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Fragility of information cascades: an experimental study using elicited beliefs

Author Info

  • Anthony Ziegelmeyer

    ()

  • Frédéric Koessler

    ()

  • Juergen Bracht

    ()

  • Eyal Winter

    ()

Abstract

This paper examines the occurrence and fragility of information cascades in two laboratory experiments. One group of low informed participants sequentially guess which of two states has been randomly chosen. In a matched pairs design, another group of high informed participants make similar guesses after having observed the guesses of the low informed participants. In the second experiment, participants' beliefs about the chosen state are elicited. In equilibrium, low informed players who observe an established pattern of identical guesses herd without regard to their private information whereas high informed players always guess according to their private information. Equilibrium behavior implies that information cascades emerge in the group of low informed participants, the belief based solely on cascade guesses is stationary, and information cascades are systematically broken by high informed participants endowed with private information contradicting the cascade guesses. Experimental results show that the behavior of low informed participants is qualitatively in line with the equilibrium prediction. Information cascades often emerge in our experiments. The tendency of low informed participants to engage in cascade behavior increases with the number of identical guesses. Our main finding is that information cascades are not fragile. The behavior of high informed participants differs markedly from the equilibrium prediction. Only one-third of laboratory cascades are broken by high informed participants endowed with private information contradicting the cascade guesses. The relative frequency of cascade breaks is 15% for the situations where five or more identical guesses are observed. Participants' elicited beliefs are strongly consistent with their own behavior and show that, unlike in equilibrium, the more cascade guesses participants observe the more they believe in the state favored by those guesses.

(This abstract was borrowed from another version of this item.)

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File URL: http://hdl.handle.net/10.1007/s10683-009-9232-x
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Article provided by Springer in its journal Experimental Economics.

Volume (Year): 13 (2010)
Issue (Month): 2 (June)
Pages: 121-145

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Handle: RePEc:kap:expeco:v:13:y:2010:i:2:p:121-145
Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=102888

Keywords: Information cascades; Fragility; Elicited beliefs; Depth-of-reasoning analysis; Experimental economics; C72; C92; D82;

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Find related papers by JEL classification:
  • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
  • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
  • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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  1. Anderson, Lisa R. & Holt, Charles A., 2008. "Information Cascade Experiments," Handbook of Experimental Economics Results, Elsevier.
  2. Philip A. Haile & Ali Hortacsu & Grigory Kosenok, 2003. "On the Empirical Content of Quantal Response Equilibrium," Levine's Bibliography 666156000000000215, UCLA Department of Economics.
  3. Anderson, Lisa R, 2001. "Payoff Effects in Information Cascade Experiments," Economic Inquiry, Western Economic Association International, vol. 39(4), pages 609-15, October.
  4. Mathias Drehmann & Joerg Oechssler & Andreas Roider, 2002. "Herding and Contrarian Behavior in Financial Markets - An Internet Experiment," Experimental 0210001, EconWPA.
  5. Mariana Blanco & Dirk Engelmann & Alexander Koch & Hans-Theo Normann, 2010. "Belief elicitation in experiments: is there a hedging problem?," Experimental Economics, Springer, vol. 13(4), pages 412-438, December.
  6. Jacob Goeree & Thomas Palfrey & Brian Rogers, 2004. "Self-Correcting Information Cascades," Levine's Bibliography 122247000000000153, UCLA Department of Economics.
  7. Dorothea Kübler & Georg Weizsäcker, 2005. "Are Longer Cascades More Stable?," Journal of the European Economic Association, MIT Press, vol. 3(2-3), pages 330-339, 04/05.
  8. Kraemer, Carlo & Nöth, Markus & Weber, Martin, 2000. "Information Aggregation with Costly Information and Random Ordering: Experimental Evidence," Sonderforschungsbereich 504 Publications 00-35, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  9. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
  10. Plott, Charles & Hung, Angela, 1998. "Information Cascades: Replication and an Extension to Majority Rule and Conformity Rewarding Institutions," Working Papers 1051, California Institute of Technology, Division of the Humanities and Social Sciences.
  11. Daron Acemoglu & Munther A. Dahleh & Ilan Lobel & Asuman Ozdaglar, 2011. "Bayesian Learning in Social Networks," Review of Economic Studies, Oxford University Press, vol. 78(4), pages 1201-1236.
  12. Yaw Nyarko & Andrew Schotter, 2002. "An Experimental Study of Belief Learning Using Elicited Beliefs," Econometrica, Econometric Society, vol. 70(3), pages 971-1005, May.
  13. Chamley,Christophe P., 2004. "Rational Herds," Cambridge Books, Cambridge University Press, number 9780521530927.
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Cited by:

  1. Christoph March, 2011. "Adaptive social learning," Working Papers halshs-00572528, HAL.
  2. Anthony Ziegelmeyer & Christoph March & Sebastian Krügel, 2012. ""Do We Follow Others when We Should? A Simple Test of Rational Expectations": Comment," Jena Economic Research Papers 2012-006, Friedrich-Schiller-University Jena.
  3. Christoph March & Sebastian Krügel & Anthony Ziegelmeyer, 2012. "Do We Follow Private Information when We Should? Laboratory Evidence on Nave Herding," Jena Economic Research Papers 2012-002, Friedrich-Schiller-University Jena.
  4. Christoph March, 2016. "Adaptive Social Learning," CESifo Working Paper Series 5783, CESifo Group Munich.
  5. Crosetto, P. & Filippin, A., 2015. "The sound of others: suprising evidence of conformist behavior," Working Papers 2015-07, Grenoble Applied Economics Laboratory (GAEL).
  6. Meub, Lukas & Proeger, Till & Hüning, Hendrik, 2013. "A comparison of endogenous and exogenous timing in a social learning experiment," Center for European, Governance and Economic Development Research Discussion Papers 167, University of Goettingen, Department of Economics.
  7. Manski, Charles F. & Neri, Claudia, 2013. "First- and second-order subjective expectations in strategic decision-making: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 81(C), pages 232-254.
  8. Bossan, Benjamin & Jann, Ole & Hammerstein, Peter, 2015. "The evolution of social learning and its economic consequences," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 266-288.
  9. Bohren, J. Aislinn, 2016. "Informational herding with model misspecification," Journal of Economic Theory, Elsevier, vol. 163(C), pages 222-247.
  10. J. Aislinn Bohren, 2013. "Informational Herding with Model Misspecification," PIER Working Paper Archive 14-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

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