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