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Zipf law and the firm size distribution: a critical discussion of popular estimators

Listed author(s):
  • Giulio Bottazzi

    ()

  • Davide Pirino
  • Federico Tamagni

The upper tail of the firm size distribution is often assumed to follow a Power Law. Several recent papers, using different estimators and different data sets, conclude that the Zipf Law, in particular, provides a good fit, implying that the fraction of firms with size above a given value is inversely proportional to the value itself. In this article we compare the asymptotic and small sample properties of different methods through which this conclusion has been reached. We find that the family of estimators most widely adopted, based on an OLS regression, is in fact unreliable and basically useless for appropriate inference. This finding raises doubts about previously identified Zipf behavior. Based on extensive numerical analysis, we recommend the adoption of the Hill estimator over any other method when individual observations are available. Copyright Springer-Verlag Berlin Heidelberg 2015

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File URL: http://hdl.handle.net/10.1007/s00191-015-0395-7
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Article provided by Springer in its journal Journal of Evolutionary Economics.

Volume (Year): 25 (2015)
Issue (Month): 3 (July)
Pages: 585-610

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Handle: RePEc:spr:joevec:v:25:y:2015:i:3:p:585-610
DOI: 10.1007/s00191-015-0395-7
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  1. Giulio Bottazzi & Alex Coad & Nadia Jacoby & Angelo Secchi, 2011. "Corporate growth and industrial dynamics: evidence from French manufacturing," Applied Economics, Taylor & Francis Journals, vol. 43(1), pages 103-116.
  2. de Wit, Gerrit, 2005. "Firm size distributions: An overview of steady-state distributions resulting from firm dynamics models," International Journal of Industrial Organization, Elsevier, vol. 23(5-6), pages 423-450, June.
  3. Xavier Gabaix & Augustin Landier, 2008. "Why has CEO Pay Increased So Much?," The Quarterly Journal of Economics, Oxford University Press, vol. 123(1), pages 49-100.
  4. Giulio Bottazzi & Angelo Secchi & Federico Tamagni, 2014. "Financial constraints and firm dynamics," Small Business Economics, Springer, vol. 42(1), pages 99-116, January.
  5. di Giovanni, Julian & Levchenko, Andrei A. & Rancière, Romain, 2011. "Power laws in firm size and openness to trade: Measurement and implications," Journal of International Economics, Elsevier, vol. 85(1), pages 42-52, September.
  6. Xavier Gabaix & Rustam Ibragimov, 2011. "Rank - 1 / 2: A Simple Way to Improve the OLS Estimation of Tail Exponents," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 24-39, January.
  7. di Giovanni, Julian & Levchenko, Andrei A., 2013. "Firm entry, trade, and welfare in Zipf's world," Journal of International Economics, Elsevier, vol. 89(2), pages 283-296.
  8. Rafał Weron, 2001. "Levy-Stable Distributions Revisited: Tail Index > 2 Does Not Exclude The Levy-Stable Regime," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 209-223.
  9. Fujiwara, Yoshi & Di Guilmi, Corrado & Aoyama, Hideaki & Gallegati, Mauro & Souma, Wataru, 2004. "Do Pareto–Zipf and Gibrat laws hold true? An analysis with European firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(1), pages 197-216.
  10. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
  11. Nunes Amaral, Luís A & Buldyrev, Sergey V & Havlin, Shlomo & Maass, Philipp & Salinger, Michael A & Eugene Stanley, H & Stanley, Michael H.R, 1997. "Scaling behavior in economics: The problem of quantifying company growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 244(1), pages 1-24.
  12. Okuyama, K & Takayasu, M & Takayasu, H, 1999. "Zipf's law in income distribution of companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(1), pages 125-131.
  13. Erzo G. J. Luttmer, 2007. "Selection, Growth, and the Size Distribution of Firms," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1103-1144.
  14. repec:wsi:ijmpcx:v:12:y:2001:i:02:n:s0129183101001614 is not listed on IDEAS
  15. Gabaix, Xavier & Ibragimov, Rustam, 2011. "Rank − 1 / 2: A Simple Way to Improve the OLS Estimation of Tail Exponents," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 24-39.
  16. Boris Podobnik & Davor Horvatic & Alexander M. Petersen & Branko Uro\v{s}evi\'c & H. Eugene Stanley, 2010. "Bankruptcy risk model and empirical tests," Papers 1011.2670, arXiv.org.
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