Abstract

Pharmaceuticals is a relatively large and mature industry, and of growing significance. The industry has stimulated extensive research on determinants of its growth and development. Specifically, the distribution of firm size has attracted significant attention, due to tis relevance as an indicator of degree of industrial concentration. A large part of this literature has focused, since the early contributions, on the explanation of the shape of firm size distribution in the industry at a given point in time by reference to steady state arguments. The dynamics in question have been relatively neglected however. The main objective of this paper is to help fill this gap. It is shown that interesting issues arise when one considers how firm structure evolves over time, rather than simply attending to equilibrium implications of processes. 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; specifically, on which characteristics lead to which kinds of dynamics. To that end, we propose a diffusion model to examine the spatial dynamics of firm size. Instead of assuming a steady state as is standard practice, we consider that firm size fluctuates around its long run stationary equilibrium, according to a double process of temporal drift and random disturbance. An empirical application to real data from the Pharmaceutical industry helps fill a second gap in the literature, as only a few diffusion studies have employed real statistical data when analyzing firm size dynamics. Our empirical application confirms results presented elsewhere and offers some new insights.

Highlights

  • Pharmaceuticals is a complex industry, bound by stringent government mandates, risk averse consumer population, and an expanding cost structure of drug production and compliance

  • We propose a diffusion model to examine the spatial dynamics of firm size

  • An empirical application to data from the Pharmaceutical industry helps fill a second gap in the literature, as only a few diffusion studies have employed real statistical data when analyzing firm size dynamics

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Summary

The Economics of the Pharmaceutical Industry

Pharmaceuticals is a complex industry, bound by stringent government mandates, risk averse consumer population, and an expanding cost structure of drug production and compliance. According to DiMasi of Tufts Centre for the Study of Drug Development, the cost of bringing a new drug to market (including the cost of clinical trials and failures) is estimated at around $820 millions in 2000 dollars. According to DiMasi of Tufts Centre for the Study of Drug Development, the cost of bringing a new drug to market (including the cost of clinical trials and failures) is estimated at around $820 millions in 2000 dollars1 These costs are roughly split between pre-clinical. It is noteworthy to mention that the time it takes to bring a drug to market has increased, with the biggest rise in the clinical-trials phase It takes an average of 12 years to develop a new drug from start to finish, depending on the nature of the molecule and of the disease it is intended to cure. We present and analyze a dynamic stochastic model for the evolution of density of firm size within the Pharmaceutical industry

Theoretical Framework
The Model
Empirical Analysis
Findings
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