EconPapers    
Economics at your fingertips  
 

Gibrat’s law and quantile regressions: An application to firm growth

Roberta Distante, Ivan Petrella and Emiliano Santoro

Economics Letters, 2018, vol. 164, issue C, 5-9

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).

Keywords: Firm growth; Size; Age; Conditional quantiles (search for similar items in EconPapers)
JEL-codes: C21 D22 L11 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176517305232
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Gibrat's Law and Quantile Regressions: an Application to Firm Growth (2017) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:164:y:2018:i:c:p:5-9

DOI: 10.1016/j.econlet.2017.12.028

Access Statistics for this article

Economics Letters is currently edited by Economics Letters Editorial Office

More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2024-09-16
Handle: RePEc:eee:ecolet:v:164:y:2018:i:c:p:5-9