Author:
Grant Simon,Meneghel Idione,Tourky Rabee
Abstract
AbstractWe propose a model of learning when experimentation is possible, but unawareness and ambiguity matter. In this model, complete lack of information regarding the underlying data generating process is expressed as a (maximal) family of priors. These priors yield posterior inferences that become more precise as more information becomes available. As information accumulates, however, the individual’s level of awareness as encoded in the state space may expand. Such newly learned states are initially seen as ambiguous, but as evidence accumulates there is a gradual reduction of ambiguity.
Funder
Australian National University
Publisher
Springer Science and Business Media LLC
Subject
Economics and Econometrics
Cited by
5 articles.
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