From Gibrat'S Legacy To Gibrat'S Fallacy. A Bayesian Approach To Study The Growth Of Firms
AbstractWe aim at testing Gibrat's Law, a building block of the corporate growth dynamics. Using a Bayesian statistical framework that nests previous approaches, we provide evidence against Gibrat's law on average, within or across industries. Notwithstanding, data show only weak evidence of mean reversion, i.e. initial larger firms do not grow relatively slower than smaller firms. Moreover, differences in growth rates and in size steady state are persistent and firm-specific. Previous results confirming Gibrat's argument are likely to be incorrect being based on models that do not exploit appropriately all information contained in a panel data set.
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Bibliographic InfoPaper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2002-19.
Length: 52 pages
Date of creation: Oct 2002
Date of revision:
Publication status: Published by Ivie
Gibrat's Law; Panel Data; Heterogeneity; Bayesian Estimation;
Other versions of this item:
- Elena Cefis & Matteo Ciccarelli & Luigi Orsenigo, 2002. "From Gibrat’s legacy to Gibrat’s fallacy. A Bayesian approach to study the growth of firms," Working Papers 0206, University of Bergamo, Department of Economics.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
- O31 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
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