What determines the size distribution of business firms? What kind of firm dynamics may be underlying observed firm size distributions? Which candidate distributions may be used for fitting purposes? We here address these questions from a stochastic model perspective. We construct a firm dynamics process that leads to a Dagum distribution of firm size at equilibrium. An empirical study shows that the proposed model captures the empirical regularities of firm size distributions with considerable accuracy.

Fiori, A., Motta, A. (2019). Stochastic Models for the Size Distribution of Italian Firms: A Proposal. In F. Greselin, L. Deldossi, L. Bagnato, M. Vichi (a cura di), Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society CLADAG 2017 Statistical Learning of Complex Data (pp. 111-120). Springer Berlin Heidelberg [10.1007/978-3-030-21140-0_12].

Stochastic Models for the Size Distribution of Italian Firms: A Proposal

Fiori, AM
;
2019

Abstract

What determines the size distribution of business firms? What kind of firm dynamics may be underlying observed firm size distributions? Which candidate distributions may be used for fitting purposes? We here address these questions from a stochastic model perspective. We construct a firm dynamics process that leads to a Dagum distribution of firm size at equilibrium. An empirical study shows that the proposed model captures the empirical regularities of firm size distributions with considerable accuracy.
Capitolo o saggio
Firm dynamics, Gibrat’s law, Dagum distribution
English
Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society CLADAG 2017 Statistical Learning of Complex Data
Greselin, F; Deldossi, L; Bagnato, L; Vichi, M
2019
9783030211394
Springer Berlin Heidelberg
111
120
Fiori, A., Motta, A. (2019). Stochastic Models for the Size Distribution of Italian Firms: A Proposal. In F. Greselin, L. Deldossi, L. Bagnato, M. Vichi (a cura di), Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society CLADAG 2017 Statistical Learning of Complex Data (pp. 111-120). Springer Berlin Heidelberg [10.1007/978-3-030-21140-0_12].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/249516
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