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Biased Social Learning

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Abstract

This paper examines social learning when only one of the two types of decisions is observable. Because agents arrive randomly over time, and only those who invest are observed, later agents face a more complicated inference problem than in the standard model, as the absence of investment might reflect either a choice not to invest, or a lack of arrivals. We show that, as in the standard model, learning is complete if and only if signals are unbounded. If signals are bounded, cascades may occur, and whether they are more or less likely than in the standard model depends on a property of the signal distribution. If the hazard ratio of the distributions increases in the signal, it is more likely that no one invests in the standard model than in this one, and welfare is higher. Conclusions are reversed if the hazard ratio is decreasing. The monotonicity of the hazard ratio is the condition that guarantees the presence or absence of informational cascades in the standard herding model.

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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1738.

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Length: 35 pages
Date of creation: Oct 2009
Date of revision:
Publication status: Published in Games and Economic Behavior (July 2013), 80: 131-146
Handle: RePEc:cwl:cwldpp:1738

Note: CFP 1380
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Related research

Keywords: Informational herds; Cascades; Selection bias;

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Cited by:
  1. Bar Ifrach & Costis Maglaras & Marco Scarsini, 2011. "Monopoly Pricing in the Presence of Social Learning," Working Papers 11-11, NET Institute, revised Nov 2011.
  2. Caroline D. Thomas & Martin W. Cripps, 2014. "Strategic Experimentation in Queues," Department of Economics Working Papers 140228, The University of Texas at Austin, Department of Economics.
  3. Guarino, Antonio & Harmgart, Heike & Huck, Steffen, 2011. "Aggregate information cascades," Games and Economic Behavior, Elsevier, vol. 73(1), pages 167-185, September.

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