measuring us pharmaceutical industry r&d spending

Pharmacoeconomics 2008; 26 (12): 1005-1017LEADING ARTICLE 1170-7690/08/0012-1005/$48.00/0

© 2008 Adis Data Information BV. All rights reserved.

Measuring US PharmaceuticalIndustry R&D SpendingJoseph Golec1 and John Vernon1,2

1 Finance Department, School of Business, University of Connecticut, Storrs, Connecticut, USA2 Department of Health Policy and Management, The University of North Carolina at Chapel

Hill, Chapel Hill, North Carolina, USA

Government policy debates on pharmaceutical pricing often turn on whetherAbstracthigher 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 consumergroups use government-generated survey data from the National Science Founda-tion (NSF), and the pharmaceutical industry uses survey data from the Pharma-ceutical Research and Manufacturers of America (PhRMA). This issue is alsorelevant to academic work because some studies use NSF data, and others usePhRMA data. This article illustrates the pros and cons of these survey data series,and offers a more reliable, comprehensive and replicable alternative series, basedon Compustat data.

1. Background series derived from Standard and Poor’s Compustatdatabase.

US healthcare costs, including pharmaceutical Government agencies, Congress and consumercosts, are rising rapidly. For example, pharmaceuti- groups typically use government surveys from thecal sales grew from about $US45 billion in 1980, to National Science Foundation (NSF) to judge theabout $US262 billion in 2004. Part of this growth pharmaceutical industry’s R&D spending.[2-6] Thewas due to pharmaceutical price inflation that out- surveys show relatively low spending. The pharma-stripped general consumer price inflation.[1] Debate ceutical industry typically uses survey data from theover the fairness of pharmaceutical price increases is Pharmaceutical Research and Manufacturers ofcontentious, partly because the parties disagree America (PhRMA), which show much higherabout how much of the industry’s growing revenue spending. This discrepancy was observed in Golecis reinvested into R&D. Each side of the debate and Vernon.[7] Although neither the PhRMA nor therelies on a different R&D data survey, which show NSF release the individual company figures that govery different levels of R&D spending. This article into their R&D totals, some[6] are more scepticalshows why these surveys differ and presents a more about the PhRMA figures because they believe thatreliable, comprehensive and replicable R&D data it is in the industry’s interests to overstate them. In

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contrast, the NSF figures come from a survey with The PhRMA series excludes R&D spending of ge-the primary goal of tracking total US R&D for neric firms and many smaller biotech firms.government policy purposes. Indeed, one purpose of The NSF compiles its series from the annualour article is to illustrate an accurate and replicable

Survey of Industrial Research and Development,pharmaceutical R&D data series that could be used

conducted by the Bureau of Census.[17] The NSFfor policy purposes.

series purports to be comprehensive and includes allAcademic studies of pharmaceutical R&D have

company-financed R&D spending performed in thealso used figures from the PhRMA[1,8] or the

US by surveyed firms (both US and foreign owned)NSF.[9,10] Scherer[11] uses PhRMA figures and refers

in the pharmaceutical and medicine manufacturingto lower (presumably NSF) figures used by the

industry (Standard Industrial Classification [SIC] =popular press. Studies of R&D in other industries or283 before 1999, and North American Industrialin aggregate typically use either NSF figures[12,13] orClassification system [NAICS] = 3254 after 1998).Compustat figures.[14,15]

Almost all firms with significant R&D, includingThe primary purpose of our article is to showlarge, small, public and private firms are said to bewhy the NSF, PhRMA and Compustat series di-included. In contrast, PhRMA members are mostlyverge. The results can help researchers decide whichlarge, public, prescription drug firms (NAICS =series best suits their purposes. To our knowledge,325 412), along with a few large public biotechnolo-there has been no detailed study that explains thegy firms (NAICS = 325 414). The broader NSFstrengths and weaknesses of the alternative dataindustry grouping includes medicinal, chemical andsources. Although we study pharmaceutical R&Din vitro diagnostic substance producers (NAICS =data, many of the issues that we cover could be325 411 and 325 413) in addition to prescriptionrelevant for comparisons between NSF R&D figuresdrug manufacturers. Hence, all else equal, the NSFand industry-derived figures for other industries.R&D figures should exceed those of the PhRMA.But because NSF excludes R&D performed by

