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 InfoPaper provided by Utrecht School of Economics in its series Working Papers with number 05-02.
Length: 27 pages
Date of creation: Nov 2004
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- Cefis, Elena & Ciccarelli, Matteo & Orsenigo, Luigi, 2007. "Testing Gibrat's legacy: A Bayesian approach to study the growth of firms," Structural Change and Economic Dynamics, Elsevier, vol. 18(3), pages 348-369, September.
- 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; Longitudinal Data; Spatial Time Series
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-10-29 (All new papers)
- NEP-COM-2005-10-29 (Industrial Competition)
- NEP-ENT-2005-10-29 (Entrepreneurship)
- NEP-TID-2005-10-29 (Technology & Industrial Dynamics)
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