IDEAS home Printed from https://ideas.repec.org/p/cam/camdae/1935.html
   My bibliography  Save this paper

Network Formation in Large Groups

Author

Listed:
  • Choi, S
  • Goyal, S.
  • Moisan, F.

Abstract

We conduct an experiment to understand the principles that govern network formation. The design of the experiment builds on a model of linking and efforts taken from Galeotti and Goyal [2010]. In order to reduce cognitive complexity facing human subjects and facilitate learning, we develop a new experimental platform that integrates a network visualization tool using an algorithm of Barnes and Hut [1986] with an interactive tool of asynchronous choices in continuous time. Our experiment provides strong support for macroscopic predictions of the theory: there is specialization in linking and efforts across all treatments. Moreover, and in line with the theory, the specialization is more pronounced in larger groups. Thus subjects abide by the law of the few. Information on payoffs provided to subjects affects their behavior and yields differential welfare consequences. In the treatment where subjects see only their own payoffs, in large groups, the most connected individuals compete fiercely-they exert large efforts and have small earnings. By contrast, when a subject sees everyone's payoffs, in large groups, the most connected individuals engage in less intense competition-they exert little effort and have large earnings. The effects of information are much more muted in small groups.

Suggested Citation

  • Choi, S & Goyal, S. & Moisan, F., 2019. "Network Formation in Large Groups," Cambridge Working Papers in Economics 1935, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1935
    Note: sg472, fm442
    as

    Download full text from publisher

    File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe1935.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Falk Armin & Kosfeld Michael, 2012. "It's all about Connections: Evidence on Network Formation," Review of Network Economics, De Gruyter, vol. 11(3), pages 1-36, September.
    2. repec:wly:emetrp:v:85:y:2017:i::p:915-935 is not listed on IDEAS
    3. Siegfried Berninghaus & Karl-Martin Ehrhart & Marion Ott, 2006. "A network experiment in continuous time: The influence of link costs," Experimental Economics, Springer;Economic Science Association, vol. 9(3), pages 237-251, September.
    4. Arno Riedl & Ingrid M. T. Rohde & Martin Strobel, 2016. "Efficient Coordination in Weakest-Link Games," Review of Economic Studies, Oxford University Press, vol. 83(2), pages 737-767.
    5. Yann Bramoullé & Andrea Galeotti & Brian Rogers, 2016. "The Oxford Handbook of the Economics of Networks," Post-Print hal-01447842, HAL.
    6. 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.
    7. Goeree, Jacob K. & Riedl, Arno & Ule, Aljaz, 2009. "In search of stars: Network formation among heterogeneous agents," Games and Economic Behavior, Elsevier, vol. 67(2), pages 445-466, November.
    8. Sanjeev Goyal & Stephanie Rosenkranz & Utz Weitzel & Vincent Buskens, 2017. "Information Acquisition and Exchange in Social Networks," Economic Journal, Royal Economic Society, vol. 127(606), pages 2302-2331, November.
    9. Sanjeev Goyal & Marco J. van der Leij & José Luis Moraga-Gonzalez, 2006. "Economics: An Emerging Small World," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 403-432, April.
    10. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    11. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
    12. Daniel Friedman & Ryan Oprea, 2012. "A Continuous Dilemma," American Economic Review, American Economic Association, vol. 102(1), pages 337-363, February.
    13. James Pettit & Daniel Friedman & Curtis Kephart & Ryan Oprea, 2014. "Software for continuous game experiments," Experimental Economics, Springer;Economic Science Association, vol. 17(4), pages 631-648, December.
    14. Camerer, Colin F. & Ho, Teck-Hua & Chong, Juin-Kuan, 2002. "Sophisticated Experience-Weighted Attraction Learning and Strategic Teaching in Repeated Games," Journal of Economic Theory, Elsevier, vol. 104(1), pages 137-188, May.
    15. James Andreoni & John Miller, 2002. "Giving According to GARP: An Experimental Test of the Consistency of Preferences for Altruism," Econometrica, Econometric Society, vol. 70(2), pages 737-753, March.
    16. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
    17. Callander, Steven & Plott, Charles R., 2005. "Principles of network development and evolution: an experimental study," Journal of Public Economics, Elsevier, vol. 89(8), pages 1469-1495, August.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cam:camdae:1935. 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: (Jake Dyer). General contact details of provider: http://www.econ.cam.ac.uk/ .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.