2. Comparing Pharmaceutical ResearchCROs, and such R&D spending by pharmaceutical

and Manufacturers of America (PhRMA)firms is thought to have grown significantly, NSFand National Science Foundationfigures could be lower than those of the PhRMA.(NSF) Estimates

Figure 1 plots the two series between 1980 and2003. Until 1984, the NSF figures exceeded theEach year, the PhRMA surveys its member firmsPhRMA figures and the two series grew at the samefor data on their R&D spending within and outsideannual rate of about 17%. From 1984 to 1995, thethe US. They aggregate the data across all membersseries diverge somewhat, but the growth differenceand publish the total US R&D and total foreignis only about 2% (PhRMA = 13%, NSF = 11%).R&D spending in their annual report entitled, “Phar-The largest discrepancy comes between 1995 andmaceutical Industry Profile.”[16] The US R&D series2003. The PhRMA figures grow at about 12% com-includes all company-financed R&D spending in thepared with only 5% for the NSF. Based on thisUS by member firms, including R&D performedrecent period, the PhRMA figures suggest that phar-under contract by contract research organizationsmaceutical R&D is still growing robustly, while the(CROs). PhRMA membership includes most largeNSF figures suggest that a significant slowdown hasUS pharmaceutical firms and many large foreignoccurred.firms with significant US prescription drug sales.

© 2008 Adis Data Information BV. All rights reserved. Pharmacoeconomics 2008; 26 (12)

US Pharmaceutical Industry R&D Spending 1007

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Fig. 1. US R&D spending by pharmaceutical (and biotech) firms in the Pharmaceutical Research and Manufacturers of America (PhRMA)and National Science Foundation (NSF) databases between 1980 and 2003. NSF data up until 1998[18] and between 1999 and 2003[19] aretaken from the NSF Industrial R&D Information System website. It is not available before 1980 and is updated with a lag, so the 2003 figureis the latest available. NSF R&D data for other industries are available as far back as 1953 but pharmaceutical industry figures are notseparately available before 1980. The PhRMA series is updated more quickly and all data are taken from the Pharmaceutical IndustryProfile 2005.[16]

One way to judge the reliability of a series is to and 1995, industry assets grew at an annual rate ofconsider the time paths of other variables that are about 9% and sales grew at about 11%. Theserelated to R&D spending but are less susceptible to growth rates are maintained during 1995 and 2003.overstatement or measurement errors. For example, PhRMA and Compustat sales data suggest similarthe time paths of total assets and sales compiled sales growth.1 Growth in the NSF sales series isfrom Compustat, for all US public Pharmaceutical about 8% throughout. Hence, the growth decline andPreparation Manufacturers (SIC = 2834, NAICS = sharp changes in NSF-measured R&D after 1995 are325 412) and Biological Product Manufacturers not reflected in its own sales series.(SIC = 2836, NAICS = 325 414). Also, the US sales The sharp drop in Compustat sales in 2003 is duecompiled by PhRMA and NSF in their respective to a large change in one of the sample firms. Mercksurveys. The data are illustrated in figure 2. spun off its large Medco division in 2003. Medco

Figure 2 shows that total industry assets and sales had $US34.2 billion in sales in 2003. Becausehave grown consistently between 1980 and 2003. Medco is not defined as an SIC 2834 or SIC 2836Indeed, none of these series show the sharp declines firm, its sales are excluded from the Compustat(increases) in 1998 or 2001 (1999 and 2002) observ- sample in 2003. Accounting for this change, theed in the NSF R&D series in figure 1. Between 1984 2003 Compustat sales actually increased. This type

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


1008 Golec & Vernon

of adjustment is not possible with NSF and PhRMA because pharmaceuticals account for the bulk ofdata because they do not make their individual firm their R&D, but some firms such as Johnson &data available. Johnson have considerable non-drug R&D. Al-

though firms do not report R&D spending by divi-

sion, they do report sales and assets by division.3. An Alternative to Traditional R&DSpending Series Compustat gathers this information, but the series

for drug manufacturers only goes back to 1984. WeIn this section, we offer an alternative to the use these data to adjust firms’ reported total R&D to

