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Measuring US Pharmaceutical Industry R&D Spending

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Abstract

Government policy debates on pharmaceutical pricing often turn on whether higher drug prices fund greater company-financed R&D spending. In the US, debate breaks down because each side uses a different measure of R&D spending, and the measures are far apart. Government agencies, Congress and consumer groups use government-generated survey data from the National Science Foundation (NSF), and the pharmaceutical industry uses survey data from the Pharmaceutical Research and Manufacturers of America (PhRMA). This issue is also relevant to academic work because some studies use NSF data, and others use PhRMA data. This article illustrates the pros and cons of these survey data series, and offers a more reliable, comprehensive and replicable alternative series, based on Compustat data.

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Table I
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Notes

  1. Perhaps the only unusual feature of the Compustat assets and sales series is that they are about equal up until 1990 but they split afterward. This break reflects the increase in the number of new biotechnology firms (see table I), which garnered considerable assets through public securities offerings between 1990 and 2003, but had yet to generate significant pharmaceutical sales. Even with the break, the two series are highly correlated (correlation = 0.976).

  2. We also considered the ratio of pharmaceutical sales to total sales applied to total R&D. We felt that this ratio would be less accurate for many young small high-R&D firms because, although they could have significant research assets, they may not produce many products, and hence, have little sales. In fact, the sales ratio produced very similar results, perhaps because few small research firms have multiple divisions.

  3. Changes in the distribution of R&D among the divisions of the firms in the respective samples can not explain the differences. NSF figures include all of the US R&D spending of their sample of firms, both pharmaceutical and non-pharmaceutical, while the PhRMA figures explicitly exclude non-pharmaceutical R&D, and the Compustat figures are adjusted for estimated non-pharmaceutical R&D.

  4. The composition of the Compustat and NSF samples can change significantly over time for two reasons. First, new firms are born and old firms are liquidated. Second, firms could be reclassified into different SICs. Compustat classifies a firm by the industry in which it sells the most product. The NSF classifies by the industry in which the largest number of its employees work. Firm classification changes have not had a large impact on the Compustat figures; however, NSF figures have likely been impacted. Pharmaceutical firms typically start out with mostly R&D-related employees, but, as they discover new drugs, they add large sales forces. At that point, a firm could be reassigned to a service SIC group.

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Acknowledgements

No sources of funding were used to assist in the preparation of this study. The authors have no conflicts of interest that are directly relevant to the content of this study.

The authors have both received consultancy fees from various pharmaceutical companies.

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Authors and Affiliations

  1. Finance Department, School of Business, University of Connecticut, Unit-1041F, 2100 Hillside Road, Storrs, Connecticut, 06269-1041, USA

    Joseph Golec & John Vernon

  2. Department of Health Policy and Management, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

    John Vernon

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  1. Joseph Golec
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Correspondence to Joseph Golec.

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Golec, J., Vernon, J. Measuring US Pharmaceutical Industry R&D Spending. Pharmacoeconomics 26, 1005–1017 (2008). https://doi.org/10.2165/0019053-200826120-00004

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