Title

Evaluating Ambiguous Random Variables and Updating by Proxy

Author(s)

Faruk Gul Faruk Gul (Princeton University)

Wolfgang Pesendorfer Wolfgang Pesendorfer (Princeton University)

Abstract

We introduce a new theory of belief revision under ambiguity. It is recursive (random variables are evaluated by backward induction) and consequentialist (the conditional expectation of any random variable depends only on the values the random variable attains on the conditioning event). Agents experience no change in preferences but may not be indifferent to the timing of resolution of uncertainty. We provide three main theorems: the first relates our rule to standard Bayesian updating; the others characterize the dynamic behavior of an agent who adopts our rule.

Creation Date

2018-06

Section URL ID

Paper Number

2018-7

URL

http://www.princeton.edu/~pesendor/Updating.pdf

File Function

Jel

D01

Keyword(s)

Radom Variables, Ambiguity

Suppress

false

Series

13