PhRMA and NSF US pharmaceutical R&D series obtain an estimate of their pharmaceutical R&D.using the Compustat database. Compustat gathers

We consider three approaches to estimating thedata from firms’ financial statements. As with the

pharmaceutical R&D of a firm. A simple approachassets and sales series, we select all pharmaceutical

is to estimate the pharmaceutical R&D of a firm bypreparation manufacturers (SIC = 2834, NAICS =computing the ratio of their pharmaceutical assets to325 412) and biological product manufacturers (SICtotal assets and multiplying this fraction by the= 2836, NAICS = 325 414).firm’s total R&D. This approach assumes that firmsFirms report total R&D in their financial state-distribute their R&D spending uniformly acrossments; hence, R&D figures from some sample firmstheir assets, no matter what type of product is pro-include R&D performed for products other thanduced with the assets. Because pharmaceuticals areprescription drugs. For most, this is not a problem

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Fig. 2. Total sales (or assets) for US pharmaceutical (and biotech) firms in the Compustat, National Science Foundation (NSF) andPharmaceutical Research and Manufacturers of America (PhRMA) databases between 1980 and 2003. Sales up until 1998[20] and between1999 and 2003[19] are taken from the NSF Industrial R&D Information System website. PhRMA sales come from the PharmaceuticalIndustry Profile 2005.[16]



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Foreign and US firms’ total R&DForeign and US firms’ pharmaceutical R&DForeign and US firms’ pharmaceutical R&D − simpleUS firms’ total R&DUS firms’ pharmaceutical R&D1

US firms’ pharmaceutical R&D − simple2

Fig. 3. R&D spending by pharmaceutical (and biotech) firms in the Compustat database between 1984 and 2003. 1 Uses estimates of theratio of R&D spending to assets (R&D intensity) observed for each industry in each year covered by the Compustat database. 2 Computedusing the ratio of pharmaceutical assets to total assets and multiplying this fraction by the firm’s total R&D.

relatively R&D intensive, this approach will likely sions are then summed and subtracted from its totalR&D to obtain its pharmaceutical R&D.underestimate firms’ pharmaceutical R&D.2

Finally, one could ignore the issue and use totalA more sophisticated approach uses estimates offirm R&D as an estimate of its pharmaceutical R&Dthe ratio of R&D spending to assets (R&D intensity)because few companies have large non-pharmaceu-observed for each industry in each year covered bytical divisions. Of the 569 firms with at least 1 yearthe Compustat database. We obtained the estimatesof data during the sample period, only 46 had non-by summing the reported R&D spending for allpharmaceutical divisions. Furthermore, we have notfirms within each industry (SIC) for each year andaccounted for pharmaceutical R&D spending bythen did the same for assets. The ratio of eachfirms whose primary products are in other industriesindustry’s total R&D to total assets for each year is(e.g. Procter and Gamble). If pharmaceutical R&Dits R&D intensity for that year. These intensities areby these firms approximates the non-pharmaceuticalthen matched to the assets of each of our sampleR&D by pharmaceutical firms, then total R&D is afirms’ non-pharmaceutical divisions in each year.reasonable estimate of the pharmaceutical industryTherefore, if a division is in an industry that has lowR&D.R&D intensity, our estimate of the R&D for that

division will be relatively small. The estimated Figure 3 plots the data for the three methods ofR&D for all of a firm’s non-pharmaceutical divi- estimating pharmaceutical R&D. In addition to US-

2 We also considered the ratio of pharmaceutical sales to total sales applied to total R&D. We felt that this ratio wouldbe 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.


