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In search of stars: Network formation among heterogeneous agents

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  • Goeree, Jacob K.
  • Riedl, Arno
  • Ule, Aljaz

Abstract

This paper reports results from a laboratory experiment on network formation among heterogeneous agents. The experimental design extends the Bala-Goyal [Bala, V., Goyal, S., 2000. A non-cooperative model of network formation, Econometrica 68, 1131-1230] model of network formation with decay and two-way flow of benefits by introducing agents with lower linking costs or higher benefits to others. Furthermore, agents' types may be common knowledge or private information. In all treatments, the (efficient) equilibrium network has a "star" structure. While equilibrium predictions fail completely with homogeneous agents, star networks frequently occur with heterogeneous agents. Stars are not born but rather develop: with a high-value agent, the network's centrality, stability, and efficiency all increase over time. A structural econometric model based on best response dynamics and other-regarding preferences is used to analyze individual linking behavior. Maximum-likelihood estimates of the underlying structural parameters, obtained by pooling data from several treatments, allow us to explain the main treatment effects.

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Bibliographic Info

Article provided by Elsevier in its journal Games and Economic Behavior.

Volume (Year): 67 (2009)
Issue (Month): 2 (November)
Pages: 445-466

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Handle: RePEc:eee:gamebe:v:67:y:2009:i:2:p:445-466

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Web page: http://www.elsevier.com/locate/inca/622836

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Keywords: Network formation Experiment Heterogeneity Private information;

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Citations

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Cited by:
  1. KIRCHSTEIGER, Georg & MANTOVANI, Marco & MAULEON, Ana & VANNETELBOSCH, Vincent, 2011. "Myopic or farsighted? An experiment on network formation," CORE Discussion Papers 2011007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Anthony Ziegelmeyer & Katinka Pantz, 2005. "Collaborative Networks in Experimental Triopolies," Papers on Strategic Interaction 2005-38, Max Planck Institute of Economics, Strategic Interaction Group.
  3. Fehr, Ernst & Schmidt, Klaus M., 2009. "On Inequity Aversion - A Reply to Binmore and Shaked," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 256, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
  4. Rong Rong & Daniel Houser, 2012. "Growing Stars: A Laboratory Analysis of Network Formation," Working Papers 1035, George Mason University, Interdisciplinary Center for Economic Science, revised Oct 2012.
  5. Rosenkranz, Stephanie & Weitzel, Utz, 2012. "Network structure and strategic investments: An experimental analysis," Games and Economic Behavior, Elsevier, vol. 75(2), pages 898-920.
  6. Harmsen - van Hout, Marjolein J.W. & Dellaert, Benedict G.C. & Herings, P. Jean-Jacques, 2010. "Behavioral Effects in Individual Decisions of Network Formation: Complexity Reduces Payoff Orientation and Social Preferences," FCN Working Papers 5/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  7. Boris van Leeuwen & Theo Offerman & Arthur Schram, 2013. "Superstars Need Social Benefits: An Experiment on Network Formation," Tinbergen Institute Discussion Papers 13-112/I, Tinbergen Institute.
  8. Sanjeev Goyal & Stephanie Rosenkranz & Utz Weitzel & Vincent Buskens, 2014. "Individual Search and Social Networks," Working Papers 2014.49, Fondazione Eni Enrico Mattei.
  9. Doğan, Gönül & van Assen, Marcel & Potters, Jan, 2013. "The effect of link costs on simple buyer–seller networks," Games and Economic Behavior, Elsevier, vol. 77(1), pages 229-246.
  10. Anna Contea & Daniela T. Di Cagno & Emanuela Sciubbad, 2011. "Behavioural patterns in social networks," Jena Economic Research Papers 2011-060, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.

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