Strategic Learning and the Topology of Social Networks

Elchanan Mossel, Allan Sly and Omer Tamuz

Econometrica, 2015, vol. 83, issue 5, 1755-1794

Abstract: We consider a group of strategic agents who must each repeatedly take one of two possible actions. They learn which of the two actions is preferable from initial private signals and by observing the actions of their neighbors in a social network. We show that the question of whether or not the agents learn efficiently depends on the topology of the social network. In particular, we identify a geometric “egalitarianism” condition on the social network that guarantees learning in infinite networks, or learning with high probability in large finite networks, in any equilibrium. We also give examples of nonegalitarian networks with equilibria in which learning fails.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (42)

Downloads: (external link)
http://hdl.handle.net/

Related works:
Working Paper: Strategic Learning and the Topology of Social Networks (2015)
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:wly:emetrp:v:83:y:2015:i:5:p:1755-1794

Ordering information: This journal article can be ordered from
https://www.economet ... ordering-back-issues

Access Statistics for this article

Econometrica is currently edited by Guido W. Imbens

More articles in Econometrica from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().