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Confirming Information Flows in Networks

Author

Listed:
  • Pascal Billand

    (Universite de Lyon, Universite Jean Monnet, Saint-Etienne, CNRS, GATE)

  • Christophe Bravard

    (Universite de Lyon, Universite Jean Monnet, Saint-Etienne, CNRS, GATE)

  • Jurjen Kamphorst

    (Erasmus University Rotterdam)

  • Sudipta Sarangi

    (DIW Berlin and Louisiana State University)

Abstract
Social networks, be it on the internet or in real life, facilitate information flows. We model this by giving agents incentives to link with others and receive information through those links. In many networks agents will value confirmation of the information they receive from others. Our paper analyzes the impact such a need for confirmation has on the social networks which are formed. We first study the existence of Nash equilibria and then characterize the set of strict Nash networks. Next, we characterize the set of strictly efficient networks and discuss the relationship between strictly efficient networks and strict Nash networks.

Suggested Citation

  • Pascal Billand & Christophe Bravard & Jurjen Kamphorst & Sudipta Sarangi, 2012. "Confirming Information Flows in Networks," Tinbergen Institute Discussion Papers 12-019/1, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20120019
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    File URL: https://papers.tinbergen.nl/12019.pdf
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    References listed on IDEAS

    as
    1. Pascal Billand & Christophe Bravard & Sudipta Sarangi, 2011. "Strict Nash networks and partner heterogeneity," International Journal of Game Theory, Springer;Game Theory Society, vol. 40(3), pages 515-525, August.
    2. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 595-621.
    3. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    4. Venkatesh Bala & Sanjeev Goyal, 2000. "original papers : A strategic analysis of network reliability," Review of Economic Design, Springer;Society for Economic Design, vol. 5(3), pages 205-228.
    5. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
    6. Pascal Billand & Christophe Bravard & Sudipta Sarangi, 2011. "Resources Flows Asymmetries in Strict Nash Networks with Partner Heterogeneity," Working Papers 1108, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    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. Sudipta Sarangi & Pascal Billand & Christophe Bravard, 2010. "On the Interaction between Heterogeneity and Decay in Directed Networks," Departmental Working Papers 2010-04, Department of Economics, Louisiana State University.
    9. Andrea Galeotti & Sanjeev Goyal, 2010. "The Law of the Few," American Economic Review, American Economic Association, vol. 100(4), pages 1468-1492, September.
    10. K. de Jaegher & J.J.A. Kamphorst, 2009. "Two-way Flow Networks with Small Decay," Working Papers 09-34, Utrecht School of Economics.
    11. Haller, Hans & Sarangi, Sudipta, 2005. "Nash networks with heterogeneous links," Mathematical Social Sciences, Elsevier, vol. 50(2), pages 181-201, September.
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    15. repec:use:tkiwps:1616 is not listed on IDEAS
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    More about this item

    Keywords

    connections model; confirmation; two-way flow models;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

    NEP fields

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