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Social Learning in Continuous Time: When are Informational Cascades More Likely to be Inefficient?

In an observational learning environment rational agents may mimic the actions of the predecessors even when their own signal suggests the opposite. In case early movers’ signals happen to be incorrect society may settle on a common inefficient action, resulting in an inefficient informational cascade. This paper models observational learning in continuous time with endogenous timing of moves. This is the first paper with homogenous access to information that gives an analytical approximation for the probability of inefficient cascades. This permits the analysis of comparative statics results. In contrast to the general impression in the literature, the effect of an increase in signal quality on the likelihood of an inefficient cascade is shown to be non-monotonic. If agents do not have strong priors, an increase in signal quality may lead to a higher probability of inefficient herding. The analysis also suggests that markets with quick response to investment decisions, such as financial markets, are more prone to inefficient collapses.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 5120.

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Date of creation: Jul 2005
Date of revision:
Handle: RePEc:cpr:ceprdp:5120
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  1. Lones Smith & Peter Sorensen, 2000. "Pathological Outcomes of Observational Learning," Econometrica, Econometric Society, vol. 68(2), pages 371-398, March.
  2. Scharfstein, David S & Stein, Jeremy C, 1990. "Herd Behavior and Investment," American Economic Review, American Economic Association, vol. 80(3), pages 465-79, June.
  3. Devenow, Andrea & Welch, Ivo, 1996. "Rational herding in financial economics," European Economic Review, Elsevier, vol. 40(3-5), pages 603-615, April.
  4. De Vany, Arthur & Lee, Cassey, 2001. "Quality signals in information cascades and the dynamics of the distribution of motion picture box office revenues," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 593-614, March.
  5. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 2010. "A theory of Fads, Fashion, Custom and cultural change as informational Cascades," Levine's Working Paper Archive 1193, David K. Levine.
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  10. Kennedy, Robert E, 2002. "Strategy Fads and Competitive Convergence: An Empirical Test for Herd Behavior in Prime-Time Television Programming," Journal of Industrial Economics, Wiley Blackwell, vol. 50(1), pages 57-84, March.
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  12. Gale, D. & Chamley, C., 1992. "Information Revelation and Strategic Delay in a Model of Investment," Papers 10, Boston University - Department of Economics.
  13. Avery, Christopher & Zemsky, Peter, 1998. "Multidimensional Uncertainty and Herd Behavior in Financial Markets," American Economic Review, American Economic Association, vol. 88(4), pages 724-48, September.
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  15. Banerjee, Abhijit V, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, MIT Press, vol. 107(3), pages 797-817, August.
  16. Levin, Dan & Peck, James, 2008. "Investment dynamics with common and private values," Journal of Economic Theory, Elsevier, vol. 143(1), pages 114-139, November.
  17. Christophe Chamley, 2003. "Dynamic Speculative Attacks," American Economic Review, American Economic Association, vol. 93(3), pages 603-621, June.
  18. Lee Nelson, 2002. "Persistence and Reversal in Herd Behavior: Theory and Application to the Decision to Go Public," Review of Financial Studies, Society for Financial Studies, vol. 15(1), pages 65-95, March.
  19. Welch, Ivo, 2000. "Herding among security analysts," Journal of Financial Economics, Elsevier, vol. 58(3), pages 369-396, December.
  20. Maskin, Eric & Tirole, Jean, 1988. "A Theory of Dynamic Oligopoly, II: Price Competition, Kinked Demand Curves, and Edgeworth Cycles," Econometrica, Econometric Society, vol. 56(3), pages 571-99, May.
  21. Welch, Ivo, 1992. " Sequential Sales, Learning, and Cascades," Journal of Finance, American Finance Association, vol. 47(2), pages 695-732, June.
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