The Relationship Between Firm Size and Firm Growth in the U.S. Manufacturing Sector

This paper investigates the dynamics of firm growth in the U. S. manufacturing sector in the recent past. I use panel data on the publicly traded firms in the U. S. manufacturing sector: from a universe of approximately 1800 firms in 1976, I am able to follow most of them for at least three years, and over half of them from 1972 until 1983. I consider several problems, both econometric and substantive, which exist in analyzing this kind of data: the choice of size measure, the role of measurement error, and the effect of selection (attrition) on estimates obtained from this sample. Using time series methods, suitably modified for panel data (where the number of time periods per observational unit is small), I analyze the behavior of employment over time and find that most of the change in employment in any given year is permanent in the sense that there is no tendency to return to the previous level. Year-to-year growth rates are largely uncorrelated and there is almost no role for measurement error. I find that Gibrat's Law is weakly rejected for the smaller firms in my sample and accepted for the larger firms; Other measures of size produce essentially the same results. Correction for attrition from the sample changes the results somewhat: I use a simple model in which firms leave the sample because they are small and/or undervalued (since many exits are acquisitions) and find that Tobin's Q, the raio of market valuation to the value of the underlying assets of the firm, is a much better predictor of exit probability than size alone (firms with low Q are more likely to exit the sample). When I use this estimate of the probability of exit to control for selection bias, Gibrat's Law is weakly rejected for firms of all sizes and there are significant positive effects on firm growth from both investment in physical capital and R&D expenditures, with R&D having a somewhat higher net effect.