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Two-way Flow Networks with Small Decay

Author

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  • K. de Jaegher
  • J.J.A. Kamphorst

Abstract

The set of equilibrium networks in the two-way flow model of network formation (Bala and Goyal, 2000) is very sensitive to the introduction of decay. Even if decay is small enough so that equilibrium networks are minimal, the set of equilibrium architectures becomes much richer, especially when the benefit functions are nonlinear. However, not much is known about these architectures. In this paper we remedy this gap in the literature. We characterize the equilibrium architectures. Moreover, we show results on the relative stability of different types of architectures. Three of the results are that (i) at most one players receives multiple links, (ii) the absolute diameter of equilibrium networks can be arbitrarily large, and (iii) large (small) diameter networks are relatively stable under concave (convex) benefit functions.

Suggested Citation

  • K. de Jaegher & J.J.A. Kamphorst, 2009. "Two-way Flow Networks with Small Decay," Working Papers 09-34, Utrecht School of Economics.
  • Handle: RePEc:use:tkiwps:0934
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    References listed on IDEAS

    as
    1. Sudipta Sarangi & Pascal Billand & Christophe Bravard, 2006. "Heterogeneity in Nash Networks," Departmental Working Papers 2006-18, Department of Economics, Louisiana State University.
    2. Jurjen Kamphorst & Gerard Van Der Laan, 2007. "Network Formation Under Heterogeneous Costs: The Multiple Group Model," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 9(04), pages 599-635.
    3. Haller, Hans & Sarangi, Sudipta, 2005. "Nash networks with heterogeneous links," Mathematical Social Sciences, Elsevier, vol. 50(2), pages 181-201, September.
    4. Buechel, Berno, 2011. "Network formation with closeness incentives," Center for Mathematical Economics Working Papers 395, Center for Mathematical Economics, Bielefeld University.
    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. Bloch, Francis & Dutta, Bhaskar, 2009. "Communication networks with endogenous link strength," Games and Economic Behavior, Elsevier, vol. 66(1), pages 39-56, May.
    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. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    9. Sanjeev Goyal & Sumit Joshi, 2006. "Unequal connections," International Journal of Game Theory, Springer;Game Theory Society, vol. 34(3), pages 319-349, October.
    10. Filippo VERGARA CAFFARELLI, 2004. "Non-Cooperative Network Formation with Network Maintenance Costs," Economics Working Papers ECO2004/18, European University Institute.
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    Citations

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    Cited by:

    1. Pascal Billand & Christophe Bravard & Sudipta Sarangi & J. Kamphorst, 2011. "Confirming information flows in networks," Post-Print halshs-00672351, HAL.
    2. De Jaegher, K. & Kamphorst, J.J.A., 2015. "Minimal two-way flow networks with small decay," Journal of Economic Behavior & Organization, Elsevier, vol. 109(C), pages 217-239.
    3. Cui, Zhiwei & Wang, Shouyang & Zhang, Jin & Zu, Lei, 2013. "Stochastic stability in one-way flow networks," Mathematical Social Sciences, Elsevier, vol. 66(3), pages 410-421.
    4. Philipp Moehlmeier & Agnieszka Rusinowska & Emily Tanimura, 2016. "A degree-distance-based connections model with negative and positive externalities," PSE - Labex "OSE-Ouvrir la Science Economique" hal-01387467, HAL.

    More about this item

    Keywords

    Network formation; two-way flow model; decay; non-linear benefits;

    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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