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Fig. 4. Pharmaceutical R&D spending by US pharmaceutical (and biotech) firms in the Compustat, and Pharmaceutical Research andManufacturers of America (PhRMA) and National Science Foundation (NSF) databases between 1984 and 2003.

based firms’ R&D, we also present the combined pharmaceutical R&D, and $US42.4 billion using thesimple method.R&D for all US and foreign pharmaceutical and

biotechnology firms included in Compustat. Clear-

ly, including foreign firms will overestimate US 4. Explaining the Differences betweenR&D spending, but it is reassuring to see that the the US R&D Seriesspending pattern over time is very similar for the

We now explain the differences between the NSFcombined foreign and US series or the US-onlyand PhRMA data and our Compustat-based seriesseries.using only US-based firms and adjusting for non-Obviously, the total US R&D series exceedspharmaceutical R&D using industry-specific esti-

those adjusted for non-pharmaceutical divisions, butmates of division R&D intensities. Figure 4 plots

each moves along in a similar pattern over time. Aseach series.

expected, series computed using industry-specificThe Compustat and PhRMA series move togeth-

estimates of division R&D intensities exceeds theer over time, with the Compustat series exceeding

one using simple percent-of-assets estimates. This the PhRMA series. Although the two are highlymeans that firms’ non-pharmaceutical divisions are correlated between 1984 and 2003 (correla-in industries that are less R&D intensive than the tion = 0.995), they start to diverge in 1990. Thispharmaceutical industry. But the differences be- could be expected because the Compustat seriestween the series are usually small in any case. For includes many small firms that are not PhRMAexample, in 2003, total US pharmaceutical R&D members. Table I shows that the number of smallwas $US45.5 billion compared with $US44.3 billion firms grows significantly starting in 1990, and manyusing the industry-specific method to adjust for non- relatively small firms spend heavily on R&D. The



number of Compustat firms more than doubles,from 218 in 1990 to 454 in 2003 (PhRMA had only35 members in 2003). The new firms, many of thembiotech, account for a growing share of the totalR&D spending. In 1990, biotech firms accounted foronly $US298 million of $US7.99 billion of industryR&D (3.8%), but in 2003, they accounted for$US7.15 of $US44.37 billion of R&D (16%).

The pattern of the NSF series is much moredifficult to explain compared with the other twoseries. The NSF series moves with the other twoseries up until 1995, but even during this period, theNSF figures never exceed the Compustat figures andonly exceed the PhRMA figures in 1984. This isunexpected because, as noted above, the NSFfigures purportedly cover a broader industry groupthan that covered by PhRMA and our Compustat

Table I. Number of firms in the Compustat and National ScienceFoundation (NSF) pharmaceutical industry R&D samples[19,21]

Year Firms in the Firms in theCompustat sample (n) NSF sample (n)

1986 172 121

1987 178 443

1988 185 442

1989 193 439

1990 218 436

1991 251 436

1992 282 409

1993 305 258

1994 330 400

1995 387 339

1996 412 100

1997 406 199

1998 430 151

1999 446 174

2000 430 135

2001 430 347

2002 457 313

2003 454 299series. Furthermore, the NSF purportedly includespublic and private firms of all sizes. PhRMA and

while US firms spent $US14.6 billion on foreignCompustat include only public companies and

pharmaceutical R&D.[19,22]

PhRMA includes mostly large public brand-nameThe NSF figures are smaller than the associated

prescription drug firms.Compustat and PhRMA figures because the NSF’s

One reason that the Compustat figures exceed sample may include fewer firms, exclude somethose of the NSF could be that the Compustat figures high-R&D firms or include firms that under reportinclude R&D spending in foreign countries by US their R&D figures. Each possibility cannot befirms. However, this would not explain why the checked conclusively because neither the list of NSFPhRMA figures exceed those of the NSF, because sample firms nor individual firm R&D figures arethe PhRMA figures exclude foreign spending.3 Con- publicly available because of privacy concerns.versely, both the PhRMA and NSF figures include Some general evidence on these possibilities canR&D spending in the US by foreign firms, while the be found in a study commissioned by the NSF. HallCompustat figures do not. To the extent that foreign and Long[23] were given access to the NSF raw datafirms spend more on R&D in the US than US firms and studied the differences between NSF R&Dspend abroad, the Compustat figure will actually figures and those computed from Compustat for theunderestimate total US pharmaceutical R&D spend- aggregate of all industries. They did not examineing. Indeed, foreign firms spent $US34.9 billion on differences for specific industries. They report thatUS pharmaceutical R&D between 1999 and 2004, the NSF figures could be less accurate than Compu-

3 Changes in the distribution of R&D among the divisions of the firms in the respective samples can not explain thedifferences. 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 areadjusted for estimated non-pharmaceutical R&D.


