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(Anti-) Coordination in Networks

  • Jaromir Kovarik

    (University of the Basque Country)

  • Friederike Mengel

    (Maastricht University)

  • José Gabriel Romero

    (University of Santiago de Chile)

We study (anti-) coordination problems in networks in a laboratory experiment. Partici- pants interact with their neighbours in a fixed network to play a bilateral (anti-) coordination game. Our main treatment variable is the extent to which players are heterogeneous in the number of connections (neighbors) they have. Other network characteristics are held constant across treatments. We find the following results. Heterogeneity in the number of connections dramatically improves the rate of successful coordination. In addition, even though there is a multiplicity of Nash equilibria theoretically, a very sharp selection is observed empirically: the most connected player can impose her preferred Nash equilibrium almost always and observed Nash equilibria are such that all links are coordinated. As a second treatment variation we let agents decide endogenously on the amount of information they would like to have and find that local (endogenous) information is equally efficient in ensuring successful coordination as full information. We provide an intuitive explanation of these facts which is supported by our data.

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Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2010.49.

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Date of creation: May 2010
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Handle: RePEc:fem:femwpa:2010.49
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  1. Andrea Galeotti & Sanjeev Goyal, 2009. "Influencing the influencers: a theory of strategic diffusion," RAND Journal of Economics, RAND Corporation, vol. 40(3), pages 509-532.
  2. Cassar, Alessandra, 2007. "Coordination and cooperation in local, random and small world networks: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 58(2), pages 209-230, February.
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  9. repec:rne:rneart:v:3:y:2004:i:1:p:19-41 is not listed on IDEAS
  10. Kosfeld Michael, 2004. "Economic Networks in the Laboratory: A Survey," Review of Network Economics, De Gruyter, vol. 3(1), pages 1-23, March.
  11. Goyal, Sanjeev & Vega-Redondo, Fernando, 2005. "Network formation and social coordination," Games and Economic Behavior, Elsevier, vol. 50(2), pages 178-207, February.
  12. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer, vol. 10(2), pages 171-178, June.
  13. Kene BOUN MY & Marc WILLINGER & Anthony ZIEGELMEYER, 1999. "Global versus local interaction in coordination games: an experimental investigation," Working Papers of BETA 9923, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
  14. Alós-Ferrer, Carlos & Weidenholzer, Simon, 2008. "Contagion and efficiency," Journal of Economic Theory, Elsevier, vol. 143(1), pages 251-274, November.
  15. Matthew O. Jackson & Alison Watts, 2000. "On the Formation of Interaction Networks in Social Coordination Games," Econometric Society World Congress 2000 Contributed Papers 0778, Econometric Society.
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