Observational Learning in Large Anonymous Games

Ignacio Monzon

No 509, Carlo Alberto Notebooks from Collegio Carlo Alberto

Abstract: I present a model of observational learning with payoff interdependence. Agents, ordered in a sequence, receive private signals about an uncertain state of the world and sample previous actions. Unlike in standard models of observational learning, an agent’s payoff depends both on the state and on the actions of others. Agents want both to learn the state and to anticipate others’ play. As the sample of previous actions provides information on both dimensions, standard informational externalities are confounded with coordination motives. I show that in spite of these confounding factors, when signals are of unbounded strength there is learning in a strong sense: agents’ actions are ex-post optimal given both the state of the world and others’ actions. With bounded signals, actions approach ex-post optimality as the signal structure becomes more informative.

Keywords: observational learning; payoff interdependence; information aggregation; position uncertainty. (search for similar items in EconPapers)
JEL-codes: C72 D83 D85 (search for similar items in EconPapers)
Pages: pages 43
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.carloalberto.org/wp-content/uploads/2018/11/no.509.pdf (application/pdf)

Related works:
Journal Article: Observational learning in large anonymous games (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cca:wpaper:509

Access Statistics for this paper

More papers in Carlo Alberto Notebooks from Collegio Carlo Alberto Contact information at EDIRC.
Bibliographic data for series maintained by Giovanni Bert ().