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Diffusion by Imitation: The Importance of Targeting Agents

  • Nikolas Tsakas

We study the optimal targeting strategy of a planner who seeks to maximize the diffusion of an action in a network where agents imitate successful past behavior of their neighbors. We find that the optimal targeting strategy depends on two parameters: (i) the likelihood of the action being more successful than its alternative and (ii) the planner's patience. More specifically, when the planner's preferred action has higher probability of being more successful than its alternative, then the optimal strategy for an infinitely patient planner is to concentrate all the targeted agents in one connected group; whereas when this probability is lower it is optimal to spread them uniformly around the network. Interestingly, for a very impatient planner, the optimal targeting strategy is exactly the opposite. Our results highlight the importance of knowing a society's exact network structure for the efficient design of targeting strategies, especially in settings where the agents are positionally similar.

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Paper provided by Job Market Papers in its series 2013 Papers with number pts99.

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Date of creation: 08 Dec 2013
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Handle: RePEc:jmp:jm2013:pts99
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  1. Bigoni, Maria & Fort, Margherita, 2013. "Information and Learning in Oligopoly: An Experiment," IZA Discussion Papers 7125, Institute for the Study of Labor (IZA).
  2. José Apesteguía & Steffen Huck & Jorg Oechssler, 2003. "Imitation-Theory and Experimental Evidence-," Documentos de Trabajo - Lan Gaiak Departamento de Economía - Universidad Pública de Navarra 0306, Departamento de Economía - Universidad Pública de Navarra.
  3. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
  4. Fernando Vega-Redondo, 1997. "The Evolution of Walrasian Behavior," Econometrica, Econometric Society, vol. 65(2), pages 375-384, March.
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  8. Mengel, Friederike & Fosco, Constanza, 2007. "Cooperation through Imitation and Exclusion in Networks," MPRA Paper 5258, University Library of Munich, Germany.
  9. Steiner, Jakub & Sakovics, Jozsef, 2008. "Who Matters in Coordination Problems?," SIRE Discussion Papers 2008-27, Scottish Institute for Research in Economics (SIRE).
  10. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
  11. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 595-621.
  12. Tsakas Nikolas, 2014. "Imitating the Most Successful Neighbor in Social Networks," Review of Network Economics, De Gruyter, vol. 12(4), pages 33, February.
  13. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 595-621.
  14. 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.
  15. Timothy G. Conley & Christopher R. Udry, 2005. "Learning about a new technology: pineapple in Ghana," Proceedings, Federal Reserve Bank of San Francisco.
  16. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
  17. Gerd Gigerenzer & Reinhard Selten (ed.), 2002. "Bounded Rationality: The Adaptive Toolbox," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262571641, June.
  18. Alós-Ferrer, Carlos & Weidenholzer, Simon, 2008. "Contagion and efficiency," Journal of Economic Theory, Elsevier, vol. 143(1), pages 251-274, November.
  19. Nikolas Tsakas, 2015. "Optimal influence under observational learning," University of Cyprus Working Papers in Economics 10-2015, University of Cyprus Department of Economics.
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