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The "Gambler's Fallacy" in Lottery Play

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  • Charles T. Clotfelter
  • Philip J. Cook

Abstract

The -gambler's fallacy- is the belief that the probability of an event is lowered when that event has recently occurred, even though the probability of the event is objectively known to be independent from one trial to the next. This paper provides evidence on the time pattern of lottery participation to see whether actual behavior is consistent with this fallacy. Using data from the Maryland daily numbers game, we find a clear and consistent tendency for the amount of money bet on a particular number to fall sharply immediately after it is drawn, and then gradually to recover to its former level over the course of several months. This pattern is consistent with the hypothesis that lottery players are in fact subject to the gambler?s fallacy.

Suggested Citation

  • Charles T. Clotfelter & Philip J. Cook, 1991. "The "Gambler's Fallacy" in Lottery Play," NBER Working Papers 3769, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:3769
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    1. Rebecca Morrison & Peter Ordeshook, 1975. "Rational choice, light guessing and the gambler's fallacy," Public Choice, Springer, vol. 22(1), pages 79-89, June.
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    Cited by:

    1. Gerlinde Fellner & Matthias Sutter, 2009. "Causes, Consequences, and Cures of Myopic Loss Aversion – An Experimental Investigation," Economic Journal, Royal Economic Society, vol. 119(537), pages 900-916, April.
    2. Jonathan Guryan & Melissa S. Kearney, 2010. "Is Lottery Gambling Addictive?," American Economic Journal: Economic Policy, American Economic Association, vol. 2(3), pages 90-110, August.
    3. George Papachristou, 2004. "The British gambler's fallacy," Applied Economics, Taylor & Francis Journals, vol. 36(18), pages 2073-2077.
    4. Rachel Croson & James Sundali, 2005. "The Gambler’s Fallacy and the Hot Hand: Empirical Data from Casinos," Journal of Risk and Uncertainty, Springer, vol. 30(3), pages 195-209, May.
    5. Melissa S. Kearney, 2005. "The Economic Winners and Losers of Legalized Gambling," NBER Working Papers 11234, National Bureau of Economic Research, Inc.
    6. Philip Ganderton & David Brookshire & Michael McKee & Steve Stewart & Hale Thurston, 2000. "Buying Insurance for Disaster-Type Risks: Experimental Evidence," Journal of Risk and Uncertainty, Springer, vol. 20(3), pages 271-289, May.
    7. Matthew Rabin., 2000. "Inference by Believers in the Law of Small Numbers," Economics Working Papers E00-282, University of California at Berkeley.
    8. Jonathan Guryan & Melissa S. Kearney, 2005. "Lucky Stores, Gambling, and Addiction: Empirical Evidence from State Lottery Sales," NBER Working Papers 11287, National Bureau of Economic Research, Inc.
    9. Matthew Rabin & Dimitri Vayanos, 2010. "The Gambler's and Hot-Hand Fallacies: Theory and Applications," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 730-778.
    10. Narayanan, Sridhar & Manchanda, Puneet, 2008. "An Empirical Analysis of Individual Level Casino Gambling Behavior," Research Papers 2003, Stanford University, Graduate School of Business.
    11. Sridhar Narayanan & Puneet Manchanda, 2012. "An empirical analysis of individual level casino gambling behavior," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 27-62, March.
    12. Les Coleman, 2004. "New light on the longshot bias," Applied Economics, Taylor & Francis Journals, vol. 36(4), pages 315-326.

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