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Aggregate Uncertainty Can Lead to Herds

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  • Ignacio Monzón

Abstract

This paper presents a model in which homogeneous rational agents choose between two competing technologies. Agents observe a private signal and a sample of other agents’ previous choices. The signal has both an idiosyncratic and an aggregate component of uncertainty. I derive the optimal decision rule when each agent observes the decision of exactly two agents. Due to aggregate uncertainty, aggregate behavior does not necessarily reflect the true state of nature. Nonetheless, agents still find others’ choices a good source of information, and they base their decisions partly on the behavior of others. Consequently, bad choices can be perpetuated in this environment: I show that aggregate uncertainty can lead to agents herding on the inferior technology with positive probability. I also present examples in which herding occurs for arbitrarily large sample sizes.

Suggested Citation

  • Ignacio Monzón, 2012. "Aggregate Uncertainty Can Lead to Herds," Carlo Alberto Notebooks 245, Collegio Carlo Alberto.
    • Handle: RePEc:cca:wpaper:245
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    References listed on IDEAS

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    1. Callander, Steven & Hörner, Johannes, 2009. "The wisdom of the minority," Journal of Economic Theory, Elsevier, vol. 144(4), pages 1421-1439.2, July.
    2. Ellison, Glenn & Fudenberg, Drew, 1993. "Rules of Thumb for Social Learning," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 612-643, August.
    3. Judd, Kenneth L., 1985. "The law of large numbers with a continuum of IID random variables," Journal of Economic Theory, Elsevier, vol. 35(1), pages 19-25, February.
    4. Glenn Ellison & Drew Fudenberg, 1995. "Word-of-Mouth Communication and Social Learning," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 93-125.
    5. Monzón, Ignacio & Rapp, Michael, 2014. "Observational learning with position uncertainty," Journal of Economic Theory, Elsevier, vol. 154(C), pages 375-402.
    6. Patrick Bolton & Christopher Harris, 1999. "Strategic Experimentation," Econometrica, Econometric Society, vol. 67(2), pages 349-374, March.
    7. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    8. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    9. , & ,, 2015. "Information diffusion in networks through social learning," Theoretical Economics, Econometric Society, vol. 10(3), September.
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    Keywords

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    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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