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

E. Cefis, M. Ciccarelli, L. Orsenigo

Research output: Working paperAcademic


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 size-specific.
Original languageEnglish
Place of PublicationUtrecht
PublisherUU USE Tjalling C. Koopmans Research Institute
Number of pages27
Publication statusPublished - 2005

Publication series

NameDiscussion Paper Series / Tjalling C. Koopmans Research Institute
ISSN (Electronic)2666-8238


  • Gibrat's Law
  • Firm Growth
  • Pharmaceutical Industry
  • Heterogeneity
  • Bayesian Estimation


Dive into the research topics of 'Testing Gibrat's Legacy: A Bayesian Approach to Study the Growth of Firms'. Together they form a unique fingerprint.

Cite this