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Self-Organization in Communication Networks

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Author Info

  • Bala, V.
  • Goyal, S.

Abstract

We develop a dynamic model to study the formation of communication networks. In this model, individuals periodically make decisions concerning the continuation of existing information links and the formation of new information links, with their cohorts. These decisions trade off the costs of forming and maintaining links against the potential rewards from doing so. We analyze the long run behavior of this process of link formation and dissolution. Our results establish that this process always self-organizes, i.e., irrespective of the number of agents, and the initial network, the dynamic process converges to a limit social communication network with probability one. Furthermore, we prove that the limiting network is invariably either a wheel network or the empty network. We show in the (corresponding) static network formation game that, while a variety of architectures can be sustained in equilibrium, the wheel is the unique efficient architecture for the interesting class of parameters. Thus, our results imply that the dynamics have strong equilibrium selection properties.

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File URL: http://repub.eur.nl/pub/1415/eeb19960111120063.pdf
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Bibliographic Info

Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 9713-/A.

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Date of creation: 01 Jan 1997
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Handle: RePEc:ems:eureir:1415

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Related research

Keywords: coordination; learning; networks; path-dependence; self-organization;

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References

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  1. Fudenberg, Drew & Ellison, Glenn, 1995. "Word-of-Mouth Communication and Social Learning," Scholarly Articles 3196300, Harvard University Department of Economics.
  2. Mailath, George J., 1992. "Introduction: Symposium on evolutionary game theory," Journal of Economic Theory, Elsevier, vol. 57(2), pages 259-277, August.
  3. Stef Tijs & Anne van den Nouweland & Bhaskar Dutta, 1998. "Link formation in cooperative situations," International Journal of Game Theory, Springer, vol. 27(2), pages 245-256.
  4. Glen Ellison, 2010. "Learning, Local Interaction, and Coordination," Levine's Working Paper Archive 391, David K. Levine.
  5. Aderlini, L. & Ianni, A., 1993. "Path Dependence and Learning from Neighbours," Papers 186, Cambridge - Risk, Information & Quantity Signals.
  6. Radner, Roy, 1993. "The Organization of Decentralized Information Processing," Econometrica, Econometric Society, vol. 61(5), pages 1109-46, September.
  7. Hendricks, Ken & Piccione, Michele & Tan, Guofu, 1995. "The Economics of Hubs: The Case of Monopoly," Review of Economic Studies, Wiley Blackwell, vol. 62(1), pages 83-99, January.
  8. Dutta, Bhaskar & Mutuswami, Suresh, 1996. "Stable Networks," Working Papers 971, California Institute of Technology, Division of the Humanities and Social Sciences.
  9. Sanchirico, Chris William, 1996. "A Probabilistic Model of Learning in Games," Econometrica, Econometric Society, vol. 64(6), pages 1375-93, November.
  10. repec:fth:coluec:9596-22 is not listed on IDEAS
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Cited by:
  1. J. Vandenbossche & T. Demuynck & -, 2010. "Network formation with heterogeneous agents and absolute friction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/642, Ghent University, Faculty of Economics and Business Administration.

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