Tsakas, Nikolas (2012): Naive learning in social networks: Imitating the most successful neighbor.
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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.
|Item Type:||MPRA Paper|
|Original Title:||Naive learning in social networks: Imitating the most successful neighbor|
|Keywords:||Social Networks, Learning, Diffusion, Imitation|
|Subjects:||D - Microeconomics > D0 - General > D03 - Behavioral Microeconomics: Underlying Principles
D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D83 - Search ; Learning ; Information and Knowledge ; Communication ; Belief ; Unawareness
D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D85 - Network Formation and Analysis: Theory
|Depositing User:||Nikolas Tsakas|
|Date Deposited:||02. Apr 2012 13:16|
|Last Modified:||22. Feb 2013 10:16|
Acemoglu, D., Dahleh, M.A., Lobel, I. & Ozdaglar, A. (2011). Bayesian Learning in Social Networks. Review of Economic Studies, doi: 10.1093/restud/rdr004(1994).
Alos-Ferrer, C. & Weidenholzer, S. (2008). Contagion and eciency. Journal of Economic Theory 143, 251-274.
Apesteguia, J., Huck, S. & Oechssler, J. (2007). Imitation - Theory and experimental evidence. Journal of Economic Theory 136, 217-235.
Bala, V. & Goyal, S. (1998). Learning from Neighbours. Review of Economic Studies 65, 595-621.
Banerjee, A. (1992). A Simple Model of Herd Behavior. Quarterly Journal of Economics 107, 797-817.
Banerjee, A. & Fudenberg, D. (2004).Word-of-mouth learning. Games and Economic Behavior 46, 1-22.
Billingsley, P. (1995). Probability and measure. John Wiley & Sons, New York.
Conley, T. & Udry, C. (2010). Learning About a New Technology: Pineapple in Ghana. American Economic Review 100, 35-69.
DeGroot, M.H. (1974). Reaching a Consensus. Journal of the American Statistical Association 69, 118-121.
Ellison, G. & Fudenberg, D. (1993). Rules of Thumb for Social Learning. Journal of Political Economy 101, 612-644. Ellison, G. & Fudenberg, D. (1995). Word-of-mouth communication and social learning. Quarterly Journal of Economics 109, 93-125.
Eshel, I., Samuelson, L. & Shaked A. (1998). Altruists, egoists and hooligans in a local interaction model. American Economic Review 88, 157-179.
Fosco, C. & Mengel, F. (2010). Cooperation through imitation and exclusion in networks. Journal of Economic Dynamics and Control, doi:10.1016/j.jedc.2010.12.002
Fudenberg, D. & Levine, D., (1998). The Theory of Learning in Games, MIT Press, Cambridge, MA.
Gale, D. & Kariv, S. (2003) Bayesian Learning in Social Networks. Games and Economic Behavior 45, 329-346.
Golub, B. & Jackson, M.O. (2010). Naive Learning in Social Networks and the Wisdom of Crowds. American Economic Journal: Microeconomics 2, 112-149.
Jackson, M.O. (2008). Social and Economic Networks. Princeton University Press.
Jackson, M.O. & Yariv, L. (2007). Diusion of Behavior and Equilibrium Properties in Network Games. American Economic Review, Papers and Proceedings, 97, 92-98.
Josephson, J. & Matros, A. (2004). Stochastic imitation in nite games. Games and Economic Behavior 49, 244-259.
Lopez-Pintado, D. (2008). Contagion in Complex Networks. Games and Economic Behavior 62, 573-590.
Morris, S. (2000), Contagion, The Review of Economic Studies 67, 57-78.
Schlag, K. (1998). Why imitate, and if so, how? A boundedly rational approach to multi-armed bandits. Journal of Economic Theory 78, 130-156.
Schlag, K. (1999). Which one should I imitate? Journal of Mathematical Economics 31, 493-522.
Smith, L. & Sorensen, P. (2000). Pathological Outcomes of Observational Learning. Econometrica 68, 371-398.
Weibull, J. (1995). Evolutionary Game Theory. MIT Press, Cambridge, MA.
Vega-Redondo, F. (1997). The evolution of Walrasian Behavior. Econometrica 65, 375-384.
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