Version 1
: Received: 26 April 2024 / Approved: 28 April 2024 / Online: 28 April 2024 (10:31:40 CEST)
How to cite:
Tao, Y.; Liu, R. Generalized Pareto Distribution of Firm Sizes: Evidence from China. Preprints2024, 2024041840. https://doi.org/10.20944/preprints202404.1840.v1
Tao, Y.; Liu, R. Generalized Pareto Distribution of Firm Sizes: Evidence from China. Preprints 2024, 2024041840. https://doi.org/10.20944/preprints202404.1840.v1
Tao, Y.; Liu, R. Generalized Pareto Distribution of Firm Sizes: Evidence from China. Preprints2024, 2024041840. https://doi.org/10.20944/preprints202404.1840.v1
APA Style
Tao, Y., & Liu, R. (2024). Generalized Pareto Distribution of Firm Sizes: Evidence from China. Preprints. https://doi.org/10.20944/preprints202404.1840.v1
Chicago/Turabian Style
Tao, Y. and Ruoxi Liu. 2024 "Generalized Pareto Distribution of Firm Sizes: Evidence from China" Preprints. https://doi.org/10.20944/preprints202404.1840.v1
Abstract
It has been empirically observed that the upper tail of the firm size distribution follows either the Pareto distribution or the Zipf distribution, with both patterns being explained by Gibrat’s law (Gabaix, 1999). This article analyzed firm revenue data from China, spanning from 2005 to 2013, to examine the whole range of the firm size distribution. Our empirical analysis revealed that firm revenue data over these years is well fitted by a three-parameter generalized Pareto distribution, with the fitted parameters indicating a dichotomy: The size distribution of large-sized firms, namely the upper tail, is asymptotically characterized by a Pareto distribution or a Zipf distribution, whereas the size distribution of smaller and medium-sized firms is approximated by an exponential distribution. This finding suggests that Gibrat’s law should be extended to account for the emergence of a generalized Pareto distribution.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
