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Employee Number Dependence in Labor Productivity Distribution

Author

Listed:
  • Atushi Ishikawa

    (Kanazawa Gakuin University)

  • Takayuki Mizuno

    (National Institute of Informatics)

  • Shouji Fujimoto

    (Kanazawa Gakuin University)

Abstract

Using data from Japanese and French firms in the 2020 edition of ORBIS, the world’s largest commercial database, we define labor productivity to be the operating revenue per employee and analyze the dependence of distribution on the number of employees by industry. We found that the distribution of labor productivity in non-manufacturing industries is basically independent of the number of employees in each country. On the other hand, in the construction and manufacturing industries, the distribution of labor productivity shifts in a higher direction as the number of employees increases. Furthermore, we show theoretically that the logarithm of labor productivity is linearly connected to the logarithm of the number of employees, and that the strength of the connection is proportional to the difference between the ratio of the Pareto index of the number of employees to operating revenue and 1. We confirm this finding in empirical data.

Suggested Citation

  • Atushi Ishikawa & Takayuki Mizuno & Shouji Fujimoto, 2022. "Employee Number Dependence in Labor Productivity Distribution," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 465-477, October.
    • Handle: RePEc:spr:trosos:v:16:y:2022:i:2:d:10.1007_s12626-022-00121-z
    DOI: 10.1007/s12626-022-00121-z
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    References listed on IDEAS

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    1. Ishikawa, Atushi & Fujimoto, Shouji & Watanabe, Tsutomu & Mizuno, Takayuki, 2013. "The emergence of different tail exponents in the distributions of firm size variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2104-2113.
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    9. Aoyama,Hideaki & Fujiwara,Yoshi & Ikeda,Yuichi & Iyetomi,Hiroshi & Souma,Wataru Preface by-Name:Yoshikawa,Hiroshi, 2010. "Econophysics and Companies," Cambridge Books, Cambridge University Press, number 9780521191494.
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