Productivity levels and growth are extremely heterogeneous among firms. A vast literature has developed to explain the origins of productivity shocks, their dispersion, evolution and their relationship to the business cycle. We examine in detail the distribution of labor productivity levels and growth, and observe that they exhibit heavy tails. We propose to model these distributions using the four parameter Lévy stable distribution, a natural candidate deriving from the generalised Central Limit Theorem. We show that it is a better fit than several standard alternatives, and is remarkably consistent over time, countries and sectors. In all samples considered, the tail parameter is such that the theoretical variance of the distribution is infinite, so that the sample standard deviation increases with sample size. We find a consistent positive skewness, a markedly different behaviour between the left and right tails, and a positive relationship between productivity and size. The distributional approach allows us to test different measures of dispersion and find that productivity dispersion has slightly decreased over the past decade.

Among the phenomena in economics that are not yet well-understood is the fat-tailed (power-law) distribution of firm sizes in the world's economies. Different mechanisms suggested in the literature to explain this distribution of firm sizes are discussed in the present paper. The paper uses the China Industrial Enterprises Database to study the distribution (firm size in terms of the number of employees, capital, and gross profit) for the provinces of China for the years 1998-2008. We estimate the power-law distribution and confirm its plausibility using the KS test and the log-likelihood ratio vs. lognormal and exponential distributions. The analysis on regional levels allows an assessment of regional effects on differences in the distribution; we discuss possible explanations for the observed patterns in the light of the recent regional economic development in the PRC.

No abstract