Scaling Laws in Labor Productivity
AbstractEmpirical 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Research Institute of Economy, Trade and Industry (RIETI) in its series Discussion papers with number 12040.
Length: 11 pages
Date of creation: Jun 2012
Date of revision:
Contact details of provider:
Postal: 11th floor, Annex, Ministry of Economy, Trade and Industry (METI) 1-3-1, Kasumigaseki Chiyoda-ku, Tokyo, 100-8901
Web page: http://www.rieti.go.jp/
More information through EDIRC
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Tristen Hayfield & Jeffrey S. Racine, . "Nonparametric Econometrics: The np Package," Journal of Statistical Software, American Statistical Association, vol. 27(i05).
- Aoki,Masanao & Yoshikawa,Hiroshi, 2007. "Reconstructing Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521831062, December.
- Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (NUKATANI Sorahiko).
If references are entirely missing, you can add them using this form.