Multi-Dimensional Social Learning

Manuel Mueller-Frank and Itai Arieliy ()
Additional contact information
Itai Arieliy: Faculty of Industrial Engineering, Technion- Israel Institute of Technology, Postal: Haifa, 3200003, Israel

No D/1117, IESE Research Papers from IESE Business School

Abstract: This paper provides a model of social learning where the order in which actions are taken is determined by an m-dimensional integer lattice rather than along a line as in the sequential social learning model. The observation structure is determined by a random network. Every agent links to each of his preceding lattice neighbors independently with probability p, and observes the actions of all agents that are reachable via a directed path in the realized social network. We establish a strong discontinuity of learning with respect to the linkage probability. If p is close to but di¤erent from one an arbitrary high proportion of agents select the optimal action in the limit, for any informative signal structure. For bounded signals and a linkage probability equal to one, however, there exists a positive probability that all agents select the suboptimal action. We also show that for every p

Keywords: Social Learning; Lattice; informational cascades (search for similar items in EconPapers)
Pages: 37 pages
Date: 2015-02-27
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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http://www.iese.edu/research/pdfs/WP-1117-E.pdf (application/pdf)

Related works:
Journal Article: Multidimensional Social Learning (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:ebg:iesewp:d-1117

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