Firm size distributions and stochastic growth models: a comparison between ICT and Mechanical Italian Companies

Piero Ganugi (), Luigi Grossi and Lisa Crosato ()
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Piero Ganugi: Universitá Cattolica del Sacro Cuore di Piacenza

Statistical Methods & Applications, 2004, vol. 12, issue 3, No 9, 414 pages

Abstract: Abstract. In this paper we analyze the relationship between the distribution of firm size and stochastic processes of growth. Three main models have been suggested by Gibrat (1931), Kalecki (1945) and Champernowne (1973). The first two lead to lognormal distribution and the last to Pareto distribution. We fitted lognormal and Pareto distribution to two Italian sectors: ICT and mechanical. For ICT we found that lognormal distribution must be rejected and Pareto fits reasonably well to the last 30% of largest companies. For mechanical sector we can not reject lognormal distribution. Furthermore, we perform some experiments to corroborate the theoretical models. By means of transition matrices we found that ICT shows features very close to Gibrat’s and Champernowne’s models, while Kalecki’s model strongly fits to mechanical.

Keywords: Gibrat law; Pareto distribution; Lognormal distribution; Concentration; Firm size (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10260-003-0073-z

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