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

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 size-specific.