Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- List of contributors
- Acknowledgments
- 1 Introduction
- Part I Innovation and industry evolution
- Part II Firm growth and market structure
- 6 Heterogeneity and firm growth in the pharmaceutical industry
- 7 Growth and diversification patterns of the worldwide pharmaceutical industry
- 8 Entry, market structure, and innovation in a “history-friendly” model of the evolution of the pharmaceutical industry
- 9 The growth of pharmaceutical firms: a comment
- Part III Policy implications
- Index
- References
7 - Growth and diversification patterns of the worldwide pharmaceutical industry
Published online by Cambridge University Press: 22 September 2009
- Frontmatter
- Contents
- List of figures
- List of tables
- List of contributors
- Acknowledgments
- 1 Introduction
- Part I Innovation and industry evolution
- Part II Firm growth and market structure
- 6 Heterogeneity and firm growth in the pharmaceutical industry
- 7 Growth and diversification patterns of the worldwide pharmaceutical industry
- 8 Entry, market structure, and innovation in a “history-friendly” model of the evolution of the pharmaceutical industry
- 9 The growth of pharmaceutical firms: a comment
- Part III Policy implications
- Index
- References
Summary
Introduction
This chapter investigates some statistical properties of the growth patterns of a large sample of pharmaceutical companies representing the top incumbents worldwide. We articulate our analysis along three complementary directions, which, with an evident lack of precision but, we hope, with a certain degree of suggestiveness, we denote as “temporal,” “cross-sectional,” and “disaggregated.”
With the “temporal” direction of investigation we refer to statistical analyses of the size of the firm in its time evolution – i.e. the study of the time series of firm sizes and growth rates. The point of departure of this kind of analysis is usually a question à la Gibrat, addressing issues concerning the relationships between firm size and its dynamics. The Gibrat benchmark (Gibrat, 1931), also known as the “law of proportionate effect,” postulates that the growth of business firms is a random walk that ultimately yields an asymptotic log-normal size distribution. The evidence concerning these properties, as explored by a rich and growing literature (see, for instance, Dunne, Roberts, and Samuelson, 1988; Evans, 1987; Hall, 1987; Hart and Prais, 1956; and Mansfield, 1962; and, more recently, Amaral et al., 1997; Lotti, Santarelli, and Vivarelli, 2001; and De Fabritiis, Pammolli, and Riccaboni, 2003), roughly supports two main findings: Gibrat's hypothesis is confirmed by the lack of any relationship between the (log) size of firms and their average growth rates, but is violated by a clear negative dependence of the growth rates' variance on size (see Sutton, 1997, for a review).
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- Knowledge Accumulation and Industry EvolutionThe Case of Pharma-Biotech, pp. 208 - 233Publisher: Cambridge University PressPrint publication year: 2006