summary

ABSTRACT. The subjective expected utility (SEU) model rests on very strong assumptions about the consistency of decision making across a wide range of situations. The descriptive validity of these assumptions has been extensively challenged by behavioral psychologists during the last few decades, and the normative validity of the assumptions has also been reappraised by many statisticians, philosophers, and economists, motivating the development of more general utility theories and decision models. These generalized models are characterized by features such as imprecise probabilities, nonlinearly weighted probabilities, source-dependent risk attitudes, and state-dependent utilities, permitting the pattern of the decision maker's behavior to change with the decision context and to perhaps satisfy the usual SEU assumptions only locally. Recent research in the emerging field of neuroeconomics sheds light on the physiological basis of decision making, the nature of preferences and beliefs, and interpersonal differences in decision competence. These findings do not necessarily invalidate the use of SEU-based decision analysis tools, but they suggest that care needs to be taken to structure preferences and to assess beliefs and risk attitudes in a manner that is appropriate for the decision and also for the decision maker.

The SEU model and its assumptions

The subjective expected utility (SEU) model provides the conceptual and computational framework that is most often used to analyze decisions under uncertainty. In the SEU model, uncertainty about the future is represented by a set of states of the world, which are mutually exclusive and exhaustive events.

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Advances in Decision Analysis
From Foundations to Applications
 , pp. 253 - 278
Publisher: Cambridge University Press
Print publication year: 2007

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