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Scaling Laws in Labor Productivity

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  • FUJIWARA Yoshi
  • AOYAMA Hideaki
  • Mauro GALLEGATI

Abstract

Empirical study of firms' growth and fluctuation requires the understanding of the dynamics of labor and productivity among firms by using large-scale data including that of small and medium-sized enterprises (SMEs). Specifically, the key to such understanding is the findings in statistical properties in equilibrium distributions of output, labor, and productivity. We uncover a set of scaling laws of conditional probability distributions, which are sufficient for characterizing joint distributions by employing an updated database covering one million firms including domestic SMEs. These scaling laws show the existence of lognormal joint distributions for sales and labor, and the existence of a scaling law for labor productivity, both of which are confirmed empirically. This framework offers characterization of equilibrium distributions with a small number of scaling indices, which determine macroscopic quantities, thus opening a new perspective of bridging microeconomics and macroeconomics.

Suggested Citation

  • FUJIWARA Yoshi & AOYAMA Hideaki & Mauro GALLEGATI, 2012. "Scaling Laws in Labor Productivity," Discussion papers 12040, Research Institute of Economy, Trade and Industry (RIETI).
    • Handle: RePEc:eti:dpaper:12040
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    References listed on IDEAS

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    3. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    4. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
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