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Social Learning with Coarse Inference

Social Learning with Coarse Inference Abstract We study social learning by boundedly rational agents. Agents take a decision in sequence, after observing their predecessors and a private signal. They are unable to make perfect inferences from their predecessors' decisions: they only understand the relation between the aggregate distribution of actions and the state of nature, and make their inferences accordingly. We show that, in a discrete action space, even if agents receive signals of unbounded precision, there are asymptotic inefficiencies. In a continuous action space, compared to the rational case, agents overweight early signals. Despite this behavioral bias, eventually agents learn the realized state of the world and choose the correct action. (JEL D82, D83 ) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Economic Journal: Microeconomics American Economic Association

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References (36)

Publisher
American Economic Association
Copyright
Copyright © 2013 by the American Economic Association
Subject
Articles
ISSN
1945-7685
eISSN
1945-7685
DOI
10.1257/mic.5.1.147
Publisher site
See Article on Publisher Site

Abstract

Abstract We study social learning by boundedly rational agents. Agents take a decision in sequence, after observing their predecessors and a private signal. They are unable to make perfect inferences from their predecessors' decisions: they only understand the relation between the aggregate distribution of actions and the state of nature, and make their inferences accordingly. We show that, in a discrete action space, even if agents receive signals of unbounded precision, there are asymptotic inefficiencies. In a continuous action space, compared to the rational case, agents overweight early signals. Despite this behavioral bias, eventually agents learn the realized state of the world and choose the correct action. (JEL D82, D83 )

Journal

American Economic Journal: MicroeconomicsAmerican Economic Association

Published: Feb 1, 2013

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