Belief revision generalized: A joint characterization of Bayes' and Jeffrey's rules

Franz Dietrich, Christian List and Richard Bradley

Journal of Economic Theory, 2016, vol. 162, issue C, 352-371

Abstract: We present a general framework for representing belief-revision rules and use it to characterize Bayes' rule as a classical example and Jeffrey's rule as a non-classical one. In Jeffrey's rule, the input to a belief revision is not simply the information that some event has occurred, as in Bayes' rule, but a new assignment of probabilities to some events. Despite their differences, Bayes' and Jeffrey's rules can be characterized in terms of the same axioms: responsiveness, which requires that revised beliefs incorporate what has been learnt, and conservativeness, which requires that beliefs on which the learnt input is ‘silent’ do not change. To illustrate the use of non-Bayesian belief revision in economic theory, we sketch a simple decision-theoretic application.

Keywords: Belief revision; Subjective probability; Bayes' and Jeffrey's rules; Axiomatic foundations; Fine-grained versus coarse-grained beliefs; Unawareness (search for similar items in EconPapers)
JEL-codes: C73 D01 D80 D81 D83 D90 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Working Paper: Belief revision generalized: A joint characterization of Bayes' and Je¤rey's rules (2016)
Working Paper: Belief revision generalized: A joint characterization of Bayes' and Je¤rey's rules (2016)
Working Paper: Belief revision generalized: A joint characterization of Bayes' and Je¤rey's rules (2016)
Working Paper: Belief revision generalized: a joint characterization of Bayes's and Jeffrey's rules (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:162:y:2016:i:c:p:352-371

DOI: 10.1016/j.jet.2015.11.006

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