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Social Learning with Coarse Inference

  • Antonio Guarino
  • Philippe Jehie

We study social learning by boundedly rational agents. Agents take a decision in sequence, after observing their predecessors and a private signal. They are unable to make perfect inferences from their predecessors' decisions: they only understand the relation between the aggregate distribution of actions and the state of nature, and make their inferences accordingly. We show that, in a discrete action space, even if agents receive signals of unbounded precision, there are asymptotic inefficiencies. In a continuous action space, compared to the rational case, agents overweight early signals. Despite this behavioral bias, eventually agents learn the realized state of the world and choose the correct action.

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Paper provided by David K. Levine in its series Levine's Working Paper Archive with number 814577000000000292.

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Date of creation: 13 Jul 2009
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Handle: RePEc:cla:levarc:814577000000000292
Contact details of provider: Web page: http://www.dklevine.com/

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  1. Celen, Bogachan & Kariv, Shachar, 2004. "Observational learning under imperfect information," Games and Economic Behavior, Elsevier, vol. 47(1), pages 72-86, April.
  2. Weizsäcker, Georg, 2008. "Do We Follow Others When We Should? A Simple Test of Rational Expectations," IZA Discussion Papers 3616, Institute for the Study of Labor (IZA).
  3. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
  4. Allison, G. & Fudenberg, D., 1992. "Rules of Thumb for Social Learning," Working papers 92-12, Massachusetts Institute of Technology (MIT), Department of Economics.
  5. Gale, Douglas, 1996. "What have we learned from social learning?," European Economic Review, Elsevier, vol. 40(3-5), pages 617-628, April.
  6. Abhijit Banerjee & Drew Fudenberg, 2010. "Word of Mouth Learning," Levine's Working Paper Archive 723, David K. Levine.
  7. Philippe Jehiel & Frédéric Koessler, 2006. "Revisiting Games of Incomplete Information with Analogy-Based Expectations," Levine's Bibliography 122247000000000252, UCLA Department of Economics.
  8. Larson, Nathan, 2008. "Inertia in social learning from a summary statistic," MPRA Paper 32143, University Library of Munich, Germany, revised Jul 2011.
  9. Steffen Huck & Joerg Oechssler, 1997. "Informational Cascades with Continuous Action Spaces," Game Theory and Information 9710002, EconWPA.
  10. Ignacio Monzon & Michael Rapp, 2011. "Observational Learning with Position Uncertainty," Carlo Alberto Notebooks 206, Collegio Carlo Alberto.
  11. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion bias, social influence, and uni-dimensional opinions," LSE Research Online Documents on Economics 454, London School of Economics and Political Science, LSE Library.
  12. David Hirshleifer & Siew Hong Teoh, 2003. "Herd Behaviour and Cascading in Capital Markets: a Review and Synthesis," European Financial Management, European Financial Management Association, vol. 9(1), pages 25-66.
  13. Philippe Jehiel, 2005. "Analogy-based Expectation Equilibrium," Post-Print halshs-00754070, HAL.
  14. Kübler, Dorothea & Weizsäcker, Georg, 2000. "Limited depth of reasoning and failure of cascade formation in the laboratory," SFB 373 Discussion Papers 2001,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  15. Antonio Guarino & Steffen Huck & Heike Harmgart, 2008. "When half the truth is better than the truth: A Theory of aggregate information cascades," WEF Working Papers 0046, ESRC World Economy and Finance Research Programme, Birkbeck, University of London.
  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.
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