Gibrat's law revisited - A study on Gibrat's law with models of industry dynamics

Abstract

This thesis is a literature review that studies Gibrat’s law and the firm dynamics with the help of conventional models of industry dynamics. Robert Gibrat formulated one of the first models of industry dynamics already in 1931 and in this model he used the assumption of law of proportional effect that is today understood as Gibrat’s law. A common interpretation of the Gibrat’s law presented in many articles is that a firm’s growth rate and its size are independent of each other. This thesis uses this interpretation of the law. Put differently, the law states that small firms grow at the same rate as large firms. The power of Gibrat’s law is the primary research question and a common theme that is carried throughout this thesis. In addition, this thesis touches briefly on what creates firm growth.

In general, the extensive literature has rejected the law, but various studies have found that the law is valid for certain subsamples or time periods. Therefore, this thesis argues that the question is not whether Gibrat’s law is valid, but rather when and with what restrictions it is valid. This thesis also tries to understand why Gibrat’s law should be accepted. One of the aims of this study was to identify testable hypothesis that would more accurate. Hence, they would further clarify the role of Gibrat’s law.

These questions are studied with help of the theory on firm and industry dynamics. This makes the approach more unique as existing studies focuses heavily on empirical testing. As primary material, this thesis uses the existing empirical literature on Gibrat’s law and four models of industry dynamics by Hopenhayn (1992), Jovanovic (1982), Cooley & Quadrini (2001) and Murto & Terviö (2010). Hopenhayn’s model is analyzed more thoroughly than the rest of the industry dynamic models.

The conclusion of this study is that in the majority of the cases small firms indeed grow faster than large firms. This is supported both by theoretical and empirical evidence. It can be case that sometimes the growth is observed as stochastic, but it would seem that the underlying process is indeed deterministic as there are profit-maximizing firms that act and make decisions. These findings could explain why sometimes studies reject the law and sometimes they accept it. Hopenhayn’s model is a stand-alone model, but it opens the possibility for other models were Gibrat’s law could be a special case. Thus, the conclusion is that Gibrat’s law can’t be a valid. The three other models that were presented more or less confirmed that the law can’t be valid.

Furthermore, it was possible to find new testable hypothesis. For example Gibrat’s law could be tested for an industry where there has been a large increase in cost of entry, preferably over a shorter period time. The expected result is that after the increase in cost of entry, there should be less deviation from Gibrat’s law. Finally, this thesis views that superior productivity creates firm growth.