Gibrat and Pareto–Zipf revisited with European firms

Fujiwara, Yoshi; Aoyama, Hideaki; Guilmi, Corrado Di; Souma, Wataru; Gallegati, Mauro

doi:10.1016/j.physa.2004.06.098

Cited by 35 publications

(35 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Specifically, their result suggests the upper tail is relatively thin. This finding is also confirmed by Fujiwara et al (2004) by studying the data of France and UK.…”

Section: Introductionsupporting

confidence: 69%

Business Size Extension and Zipf’s Law: The Case of Top Corporate Groups in Taiwan

Lee¹,

Hsu²

2014

IJBM

View full text Add to dashboard Cite

This paper studies the upper tail distribution of the business group size in Taiwan. Our empirical study was based on the top 100 Taiwan business groups ranked in annual revenue, asset and employees during 2003 to 2009. We find that the group size distribution is fatter-tailed and gradually deviated from the Zipf's Law. Moreover, the law of proportional effect is violated.Specifically, our result shows that the larger business accompanies larger growth rate.

show abstract

“…Specifically, their result suggests the upper tail is relatively thin. This finding is also confirmed by Fujiwara et al (2004) by studying the data of France and UK.…”

Section: Introductionsupporting

confidence: 69%

Business Size Extension and Zipf’s Law: The Case of Top Corporate Groups in Taiwan

Lee¹,

Hsu²

2014

IJBM

View full text Add to dashboard Cite

show abstract

“…In 2004, Fujiwara et al [46] studied data sets of European firm sizes in order to explain firm size distribution and growth. They considered large size firms, where Pareto behavior was observed in the upper tail and checked validity of Gibrat's law in that regime.…”

Section: Economy and Power Lawsmentioning

confidence: 99%

A review of power laws in real life phenomena

Pinto

Lopes

Machado³

2012

Communications in Nonlinear Science and Numerical Simulation

127

View full text Add to dashboard Cite

a b s t r a c t Power law distributions, also known as heavy tail distributions, model distinct real life phenomena in the areas of biology, demography, computer science, economics, informa-tion theory, language, and astronomy, amongst others. In this paper, it is presented a review of the literature having in mind applications and possible explanations for the use of power laws in real phenomena. We also unravel some controversies around power laws.

show abstract

“…Both of these schemes are formalized by a kinetic equation describing the exchange of wealth between agents and global redistribution of wealth which plays the role of repelling from zero. Related approaches were subsequently pursued by a number of studies and simulations [24,25,26,27,28,29,30,31,32,33,34,35, * Electronic address: slanina@fzu.cz 36,37,38,39,40].…”

Section: Introductionmentioning

confidence: 99%