From Gibrat’s legacy to Gibrat’s fallacy. A Bayesian approach to study the growth of firms
AbstractIn this paper we investigate some properties of the patterns of firmsâ growth. Several recent studies about this topic are based on some version of the so-called Gibrat’s Law, which assumes that firmsâ growth is erratic. We aimed at testing Gibrat’s Law, as a first step towards a more systematic investigation of the patterns of firmsâ growth. Using a Bayesian statistical framework that nests previous approaches, we find that: (i) there seems to be strong evidence against the Gibratâs law on average, within or across industries; (ii) previous results are probably incorrect because they are based on models that do not exploit all information contained in a panel data set, particularly models that do not control for potential heterogeneity in the convergence rates; (iii) estimated steady states differ across units, and firm sizes and growth rates do not converge within the same industry to a common limiting distribution; (iv) there is only weak evidence of mean reversion, i.e. initial larger firms do not grow relatively slower than smaller firms. Differences in growth rates and in size steady state are firm-specific, rather than size-specific; (v) differences in growth rates do not seems to disappear over time.
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Bibliographic InfoPaper provided by University of Bergamo, Department of Economics in its series Working Papers with number 0206.
Length: 44 pages
Date of creation: Oct 2002
Date of revision:
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Gibrat’s law; panel data; heterogeneity; Bayesian estimation; Gibbs sampling;
Other versions of this item:
- Elena Cefis & Luigi Orsenigo & Matteo Ciccarelli, 2002. "From Gibrat'S Legacy To Gibrat'S Fallacy. A Bayesian Approach To Study The Growth Of Firms," Working Papers. Serie AD 2002-19, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- 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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