The Relative Contributions of Private Information Sharing and Public Information Releases to Information Aggregation
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Author(s)
Duffie, Darrell
Malamud, Semyon
Manso, Gustavo
Date Issued
November 2009
Journal
Journal of Economic Theory
Publisher
Elsevier
Citation
Duffie, Darrell, Semyon Malamud, and Gustavo Manso. “The Relative Contributions of Private Information Sharing and Public Information Releases to Information Aggregation.” Journal of Economic Theory 145.4 (2010) : 1574-1601.
Version
Author's final manuscript
Abstract
We calculate learning rates when agents are informed through both public and
private observation of other agents’ actions. We provide an explicit solution for
the evolution of the distribution of posterior beliefs. When the private learning
channel is present, we show that convergence of the distribution of beliefs to the
perfect-information limit is exponential at a rate equal to the sum of the mean
arrival rate of public information and the mean rate at which individual agents are
randomly matched with other agents. If, however, there is no private information
sharing, then convergence is exponential at a rate strictly lower than the mean
arrival rate of public information.
MIT Department
Sloan School of Management
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1016/j.jet.2009.10.017
