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Herding With and Without Payoff Externalities - An Internet Experiment

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  • Drehmann, Mathias
  • Roider, Andreas
  • Oechssler, Joerg

Abstract

Most real world situations that are susceptible to herding are also characterized by direct payoff externalities. Yet, the bulk of the theoretical and experimental literature on herding has focused on pure informational externalities. In this paper we experimentally investigate the effects of several different forms of payoff externalities (e.g., network effects, first-mover advantage, etc.) in a standard information-based herding model. Our results are based on an internet experiment with more than 6000 subjects, including a subsample of 267 consultants from an international consulting firm. We also replicate and review earlier cascade experiments. Finally, we study reputation effects (i.e., the influence of success models) in the context of herding.

Suggested Citation

  • Drehmann, Mathias & Roider, Andreas & Oechssler, Joerg, 2005. "Herding With and Without Payoff Externalities - An Internet Experiment," CEPR Discussion Papers 5310, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:5310
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    Cited by:

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    3. Oechssler, Jörg & Roider, Andreas & Schmitz, Patrick W., 2009. "Cognitive abilities and behavioral biases," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 147-152, October.
    4. Omar Al-Ubaydli & John A. List, 2016. "Field Experiments in Markets," NBER Working Papers 22113, National Bureau of Economic Research, Inc.
    5. Jacob K. Goeree & Leeat Yariv, 2015. "Conformity in the lab," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 15-28, July.
    6. Morone, Andrea & Ozdemir, Ozlem, 2012. "Black swan protection: an experimental investigation," MPRA Paper 38842, University Library of Munich, Germany.
    7. Fiedler, Marina & Haruvy, Ernan, 2009. "The lab versus the virtual lab and virtual field--An experimental investigation of trust games with communication," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 716-724, November.
    8. Jörg Oechssler & Andreas Roider & Patrick W. Schmitz, 2015. "Cooling Off in Negotiations: Does it Work?," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 171(4), pages 565-588, December.
    9. Eyster, Erik & Galeotti, Andrea & Kartik, Navin & Rabin, Matthew, 2014. "Congested observational learning," Games and Economic Behavior, Elsevier, vol. 87(C), pages 519-538.
    10. Andreas Roider & Andrea Voskort, 2016. "Reputational Herding in Financial Markets: A Laboratory Experiment," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 17(3), pages 244-266, July.
    11. Paul J. Healy & John Conlon & Yeochang Yoon, 2016. "Information Cascades with Informative Ratings: An Experimental Test," Working Papers 16-05, Ohio State University, Department of Economics.
    12. Christoph Brunner & Jacob K. Goeree, 2009. "Wise crowds or wise minorities?," IEW - Working Papers 439, Institute for Empirical Research in Economics - University of Zurich.
    13. Ozge Dinc‐Cavlak & Ozlem Ozdemir, 2021. "Comparing the willingness to pay through three elicitation mechanisms: An experimental evidence for organic egg product," Agribusiness, John Wiley & Sons, Ltd., vol. 37(4), pages 782-803, October.
    14. Duersch, Peter & Oechssler, Jörg & Schipper, Burkhard C., 2009. "Incentives for subjects in internet experiments," Economics Letters, Elsevier, vol. 105(1), pages 120-122, October.
    15. Chmura, Thorsten & Le, Hang & Nguyen, Kim, 2022. "Herding with leading traders: Evidence from a laboratory social trading platform," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 93-106.
    16. Davis, Brent J., 2017. "An experiment on behavior in social learning games with collective preferences," Economics Letters, Elsevier, vol. 152(C), pages 93-95.
    17. Georg Weizsacker, 2010. "Do We Follow Others When We Should? A Simple Test of Rational Expectations," American Economic Review, American Economic Association, vol. 100(5), pages 2340-2360, December.
    18. Tomasz Kopczewski & Michał Krawczyk & Przemysław Kusztelak, 2013. "Enforced compatibility and control of switching costs in markets with network externalities: an experiment," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 35.
    19. Song, Yangbo & Zhang, Jiahua, 2020. "Social learning with coordination motives," Games and Economic Behavior, Elsevier, vol. 123(C), pages 81-100.
    20. Christoph Buehren & Tim Meyer & Christian Pierdzioch, 2020. "Experimental Evidence on Forecaster (anti-) Herding in Sports Markets," MAGKS Papers on Economics 202038, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    21. Efraim Berkovich, 2011. "Search and herding effects in peer-to-peer lending: evidence from prosper.com," Annals of Finance, Springer, vol. 7(3), pages 389-405, August.
    22. Fahr, René & Irlenbusch, Bernd, 2011. "Who follows the crowd—Groups or individuals?," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 200-209.
    23. Irene Comeig & Ernesto Mesa-Vázquez & Pau Sendra-Pons & Amparo Urbano, 2020. "Rational Herding in Reward-Based Crowdfunding: An MTurk Experiment," Sustainability, MDPI, vol. 12(23), pages 1-21, November.
    24. Oechssler, Jörg & Roider, Andreas & Schmitz, Patrick W., 2009. "Cognitive abilities and behavioral biases," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 147-152, October.

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    More about this item

    Keywords

    Information cascades; Herding; Network effects; Experiment; Internet;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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