Non-Bayesian updating: A theoretical framework

This paper models an agent in a multi-period setting who does not update according to Bayes' Rule, and who is self-aware and anticipates her updating behavior when formulating plans. Choice-theoretic axiomatic foundations are provided to capture updating biases that reflect excessive weight given to either prior beliefs, or alternatively, to observed data. A counterpart of the exchangeable Bayesian learning model is also described.

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Year of publication:	2008
Authors:	Epstein, Larry G. ; Noor, Jawwad ; Sandroni, Alvaro
Published in:	Theoretical Economics. - New York, NY : The Econometric Society, ISSN 1555-7561. - Vol. 3.2008, 2, p. 193-229
Publisher:	New York, NY : The Econometric Society
Subject:	Non-Bayesian updating \| temptation and self-control \| overreaction \| underreaction \| learning \| law of small numbers

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Type of publication:	Article
Type of publication (narrower categories):	Article
Language:	English
Other identifiers:	895407930 [GVK] hdl:10419/150110 [Handle] RePEc:the:publsh:253 [RePEc]
Classification:	D81 - Criteria for Decision-Making under Risk and Uncertainty
Source:	EconStor

Persistent link: https://www.econbiz.de/10011599401