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Confirming Information Flows in Networks

Author

Listed:
  • Sudipta Sarangi
  • Pascal Billand
  • Christophe Bravard
  • Jurjen Kamphorst

Abstract

Our paper belongs to the strand of literature associated with the notion of Nash networks introduced by Bala and Goyal [1] in the connections model. Our aim is to consider situations where agent i has concerns about the validity of information that she acquires from agent j. Independently confirming this information through another set of agents allows i to put more faith in j's information, that is increases the value of j's information. In such situations, we characterize the set of strict Nash networks. Then, we provide a condition which ensures the existence of Nash networks when agents play pure strategies. Finally, we characterize the set of strict efficient networks and we discuss the relationship between efficient networks and strict Nash networks.

Suggested Citation

  • Sudipta Sarangi & Pascal Billand & Christophe Bravard & Jurjen Kamphorst, 2012. "Confirming Information Flows in Networks," Departmental Working Papers 2012-02, Department of Economics, Louisiana State University.
    • Handle: RePEc:lsu:lsuwpp:2012-02
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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. Haller, Hans & Sarangi, Sudipta, 2005. "Nash networks with heterogeneous links," Mathematical Social Sciences, Elsevier, vol. 50(2), pages 181-201, September.
    3. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 595-621.
    4. 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.
    5. Hojman, Daniel A. & Szeidl, Adam, 2008. "Core and periphery in networks," Journal of Economic Theory, Elsevier, vol. 139(1), pages 295-309, March.
    6. K. de Jaegher & J.J.A. Kamphorst, 2008. "Network formation with decreasing marginal benefits of information," Working Papers 08-16, Utrecht School of Economics.
    7. 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.
    8. Kim, Chongmin & Wong, Kam-Chau, 2007. "Network formation and stable equilibrium," Journal of Economic Theory, Elsevier, vol. 133(1), pages 536-549, March.
    9. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
    10. 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.
    11. Galeotti, Andrea & Goyal, Sanjeev & Kamphorst, Jurjen, 2006. "Network formation with heterogeneous players," Games and Economic Behavior, Elsevier, vol. 54(2), pages 353-372, February.
    12. 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.
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    14. Andrea Galeotti & Sanjeev Goyal, 2010. "The Law of the Few," American Economic Review, American Economic Association, vol. 100(4), pages 1468-1492, September.
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    More about this item

    JEL classification:

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

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