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Gibrat's Law and quantile regressions : an application to firm growth

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Distante, Roberta, Petrella, Ivan and Santoro, Emiliano (2018) Gibrat's Law and quantile regressions : an application to firm growth. Economics Letters, 164 . pp. 5-9. doi:10.1016/j.econlet.2017.12.028 ISSN 0165-1765.

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Official URL: https://doi.org/10.1016/j.econlet.2017.12.028

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Abstract

The nexus between firm growth, size and age in U.S. manufacturing is examined through the lens of quantile regression models. This methodology allows us to overcome serious shortcomings entailed by linear regression models employed by much of the existing literature, unveiling a number of important properties. Size pushes both low and high performing firms towards the median rate of growth, while age is never advantageous, and more so as firms are relatively small and grow faster. These findings support theoretical generalizations of Gibrat's law that allow size to affect the variance of the growth process, but not its mean (Cordoba, 2008).

Item Type: Journal Article
Subjects: H Social Sciences > HD Industries. Land use. Labor
Divisions: Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH): Business enterprises -- Growth -- Mathematical models -- United States, Quantile regression
Journal or Publication Title: Economics Letters
Publisher: Elsevier
ISSN: 0165-1765
Official Date: March 2018
Dates:
DateEvent
March 2018Published
27 December 2017Available
19 December 2017Accepted
Volume: 164
Page Range: pp. 5-9
DOI: 10.1016/j.econlet.2017.12.028
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 21 December 2017
Date of first compliant Open Access: 27 June 2019

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