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

Elena Cefis (), Matteo Ciccarelli and Luigi Orsenigo

No 05-02, Working Papers from Utrecht School of Economics

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.

Keywords: Gibrat's Law; Firm Growth; Pharmaceutical Industry; Heterogeneity; Bayesian Estimation (search for similar items in EconPapers)
JEL-codes: C11 C23 D21 L11 L25 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-com, nep-ent and nep-tid
Date: Written 2004-11
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Related works:
Journal Article: Testing Gibrat's legacy: A Bayesian approach to study the growth of firms (2007)
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