Scaling Laws in Labor Productivity
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.
|Date of creation:||Jun 2012|
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- Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355, April.
- Tristen Hayfield & Jeffrey S. Racine, . "Nonparametric Econometrics: The np Package," Journal of Statistical Software, American Statistical Association, vol. 27(i05).
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