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Naive learning in social networks: Imitating the most successful neighbor

Author Info

  • Tsakas, Nikolas

Abstract

This paper considers a model of observational learning in social networks. Every period, the agents observe the actions of their neighbors and their realized outcomes, and they imitate the most successful. First, we study the case where the network has finite population and we show that, regardless of the structure, the population converges to a monomorphic steady state, i.e. where every agent chooses the same action. Subsequently, we extend our analysis to infinitely large networks and we differentiate the cases where agents have bounded neighborhoods, with those where they do not. Under bounded neighborhoods, an action is diffused to the whole population if it is the only one initially chosen by infinitely many agents. If there exist more than one such actions, we provide an additional sufficient condition in the payoff structure, which ensures convergence for any network. Without the assumption of bounded neighborhoods, we show that an action can survive even if it is initially chosen by a single agent and also that a network can be in steady state without this being monomorphic.

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File URL: https://mpra.ub.uni-muenchen.de/37796/1/MPRA_paper_37796.pdf
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File URL: https://mpra.ub.uni-muenchen.de/45210/8/MPRA_paper_45210.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 37796.

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Date of creation: 23 Mar 2012
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Handle: RePEc:pra:mprapa:37796
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Keywords: Social Networks; Learning; Diffusion; Imitation;

Find related papers by JEL classification:

  • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
  • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
  • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

This paper has been announced in the following NEP Reports:

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  1. Dekel, Eddie & Fudenberg, Drew & Levine, David K., 2004. "Learning to play Bayesian games," Games and Economic Behavior, Elsevier, vol. 46(2), pages 282-303, February.
  2. Schlag, Karl H., 1994. "Why Imitate, and if so, How? Exploring a Model of Social Evolution," Discussion Paper Serie B 296, University of Bonn, Germany.
  3. Drew Fudenberg & David K. Levine, 1996. "The Theory of Learning in Games," Levine's Working Paper Archive 624, David K. Levine.
  4. Abhijit Banerjee & Drew Fudenberg, 2010. "Word of Mouth Learning," Levine's Working Paper Archive 723, David K. Levine.
  5. Apesteguia, Jose & Huck, Steffen & Oechssler, Joerg, 2003. "Imitation - Theory and Experimental Evidence," University of California at Santa Barbara, Economics Working Paper Series qt3h0887tj, Department of Economics, UC Santa Barbara.
  6. Alós-Ferrer, Carlos & Weidenholzer, Simon, 2008. "Contagion and efficiency," Journal of Economic Theory, Elsevier, vol. 143(1), pages 251-274, November.
  7. Timothy G. Conley & Christopher R. Udry, 2005. "Learning about a new technology: pineapple in Ghana," Proceedings, Federal Reserve Bank of San Francisco.
  8. Josephson, Jens & Matros, Alexander, 2000. "Stochastic Imitation in Finite Games," SSE/EFI Working Paper Series in Economics and Finance 363, Stockholm School of Economics, revised 26 Nov 2002.
  9. Karl H. Schlag, 1995. "Why Imitate, and if so, How? A Bounded Rational Approach to Multi-Armed Bandits," Discussion Paper Serie B 361, University of Bonn, Germany, revised Mar 1996.
  10. Constanza Fosco & Friederike Mengel, 2009. "Cooperation through Imitation and Exclusion in Networks," Working Papers 2009.37, Fondazione Eni Enrico Mattei.
  11. Eshel, Ilan & Samuelson, Larry & Shaked, Avner, 1998. "Altruists, Egoists, and Hooligans in a Local Interaction Model," American Economic Review, American Economic Association, vol. 88(1), pages 157-79, March.
  12. Schlag, Karl H., 1996. "Which one should I imitate?," Discussion Paper Serie B 365, University of Bonn, Germany.
  13. Fernando Vega Redondo, 1996. "The evolution of walrasian behavior," Working Papers. Serie AD 1996-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  14. Ellison, Glenn & Fudenberg, Drew, 1992. "Rules of Thumb for Social Learning," IDEI Working Papers 17, Institut d'Économie Industrielle (IDEI), Toulouse.
  15. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
  16. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
  17. A. Banerjee & Drew Fudenberg, 2010. "Word-of-Mouth Communication and Social Learning," Levine's Working Paper Archive 425, David K. Levine.
  18. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 595-621.
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