IDEAS home Printed from https://ideas.repec.org/a/bpj/bejtec/v7y2008i1n46.html
   My bibliography  Save this article

Local Network Effects and Complex Network Structure

Author

Listed:
  • Sundararajan Arun

    () (New York University)

Abstract

This paper presents a model of local network effects in which agents connected in a social network each value the adoption of a product by a heterogeneous subset of other agents in their neighborhood, and have incomplete information about the structure and strength of adoption complementarities between all other agents. I show that the symmetric Bayes-Nash equilibria of this network game are in monotone strategies, can be strictly Pareto-ranked based on a scalar neighbor-adoption probability value, and that the greatest such equilibrium is uniquely coalition-proof. Each Bayes-Nash equilibrium has a corresponding fulfilled-expectations equilibrium under which agents form local adoption expectations. Examples illustrate cases in which the social network is an instance of a Poisson random graph, when it is a complete graph, a standard model of network effects, and when it is a generalized random graph. A generating function describing the structure of networks of adopting agents is characterized as a function of the Bayes-Nash equilibrium they play, and empirical implications of this characterization are discussed.

Suggested Citation

  • Sundararajan Arun, 2008. "Local Network Effects and Complex Network Structure," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-37, January.
  • Handle: RePEc:bpj:bejtec:v:7:y:2008:i:1:n:46
    as

    Download full text from publisher

    File URL: https://www.degruyter.com/view/j/bejte.2007.7.1/bejte.2007.7.1.1319/bejte.2007.7.1.1319.xml?format=INT
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Harmsen - van Hout, Marjolein J.W. & Dellaert, Benedict G.C. & Herings, P. Jean-Jacques, 2016. "Heuristic decision making in network linking," European Journal of Operational Research, Elsevier, vol. 251(1), pages 158-170.
    2. Mohamed Belhaj & Frédéric Deroïan, 2016. "The Value of Network Information: Assortative Mixing Makes the Difference," Working Papers halshs-01314954, HAL.
    3. Iván Arribas & Amparo Urbano Salvador, 2014. "Local coordination and global congestion in random networks," Discussion Papers in Economic Behaviour 0814, University of Valencia, ERI-CES.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:bejtec:v:7:y:2008:i:1:n:46. 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: (Peter Golla). General contact details of provider: https://www.degruyter.com .

    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.

    We have no references for this item. You can help adding them by using 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.