Abstract
The field of modern biotechnology is thought to have largely begun in 1980, when the United States Supreme Court ruled that a genetically-modified microorganism could be patented. The growth of the Biotechnology industry has stimulated extensive research on its determinants. One of the areas which has attracted a fair amount of attention is the distribution of firm size within an industry. What is less known however, is the dynamics of firm size. This paper considers a statistical model to describe the spatial dynamics of firm size across the biotechnology industry. It is found that firm size fluctuates around its long run stationary equilibrium according to a temporal drift and random disturbance. The empirical results illustrate that diffusion is a potential technique for the analysis of spatial dynamics of firm size.
Highlights
While much attention has been devoted in the economics literature to the explanation of the shape of firm size distribution with reference to steady state arguments [1,2,3,4,5,6,7], the dynamics in question have been relatively ignored
This paper considers a statistical model to describe the spatial dynamics of firm size across the biotechnology industry
In order to confirm that the parameter estimates reliably characterize the real data presented in the descriptive analysis, Figure 4 graphically illustrates the evolution of the firm size distribution over time for the industry, superimposed on histograms which describe the time evolution of the distribution of firm sizes in the data
Summary
While much attention has been devoted in the economics literature to the explanation of the shape of firm size distribution with reference to steady state arguments [1,2,3,4,5,6,7], the dynamics in question have been relatively ignored. Sutton [8] proposes a theory with implications for the evolution of the size distribution but the empirical test of his theory does not include dynamic data. The stochastic process generating the size of a firm in Jovanovic’s model [10] is characterized by a form of heterogeneity, the model implies a monotone convergence, with the size distribution of survivors increasing stochastically over time. The present study builds on Jovanovic, but proposes a framework for the smooth evolution of density of cross-sectional distribution of firm size instead. Information on the shape and time-evolution of the size distribution of firms over an extended period of time can be used to make inferences about an underlying process; on which characteristics lead to which kinds of dynamics
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