IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Dynamics of Information Exchange in Endogenous Social Networks

  • Daron Acemoglu
  • Kostas Bimpikis
  • Asuman Ozdaglar

We develop a model of information exchange through communication and investigate its implications for information aggregation in large societies. An underlying state determines payoffs from different actions. Agents decide which others to form a costly communication link with incurring the associated cost. After receiving a private signal correlated with the underlying state, they exchange information over the induced communication network until taking an (irreversible) action. We define asymptotic learning as the fraction of agents taking the correct action converging to one in probability as a society grows large. Under truthful communication, we show that asymptotic learning occurs if (and under some additional conditions, also only if) in the induced communication network most agents are a short distance away from "information hubs", which receive and distribute a large amount of information. Asymptotic learning therefore requires information to be aggregated in the hands of a few agents. We also show that while truthful communication may not always be a best response, it is an equilibrium when the communication network induces asymptotic learning. Moreover, we contrast equilibrium behavior with a socially optimal strategy profile, i.e., a profile that maximizes aggregate welfare. We show that when the network induces asymptotic learning, equilibrium behavior leads to maximum aggregate welfare, but this may not be the case when asymptotic learning does not occur. We then provide a systematic investigation of what types of cost structures and associated social cliques (consisting of groups of individuals linked to each other at zero cost, such as friendship networks) ensure the emergence of communication networks that lead to asymptotic learning. Our result shows that societies with too many and sufficiently large social cliques do not induce asymptotic learning, because each social clique would have sufficient information by itself, making communication with others relatively unattractive. Asymptotic learning results if social cliques are neither too numerous nor too large, in which case communication across cliques is encouraged.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nber.org/papers/w16410.pdf
Download Restriction: no

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16410.

as
in new window

Length:
Date of creation: Sep 2010
Date of revision:
Publication status: published as Bimpikis, Kostas & Ozdaglar, Asuman & Acemoglu, Daron, 2014. "Dynamics of information exchange in endogenous social networks," Theoretical Economics, Econometric Society, vol. 9(1), January.
Handle: RePEc:nbr:nberwo:16410
Note: EFG
Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Phone: 617-868-3900
Web page: http://www.nber.org
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Marco Ottaviani & Giuseppe Moscarini & Lones Smith, 1998. "Social learning in a changing world," Economic Theory, Springer, vol. 11(3), pages 657-665.
  2. Darrell Duffie & Semyon Malamud & Gustavo Manso, 2009. "Information Percolation With Equilibrium Search Dynamics," Econometrica, Econometric Society, vol. 77(5), pages 1513-1574, 09.
  3. Andrea Galeotti & Christian Ghiglino & Francesco Squintani, 2009. "Strategic Information Transmission in Networks," Economics Discussion Papers 668, University of Essex, Department of Economics.
  4. Oriana Bandiera & Imran Rasul, 2006. "Social Networks and Technology Adoption in Northern Mozambique," Economic Journal, Royal Economic Society, vol. 116(514), pages 869-902, October.
  5. David A. Reinstein & Christopher M. Snyder, 2005. "THE INFLUENCE OF EXPERT REVIEWS ON CONSUMER DEMAND FOR EXPERIENCE GOODS: A CASE STUDY OF MOVIE CRITICS -super-* ," Journal of Industrial Economics, Wiley Blackwell, vol. 53(1), pages 27-51, 03.
  6. Nair, Harikesh S. & Manchanda, Puneet & Bhatia, Tulikaa, 2006. "Asymmetric Peer Effects in Physician Prescription Behavior: The Role of Opinion Leaders," Research Papers 1970, Stanford University, Graduate School of Business.
  7. Galeotti, Andrea & Goyal, Sanjeev & Kamphorst, Jurjen, 2006. "Network formation with heterogeneous players," Games and Economic Behavior, Elsevier, vol. 54(2), pages 353-372, February.
  8. Sanjeev Goyal, 2007. "Introduction to Connections: An Introduction to the Economics of Networks
    [Connections: An Introduction to the Economics of Networks]
    ," Introductory Chapters, Princeton University Press.
  9. Andrea Galeotti, 2006. "One-way flow networks: the role of heterogeneity," Economic Theory, Springer, vol. 29(1), pages 163-179, September.
  10. Hojman, Daniel A. & Szeidl, Adam, 2008. "Core and periphery in networks," Journal of Economic Theory, Elsevier, vol. 139(1), pages 295-309, March.
  11. Jeanne Hagenbach & Frédéric Koessler, 2009. "Strategic Communication Networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00367692, HAL.
  12. Ambrus, Attila & Azevedo, Eduardo M. & Kamada, Yuichiro, 2013. "Hierarchical cheap talk," Theoretical Economics, Econometric Society, vol. 8(1), January.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:16410. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.