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

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Gibrat’s law and quantile regressions : An application to firm growth. / Distante, Roberta; Petrella, Ivan; Santoro, Emiliano.

In: Economics Letters, Vol. 164, 2018, p. 5-9.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Distante, R, Petrella, I & Santoro, E 2018, 'Gibrat’s law and quantile regressions: An application to firm growth', Economics Letters, vol. 164, pp. 5-9. https://doi.org/10.1016/j.econlet.2017.12.028

APA

Distante, R., Petrella, I., & Santoro, E. (2018). Gibrat’s law and quantile regressions: An application to firm growth. Economics Letters, 164, 5-9. https://doi.org/10.1016/j.econlet.2017.12.028

Vancouver

Distante R, Petrella I, Santoro E. Gibrat’s law and quantile regressions: An application to firm growth. Economics Letters. 2018;164:5-9. https://doi.org/10.1016/j.econlet.2017.12.028

Author

Distante, Roberta ; Petrella, Ivan ; Santoro, Emiliano. / Gibrat’s law and quantile regressions : An application to firm growth. In: Economics Letters. 2018 ; Vol. 164. pp. 5-9.

Bibtex

@article{cf24fe2cc830468f9ecc0c908ed69c40,
title = "Gibrat{\textquoteright}s law and quantile regressions: An application to firm growth",
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{\textquoteright}s law that allow size to affect the variance of the growth process, but not its mean (Cordoba, 2008).",
keywords = "Faculty of Social Sciences, Firm growth, Size, Age, Conditional quantiles",
author = "Roberta Distante and Ivan Petrella and Emiliano Santoro",
year = "2018",
doi = "10.1016/j.econlet.2017.12.028",
language = "English",
volume = "164",
pages = "5--9",
journal = "Economics Letters",
issn = "0165-1765",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Gibrat’s law and quantile regressions

T2 - An application to firm growth

AU - Distante, Roberta

AU - Petrella, Ivan

AU - Santoro, Emiliano

PY - 2018

Y1 - 2018

N2 - 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).

AB - 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).

KW - Faculty of Social Sciences

KW - Firm growth

KW - Size

KW - Age

KW - Conditional quantiles

U2 - 10.1016/j.econlet.2017.12.028

DO - 10.1016/j.econlet.2017.12.028

M3 - Journal article

VL - 164

SP - 5

EP - 9

JO - Economics Letters

JF - Economics Letters

SN - 0165-1765

ER -

ID: 222750740