Testing Gibrat's legacy: A Bayesian approach to study the growth of firms
AbstractGibrat's law is a referent model of corporate growth dynamics. This paper employs Bayesian panel data methods to test for Gibrat's law and its implications. Using a Pharmaceutical Industry Database (1987-1998), we find evidence against Gibrat's law on average, within or across industries. Estimated steady states differ across firms, and firm sizes and growth rates don't converge within the same industry to a common limiting distribution. There is only weak evidence of mean reversion: initial larger firms do not grow relatively slower than smaller firms. Differences in growth rates and in size steady state are persistent and firm-specific, rather than sizespecific.
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Bibliographic InfoArticle provided by Elsevier in its journal Structural Change and Economic Dynamics.
Volume (Year): 18 (2007)
Issue (Month): 3 (September)
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Web page: http://www.elsevier.com/locate/inca/525148
Other versions of this item:
- Elena Cefis & Matteo Ciccarelli & Luigi Orsenigo, 2004. "Testing Gibrat's Legacy: A Bayesian Approach to Study the Growth of Firms," Working Papers 05-02, Utrecht School 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
- D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
- L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
- L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
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