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stat figures because the NSF may not accurately NSF CRO figures grow more slowly than the origi-capture CRO R&D, and the CRO R&D that it does nal NSF series. But this contradicts the notion thatcapture appears in a separate category (Scientific CRO spending has grown strongly in recent years.R&D Services [NAICS = 5417]). This could be im- The drop in growth after 1995 could be explainedportant in our case because PhRMA and Compustat by a difference in R&D definitions. The PhRMAinclude pharmaceutical CRO R&D spending. and Compustat definition is the US generally ac-

We were able to consider this possibility because cepted accounting principles (GAAP) definition,the NSF provides some CRO data for the pharma- which includes post-marketing R&D. The NSF sur-ceutical industry, although the data is reported only vey excludes R&D spent after a product is marketed.every other year before 1993. Pharmaceutical CRO Post-marketing R&D includes phase IV and manu-figures up until 1998[21] and between 1999 and facturing process R&D. PhRMA reports R&D bro-2003[19] are taken from the NSF Industrial R&D ken down by clinical phase. They show thatInformation System website. For estimates in miss- phase IV spending started growing quickly in 1995,ing years, figures for the 2 adjacent years are aver- hence, this exclusion by the NSF could account foraged. Figure 5 illustrates the new NSF series after the divergence after 1995.adding the CRO figures to the original series. Hall and Long[23] suggest other reasons that the

Adding CRO R&D to the original NSF series NSF data could be less reliable. These include con-eliminates the divergence between the NSF and fusing survey instructions and unclear R&D defini-PhRMA series that started in 1990. However, CRO tions that lead firms to make improper R&D esti-R&D does not explain the sharp drop in R&D mates. For example, financial statements cover fis-growth after 1995. Indeed, R&D growth from 1995 cal years, whereas the NSF asks for calendar yearto 2003 is now closer to 4% than 5% because the figures. But some firms may report their partial

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Fig. 5. US pharmaceutical R&D spending between 1984 and 2003 for Compustat, and Pharmaceutical Research and Manufacturers ofAmerica (PhRMA) and National Science Foundation (NSF) databases after adding contract research organizations’ (CROs) spending to theNSF.



fiscal figures to the NSF because they do not have The NSF warns that “The statistics from thiscalendar year figures at the time of the survey. survey are better indicators of changes in, ratherCompustat avoids the problem by using fiscal year than absolute levels of, R&D spending and person-figures and defining how fiscal years map to calen- nel. Nevertheless, the statistics are often taken to bedar years. Hall and Long[23] also found that the NSF a continuous time series prepared using the samenever contacted some firms with inaccurate figures collection, processing, and tabulation methods.to clarify how R&D should be reported, and that Such uniformity has not been the case.”[24] But thissome firms received surveys in some years but not in may be more relevant to the prime statistic: total USothers. R&D. Clearly, since 1995, even the rate of change in

the NSF’s pharmaceutical R&D has been erratic.As we do not have access to the NSF firm-leveldata, we cannot compare the compositions of the The NSF acknowledged that some of the problemNSF and Compustat samples. But in 1986, the NSF with the pharmaceutical series could be becausestarted to report the number of firms in their industry some pharmaceutical firms previously grouped withsamples (see table I). The PhRMA does not report pharmaceuticals and medicines (NAICS 3254),the number of firms included in each year, but the were reassigned to the drugs and druggists wholesal-number is relatively small (only 35 members in ers group (NAICS 4222).[25] They suggest that those2003). who wish, could simply combine the R&D for the

two categories. But there are problems with thisClearly, the composition of the NSF sample isapproach. First, one cannot generate a historicalmore volatile than that of the Compustat sampletime series because figures for NAICS 4222 were(e.g. the number of firms in the NSF sample de-not reported before 2003. Second, NAICS 4222clined from 339 in 1995 to 100 in 1996). Theincludes many true wholesalers, and their R&DCompustat sample changes year to year as newshould not be included in the total of pharmaceuticalfirms are born and old firms merge or liquidate, butmanufacturers’ R&D. Finally, if one combines thethe sample grows steadily over time.4 The NSF has2003 figures that the NSF reports in the brief forchanged its sampling methods many times duringNAICS 3254 and NAICS 4222, the total is still athe 1980–2002 period.[24] According to the NSFrelatively low $US25 billion. Our Compustat figuredescription of its sampling methods, even largefor 2003 is $US44.4 billion.firms can move in or out of its sample in particular

