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The Law Of Genius And Home Runs Refuted

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  • JOHN DINARDO
  • JASON WINFREE

Abstract

"In a lively, provocative article, DeVany claims inter alia that the size distribution of home runs follows a continuous "power law" distribution which is nested in a larger class of "stable" statistical distributions characterized by an infinite variance. He uses this putative fact about the size distribution of home runs to argue that concern about the use of steroids to enhance home run ability is necessarily misplaced. In this article, we show that the initial claim is false and argue that the subsequent claim about the potential importance of steroid use does not follow from the first. We also show that the method used to establish that the size distribution of home runs is characterized by an infinite variance is unreliable and will find evidence "consistent" with infinite variance in all but the most trivial of data sets generated by processes with finite variance. Despite a large and growing literature that spans several fields and uses methods and arguments similar to DeVany's, we argue that mere inspection of the unconditional distribution of some human phenomenon is unlikely to yield much insight." ("JEL" C16, L83) Copyright (c) 2008 Western Economic Association International.

Suggested Citation

  • John Dinardo & Jason Winfree, 2010. "The Law Of Genius And Home Runs Refuted," Economic Inquiry, Western Economic Association International, vol. 48(1), pages 51-64, January.
  • Handle: RePEc:bla:ecinqu:v:48:y:2010:i:1:p:51-64
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    File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1465-7295.2008.00176.x
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    References listed on IDEAS

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    1. John DiNardo, 2007. "Interesting Questions in Freakonomics," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 973-1000, December.
    2. Andrew R. Solow & Christopher J. Costello & Michael B. Ward, 2003. "Testing the power law model for discrete size data," Monash Economics Working Papers archive-16, Monash University, Department of Economics.
    3. Brock, W A, 1999. "Scaling in Economics: A Reader's Guide," Industrial and Corporate Change, Oxford University Press, vol. 8(3), pages 409-446, September.
    4. Xavier Gabaix, 1999. "Zipf's Law for Cities: An Explanation," The Quarterly Journal of Economics, Oxford University Press, vol. 114(3), pages 739-767.
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    Cited by:

    1. repec:bla:ecinqu:v:55:y:2017:i:2:p:1104-1118 is not listed on IDEAS
    2. Gould, Eric D. & Kaplan, Todd R., 2011. "Learning unethical practices from a co-worker: The peer effect of Jose Canseco," Labour Economics, Elsevier, vol. 18(3), pages 338-348, June.
    3. William A. Brock & Steven N. Durlauf, 2010. "Adoption Curves and Social Interactions," Journal of the European Economic Association, MIT Press, vol. 8(1), pages 232-251, March.
    4. Nieswiadomy Michael L. & Strazicich Mark C. & Clayton Stephen, 2012. "Was There a Structural Break in Barry Bonds's Bat?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(3), pages 1-19, October.
    5. Rodney Fort & Young Hoon Lee, 2013. "Major League Baseball attendance time series: league policy lessons," Chapters,in: The Econometrics of Sport, chapter 2, pages 35-50 Edward Elgar Publishing.
    6. Aloys Prinz & Jan Piening & Thomas Ehrmann, 2015. "The success of art galleries: a dynamic model with competition and information effects," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(2), pages 153-176, May.

    More about this item

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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