Better models for Gibrat’s data

Saralees Nadarajah () and Emmanuel Afuecheta ()
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Saralees Nadarajah: University of Manchester
Emmanuel Afuecheta: King Fahd University of Petroleum & Minerals

Empirical Economics, 2022, vol. 62, issue 4, No 19, 2057-2067

Abstract: Abstract Akhundjanov and Toda (Empir Econ 59:2071–2091, 2020) analyzed 24 data sets in as reported by Gibrat (Les Inégalités Économiques, Librairie du Recueil Sirey, Paris, 1931), showing among others that 17 of the data sets can be best modeled by the Pareto-lognormal distribution due to Reed and Jorgensen (Commun Stat Theory Methods 33:1733–1753, 2004). Here, we reanalyze the same data sets and show that a new distribution exhibiting polynomial tails can provide even better fits. The assessment of better fits is based on two information criteria and likelihood ratio tests.

Keywords: Estimation; Polynomial tails; Student’s t distribution (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s00181-021-02081-9

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