years. The slow growth in the NSF R&D series after Even if the NSF R&D figures are understated for1995 could be explained by the sharp drop in the various reasons, public policy debates often consid-number of firms in its sample after 1995. A signif- er R&D as a proportion of sales as opposed to theicant change in sampling methods occurred, starting absolute number. If the NSF figures underestimatewith the 1995 sample. But the sharp drop in R&D in R&D, perhaps its industry sales figures are also2001 is not consistent with the sharp increase in the underestimated so that the ratio of R&D to sales isnumber of sample firms in that year. unaffected. Figure 6 plots this ratio for the three

4 The composition of the Compustat and NSF samples can change significantly over time for two reasons. First, newfirms are born and old firms are liquidated. Second, firms could be reclassified into different SICs. Compustat classifies afirm by the industry in which it sells the most product. The NSF classifies by the industry in which the largest number ofits employees work. Firm classification changes have not had a large impact on the Compustat figures; however, NSFfigures have likely been impacted. Pharmaceutical firms typically start out with mostly R&D-related employees, but, asthey 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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Fig. 6. Ratio of US pharmaceutical R&D spending to US sales between 1984 and 2003 for Compustat, Pharmaceutical Research andManufacturers of America (PhRMA) and National Science Foundation (NSF) databases. CRO = contract research organizations.

samples using sales data from figure 2 and R&D First, as noted earlier, growth in the number ofdata from figure 5. biotech firms since 1996 has boosted the R&D to

sales ratio because these firms spend heavily onFigure 6 shows that the NSF R&D to sales ratio isR&D compared with the level of their sales. Lessabout half that of the PhRMA figure for most years.importantly, the jump in 2003 is accentuated by theIt is also less than the Compustat figure in each year

and less than half the Compustat figure in recent large drop in Merck sales due to the Medco spinoff.years. The NSF time series pattern is similar to that After adjusting for Medco’s sales, the ratio stillof the PhRMA, but both differ from the Compustat increases, but not as sharply. PhRMA does not in-pattern, particularly after 1996. There are two rea- clude most of these biotech firms. The NSF figuressons for the upward trend in the Compustat figures. should include them, but there is no way to check

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this. If they were included, one would expect to see of large numbers of relatively small biotechnologysome increase in the ratio in recent years; however, firms has become more important.the trend in NSF figures is actually down. We argue that the Compustat series has three

Finally, dollars of R&D spending and even the advantages. First, the data are reported in auditedratio of R&D to sales could be misleading because financial statements. Companies have incentives tothe underlying time path of real pharmaceutical re- report accurately because the company and auditorsearch activity could look different from dollar can be fined and sued by the Securities and Ex-spending if the costs of the inputs to research change Commission or shareholders for materialprojects rise at different rates over time than general discrepancies. Neither the NSF nor the PhRMA datainflation rates. To get an idea of the time path of the are independently audited. Second, the Compustatreal level of pharmaceutical R&D, consider figure 7. sample of firms appears to be more comprehensiveIt plots the aggregate number of commercial investi- and stable over time. Data from the PhRMA covergational new drugs (INDs) being monitored by the only its members (35 firms in 2003). CompustatUS FDA by year for the years 1990 and 2003.[26]

figures include many biotechnology companies thatThese are the years when one or more of the R&D are excluded from the PhRMA sample.[11] The NSFspending series start to diverge from the others. claims to cover both private and public firms, but inWhenever a firm wants to start human testing for a many years it covers fewer firms than the Compustatnew drug, they must file an IND with the FDA. The sample, and the NSF sample size fluctuates consid-IND contains a firm’s early laboratory data along erably over time. Finally, the Compustat series iswith a step-by-step plan for the phases of human replicable with access to Standard and Poor’s Com-clinical trials. Each year of development, the firm pustat, while the NSF and the PhRMA do not releasemust report its progress to the FDA until trials end firm-level data, for privacy reasons. Therefore, thesuccessfully, the firm stops the trials and withdraws accuracy of the Compustat figures for individualits IND or the FDA orders the firm to stop the trials. companies can be freely checked online using the

