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Growing Stars: A Laboratory Analysis of Network Formation

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  • Rong Rong

    ()
    (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University)

  • Daniel Houser

    ()
    (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University)

Abstract

The acquisition and dispersion of information, a critical aspect of economic decisions, can occur through a network of agents (Jackson, 2009). Empirical and theoretical findings suggest that an efficient information dispersion network takes the form of a star: small numbers of agents gather information and distribute it to a large group. Controlled tests of this theory, however, have typically found little evidence of star network emergence. An exception is Goeree et al (2009), which reports reliable star network formation in an environment that includes ex ante heterogeneous agents. While heterogeneity may explain network formation sometimes, it seems to play a smaller role in other cases (Feick and Price, 1987; Conley and Udry, 2010). In this paper we investigate whether specific institutional conditions promote star network formation with ex ante homogeneous agents. We  find  that  investment  limits  and  the  “right-of- first-refusal,† both  of  which  are institutions that stabilize decision making, have a surprising ability to promote star network formation. Further, using a cluster analysis that allows us to draw inferences about individuals’  behavioral rules, we find that these effective institutions encourage individual rationality as well as positive habits. We argue that these decision rules emerge due to the stabilizing features of the institutions and this stability facilitates improved network behaviors and outcomes. Length: 56

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Bibliographic Info

Paper provided by George Mason University, Interdisciplinary Center for Economic Science in its series Working Papers with number 1035.

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Date of creation: Jun 2012
Date of revision: Oct 2012
Handle: RePEc:gms:wpaper:1035

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Keywords: social networks; star network formation; cluster analysis; experiments.;

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  1. 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.
  2. Yann Bramoullé & Dunia López-Pintado & Sanjeev Goyal & Fernando Vega-Redondo, 2004. "Network formation and anti-coordination games," International Journal of Game Theory, Springer, vol. 33(1), pages 1-19, January.
  3. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
  4. Song, Lina & Appleton, Simon & Knight, John, 2006. "Why Do Girls in Rural China Have Lower School Enrollment?," World Development, Elsevier, vol. 34(9), pages 1639-1653, September.
  5. Cary Deck & Cathleen Johnson, 2004. "Link bidding in laboratory networks," Review of Economic Design, Springer, vol. 8(4), pages 359-372, 04.
  6. Bramoulle, Yann & Kranton, Rachel, 2007. "Public goods in networks," Journal of Economic Theory, Elsevier, vol. 135(1), pages 478-494, July.
  7. Hirschberg, Joseph G. & Maasoumi, Esfandiar & Slottje, Daniel J., 1991. "Cluster analysis for measuring welfare and quality of life across countries," Journal of Econometrics, Elsevier, vol. 50(1-2), pages 131-150, October.
  8. Juan Larrosa & Fernando Tohme, 2003. "Network Formation with Heterogenous Agents," Microeconomics 0301002, EconWPA.
  9. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer, vol. 50(2), pages 159-179, June.
  10. 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.
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