Template-Type: ReDIF-Paper 1.0

Author-Name: Larry G. Epstein
Author-X-Name-First: Larry
Author-X-Name-Last: Epstein
Author-Email: lepn@troi.cc.rochester.edu
Author-Workplace-Name: Department of Economics, University of Rochester

Author-Name: Jawwad Noor
Author-X-Name-First: Jawwad
Author-X-Name-Last: Noor
Author-Email: jnoor@bu.edu
Author-Workplace-Name: Department of Economics, Boston University

Author-Name: Alvaro Sandroni
Author-X-Name-First: Alvaro
Author-X-Name-Last: Sandroni
Author-Email: sandroni@kellogg.northwestern.edu
Author-Workplace-Name: Kellogg School of Management

Title: NON-BAYESIAN UPDATING: A THEORETICAL FRAMEWORK

Abstract: 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. Then the model is specialized axiomatically to
capture updating biases that reflect excessive weight given to (i) prior be-
liefs, or alternatively, (ii) the realized sample. Finally, the paper describes
a counterpart of the exchangeable Bayesian model, where the agent tries
to learn about parameters, and some answers are provided to the question 
what does a non-Bayesian updater learn?


Length: 50 pages
Creation-Date: 2005-10
Revision-Date: 
Publication-Status:
File-URL: http://people.bu.edu/jnoor/research/past-updting52.pdf
File-Format: Application/pdf
File-Function: 
Number: WP2005-049
Classification-JEL: 
Keywords: 
Handle: RePEc:bos:wpaper:WP2005-049