The time path of INDs is similar to the time paths SEC’s Electronic Data Gathering, Analysis and Re-of the Compustat and PhRMA R&D series. It has no trieval (EDGAR) system[27] of public company fi-dips in 1998 and 2001, unlike the NSF series. There- nancial statement filings.fore, real pharmaceutical R&D activity seems to

The NSF series exhibits a number of problems,follow the dollar R&D spending reported by Com-some of which are shared by the PhRMA series. Thepustat and PhRMA quite closely.appendix (see the supplementary material [‘Ar-ticlePlus’] at http://pharmacoeconomics.adison-

5. Conclusions line.com) compares the characteristics of each of theseries discussed above. Although some believe thatthe NSF series is more objective because it is con-After comparing three series of estimates for USstructed by a government agency (the NSF), thepharmaceutical R&D spending, we believe that theevidence shows that it behaves erratically in someseries constructed from the financial statement datayears and appears to understate R&D, particularlycompiled by Compustat is probably the most accu-after 1995. The NSF R&D series does not grow in arate. The Compustat and PhRMA series behavepattern similar to its own sales series. The number ofsimilarly over time, except recently. Large membersfirms in the NSF sample changes erratically overof the PhRMA account for the bulk of the industry’stime, although not always in the same direction asR&D spending, but recently, the combined spending


1016 Golec & Vernon

3. Light D, Warburton R. Extraordinary claims require extraordi-the R&D figures. This suggests that the samplenary evidence. J Health Econ 2005; 24: 1030-3

composition changes significantly in particular 4. Public Citizen. America’s other drug problem: a briefing bookon the Rx drug debate. Washington, DC: Public Citizen Con-years.gress Watch, 2003

Overall, our results suggest that those consider- 5. Public Citizen. Rx R&D myths: the case against the druging using NSF data to study R&D spending in industry’s R&D scare card. Washington, DC: Public Citizen

Congress Watch, 2001 Julindividual industries should compare the consisten-6. Angell M. The truth about the drug companies: how they

cy of the NSF data over time with Compustat- and deceive us and what to do about it. New York: Random HousePublishing Group, 2004industry-generated data series. We have shown that

7. Golec J, Vernon J. New estimates of pharmaceutical researchthe Compustat-based series is more reliable andand development spending by US-based firms from 1984 to

comprehensive than the alternative series, at least 2003. Managerial Decision Econ 2007; 28: 481-38. Cockburn I. The changing structure of the pharmaceutical in-for the pharmaceutical industry. Because the Com-

dustry. Health Aff 2004; 23: 10-22pustat series is also replicable by interested parties, 9. Okunade A, Murthy V. Technology as a ‘major driver’ of health

care costs: a cointegration analysis of the Newhouse conjec-it provides a common basis for public policy debate.ture. J Health Econ 2002; 21: 147-59Finally, it would be interesting to see if pharma-

10. Zinner D. Medical R&D at the turn of the millennium. Healthceutical R&D figures reported by industry sources Aff 2001; 20: 202-9

11. Scherer F. The pharmaceutical industry: prices and progress.in other countries exceed the government-producedN Engl J Med 2004; 351: 927-32

figures of those countries. We do not attempt an 12. Lichtenberg F. The private Rand D investment response toextensive analysis here, but we find the opposite for federal design and technical competitions. Am Econ Rev 1986;

78: 550-9the UK, the largest pharmaceutical R&D spender13. Griliches Z. Productivity, R&D, and the data constraint. Am

among European countries. The UK Office of Na- Econ Rev 1994; 84: 1-2314. Cockburn I, Griliches Z. Industry effects and appropriabilitytional Statistics pharmaceutical R&D figures over

measures in the stock market’s valuation of R&D and patents.1995–2003 range between 23% and 31% larger thanAm Econ Rev 1988; 78: 419-23

figures reported by the European Federation of 15. Waring G. Industry differences in persistence of firm-specificreturns. Am Econ Rev 1996; 86: 1253-65Pharmaceutical Industries and Associations

