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Fragility of information cascades: an experimental study using elicited beliefs

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Listed author(s):
  • 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 & Economic Science Association 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
DOI: 10.1007/s10683-009-9232-x
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Keywords: Information cascades; Fragility; Elicited beliefs; Depth-of-reasoning analysis; Experimental economics; C72; C92; D82;

Other versions of this item:

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. Mathias Drehmann & Jörg Oechssler & Andreas Roider, 2005. "Herding and Contrarian Behavior in Financial Markets: An Internet Experiment," American Economic Review, American Economic Association, vol. 95(5), pages 1403-1426, December.
  2. 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.
  3. Mariana Blanco & Dirk Engelmann & Alexander Koch & Hans-Theo Normann, 2010. "Belief elicitation in experiments: is there a hedging problem?," Experimental Economics, Springer;Economic Science Association, vol. 13(4), pages 412-438, December.
  4. Chamley,Christophe P., 2004. "Rational Herds," Cambridge Books, Cambridge University Press, number 9780521530927, September.
  5. Anderson, Lisa R, 2001. "Payoff Effects in Information Cascade Experiments," Economic Inquiry, Western Economic Association International, vol. 39(4), pages 609-615, October.
  6. Philip A. Haile & Ali Hortaçsu & Grigory Kosenok, 2008. "On the Empirical Content of Quantal Response Equilibrium," American Economic Review, American Economic Association, vol. 98(1), pages 180-200, March.
  7. Angela A. Hung & Charles R. Plott, 2001. "Information Cascades: Replication and an Extension to Majority Rule and Conformity-Rewarding Institutions," American Economic Review, American Economic Association, vol. 91(5), pages 1508-1520, December.
  8. Yaw Nyarko & Andrew Schotter, 2002. "An Experimental Study of Belief Learning Using Elicited Beliefs," Econometrica, Econometric Society, vol. 70(3), pages 971-1005, May.
  9. Jacob K. Goeree & Thomas R. Palfrey & Brian W. Rogers & Richard D. McKelvey, 2007. "Self-Correcting Information Cascades," Review of Economic Studies, Oxford University Press, vol. 74(3), pages 733-762.
  10. Chamley,Christophe P., 2004. "Rational Herds," Cambridge Books, Cambridge University Press, number 9780521824019, September.
  11. Anderson, Lisa R. & Holt, Charles A., 2008. "Information Cascade Experiments," Handbook of Experimental Economics Results, Elsevier.
  12. Kraemer, Carlo & Noth, Markus & Weber, Martin, 2006. "Information aggregation with costly information and random ordering: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 59(3), pages 423-432, March.
  13. 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.
  14. 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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Cited by:

  1. Anthony Ziegelmeyer & Christoph March & Sebastian Kr?gel, 2013. "Do We Follow Others When We Should? A Simple Test of Rational Expectations: Comment," American Economic Review, American Economic Association, vol. 103(6), pages 2633-2642, October.
  2. repec:eee:eecrev:v:94:y:2017:i:c:p:148-165 is not listed on IDEAS
  3. Christoph March, 2011. "Adaptive social learning," PSE Working Papers halshs-00572528, HAL.
  4. 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.
  5. 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.
  6. Crosetto, P. & Filippin, A., 2015. "The sound of others: suprising evidence of conformist behavior," Working Papers 2015-07, Grenoble Applied Economics Laboratory (GAEL).
  7. Bohren, J. Aislinn, 2016. "Informational herding with model misspecification," Journal of Economic Theory, Elsevier, vol. 163(C), pages 222-247.
  8. 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.
  9. 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.

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