The Likelihood Method for Decision under Uncertainty

M. Abdellaoui*, P.P. Wakker

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This paper introduces the likelihood method for decision under uncertainty. The method allows the quantitative determination of subjective beliefs or decision weights without invoking additional separability conditions, and generalizes the savage–de finetti betting method. It is applied to a number of popular models for decision under uncertainty. In each case, preference foundations result from the requirement that no inconsistencies are to be revealed by the version of the likelihood method appropriate for the model considered. A unified treatment of subjective decision weights results for most of the decision models popular today. Savage’s derivation of subjective expected utility can now be generalized and simplified. In addition to the intuitive and empirical contributions of the likelihood method, we provide a number of technical contributions: we generalize savage’s nonatomiticy condition (“p6”) and his assumption of (sigma) algebras of events, while fully maintaining his flexibility regarding the outcome set. Derivations of choquet expected utility and probabilistic sophistication are generalized and simplified similarly. The likelihood method also reveals a common intuition underlying many other conditions for uncertainty, such as definitions of ambiguity aversion and pessimism.
Original languageEnglish
Pages (from-to)03-076
Number of pages72
JournalTheory and Decision
Volume58
DOIs
Publication statusPublished - 1 Jan 2005

Fingerprint

Dive into the research topics of 'The Likelihood Method for Decision under Uncertainty'. Together they form a unique fingerprint.

Cite this