16. PhRMA. Pharmaceutical Industry Profile 2005 [online]. Avail-(EFPIA).[28,29] The larger government figures make able from URL: http://members.phrma.org/publications/publi

cations/17.03.2005.1142.cfm [Accessed 2008 Oct 2]sense because UK government figures include17. National Science Foundation: Bureau of Census. Survey ofspending by firms of all sizes, while EFPIA figures

Industrial Research and Development [online]. Available fromonly include R&D spending of its members, typical- URL: http://www.nsf.gov/statistics/srvyindustry/ [Accessed

2008 Sep 26]ly just the larger firms.18. National Science Foundation. Industrial research and develop-

ment information system: historical data 1953–98 [online].Acknowledgements Available from URL: http://www.nsf.gov/statistics/iris/

search_hist.cfm?indx=10 [Accessed 2005 Dec 21]19. National Science Foundation [online]. Available from URL:No sources of funding were used to assist in the prepara-

http://www.nsf.gov/statistics/nsf07314/content.cfm?pub_idtion of this study. The authors have no conflicts of interest=2488&id=2 [Accessed 2005 Dec 21]that are directly relevant to the content of this study.

20. National Science Foundation. Industrial research and develop-The authors have both received consultancy fees from ment information system: historical data 1953–98 [online].

various pharmaceutical companies. Available from URL: http://www.nsf.gov/statistics/iris/search_hist.cfm?indx=27 [Accessed 2005 Dec 21]

21. National Science Foundation. Industrial research and develop-References ment information system: historical data 1953–98 [online].

Available from URL: http://www.nsf.gov/statistics/iris/1. Giaccotto C, Santerre R, Vernon J. Drug prices and research andsearch_hist.cfm?indx=12 [Accessed 2005 Dec 21]development investment behavior in the pharmaceutical indus-

try. J Law Econ 2005; 48: 195-214 22. US Department of Commerce. Bureau of Economic Analysis:2. Light D, Lexchin J. Will lower drug prices jeopardize drug International Economic Accounts. Foreign direct investment

research? A policy fact sheet. Am J Bioeth 2004; 4: W1-4 in the US: financial and operating data for US affiliates of



foreign multinational companies [online]. Available from 27. US Securities and Exchange Commission. Electronic DataURL: http://www.bea.gov/bea/di/di1fdiop.htm [Accessed Gathering, Analysis and Retrieval (EDGAR) system [online].2006 Mar 12] Available from URL: http://www.sec.gov/edgar.shtml [Ac-

23. Hall B, Long W. Differences in reporting R&D data on the NSF/ cessed 2008 Sep 26]Census RD-1 form and the SEC 10-K form: a micro-data

28. European Federation of Pharmaceutical Industries and Associa-investigation, report to the National Science Foundation; 1999tions (EFPIA). The pharmaceutical industry in figures. Brus-[online]. Available from URL: http://elsa.berkeley.edu/~bh-

hall/papers/HallLong99%20R&Ddata.pdf [Accessed 2008 sels: EFPIA, 2005Sep 25] 29. Owens J, for the Office for National Statistics. Research and

24. National Science Foundation. Survey of industrial research andexperimental development (R&D) statistics, 2003. Econ

development [online]. Available from URL: http://www.Trends 2005 Aug; 621: 28-52 [online]. Available from URL:nsf.gov/statistics/showsrvy.cfm?srvy_CatID=4&srvy_Seri=http://www.statistics.gov.uk/articles/economic_trends/et62113 [Accessed 2005 Dec 21]_owen.pdf [Accessed 2008 Sep 25]25. National Science Foundation. Increase in US R&D expenditures

reported for 2003 makes up for earlier decline [online]. Avail-able from URL: www.nsf.gov/statistics/infbrief/nsf06305/nsf06305.pdf [Accessed 2005 Dec 21] Correspondence: Joseph Golec, Finance Department, School

26. US Food and Drug Administration, Center for Drug Evaluation of Business, University of Connecticut, Unit-1041F, 2100and Research. CDER original INDs received: calendar years

Hillside Road, Storrs, CT 06269-1041, USA.1986–2006 [online]. Available from URL: http://www.fda.E-mail: [email protected]/cder/rdmt/Cyindrec.htm [Accessed 2005 Dec 21]


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