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Testing the power law model for discrete size data

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  • Andrew R. Solow
  • Christopher J. Costello
  • Michael B. Ward

Abstract

It is sometimes claimed that different types of size data in biology follow a power law. Here, a formal statistical test of the power law for discrete size data is described. The test is based on embedding the power law in the nonparametric family of distributions for which frequency is nonincreasing with size. A parametric bootstrap is used to assess significance. The test is applied to four data sets concerning the frequency of genera of different sizes. The power law is rejected in three out of four cases.

Suggested Citation

  • 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.
    • Handle: RePEc:mos:moswps:archive-16
    DOI: 10.1086/378956
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    Cited by:

    1. 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.
    2. Martins, Francisco Leonardo Bezerra & do Nascimento, José Cláudio, 2022. "Power law dynamics in genealogical graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.

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