Social learning with course inference

Social learning with course inference
Document type
Working Paper
Author(s)
Guarino, Antonio; Jehiel, Philippe
Publisher
Birkbeck, University of London
Date of publication
1 July 2009
Series
World Economy & Finance Research Programme Working Paper Series
Subject(s)
Trends: economic, social and technology trends affecting business
Collection
Business and management
Material type
Reports

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This 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 understand their predecessors’ decisions in their finest details: they only understand the relation between the aggregate distribution of actions and the state of nature. We show that, in a continuous action space, compared to the rational case, agents put more weight on early signals. Despite this
behavioral bias, beliefs converge to the truth. In a discrete action space, instead, convergence to the truth does not occur even if agents receive signals of unbounded precisions. 

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