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Testing Gibrat's Legacy: A Bayesian Approach to Study the Growth of Firms

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  • Elena Cefis

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  • Matteo Ciccarelli
  • Luigi Orsenigo

Abstract

Gibrat'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 Info

Paper provided by Utrecht School of Economics in its series Working Papers with number 05-02.

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Length: 27 pages
Date of creation: Nov 2004
Date of revision:
Handle: RePEc:use:tkiwps:0502

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Keywords: Gibrat's Law; Firm Growth; Pharmaceutical Industry; Heterogeneity; Bayesian Estimation;

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Citations

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Cited by:
  1. Ioannis Kessides & Li Tang, 2010. "Sunk Costs, Market Contestability, and the Size Distribution of Firms," Review of Industrial Organization, Springer, vol. 37(3), pages 215-236, November.
  2. Alessandra Colombelli & Naciba Haned & Christian Le Bas, 2011. "On Firm Growth and Innovation. Some new empirical perspectives using French CIS (1992-2004)," ICER Working Papers 07-2011, ICER - International Centre for Economic Research.
  3. Marco Capasso & Elena Cefis & Alessandro Sapio, 2013. "Reconciling quantile autoregressions of firm size and variance–size scaling," Small Business Economics, Springer, vol. 41(3), pages 609-632, October.
  4. E. Cefis & O. Marsili & E.J.J. Schenk, 2006. "The effects of mergers and acquisitions on the firm size distribution," Working Papers 06-17, Utrecht School of Economics.

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