Science and Engineering Indicators 2012

Measured and Unmeasured R&D

The statistics on U.S. R&D discussed in this section reflect the National Science Foundation's periodic National Patterns of R&D Resources reports and data series with a comprehensive account of total U.S. R&D performance. The National Patterns data, in turn, derive from five major NSF surveys of organizations that perform the bulk of U.S. R&D. These are:

• Survey of Federal Funds for R&D
• Survey of R&D Expenditures at Federally Funded R&D Centers
• Business R&D and Innovation Survey
• Survey of R&D Expenditures at Universities and Colleges
• Survey of R&D Funding and Performance by Nonprofit Organizations

National Patterns integrates the R&D spending and funding data from these separate surveys into U.S. R&D totals, which are calculated on a calendar-year basis, disaggregated for the main performing sectors and funding sources. Due to practical constraints, some elements of R&D performance are omitted from the U.S. totals. In evaluating R&D performance trends over time and in international comparisons, it is important to be aware of these omissions.

To reduce cost and respondent burden, the U.S. business R&D estimates are derived from a survey of R&D-performing companies with five or more employees. Accordingly, no estimates of R&D performance currently are available for companies with fewer than five employees. (NSF is currently working on the design and implementation of a Microbusiness Innovation and Science and Technology (MIST) Survey, which will collect data from companies with fewer than five employees.)

Social science R&D had, until 2008, been excluded from the U.S. business R&D statistics. R&D in the humanities and other non-S&E fields (such as law) has been excluded from the U.S. academic R&D statistics. (Other countries include both in their national statistics, making their national R&D expenditures relatively larger when compared with those of the United States.) Changes are now underway in both these respects in the U.S. surveys. NSF's new U.S. Business R&D and Innovation Survey (see BRDIS sidebar later in this chapter), fielded for the first time in 2009 (to collect 2008 data), now includes social science R&D ($1.2 billion in 2008) and will also better capture the full range of business R&D funded by others. NSF is also now fielding a redesigned Higher Education R&D Survey (starting with the 2010 academic fiscal year), which will include non-S&E R&D expenditures in the reported totals.

The statistics for academic R&D track research expenditures that are separately budgeted and accounted (notably, sponsored research). But U.S. universities generally do not maintain records for the "departmental research" performed by faculty, which then cannot be included in the academic R&D totals. This can be a significant limitation in international R&D comparisons, as department research estimates are often included in the national statistics of other countries. (For a further discussion, see sidebar "Government Funding Mechanisms for Academic Research" later in this chapter.)

Likewise, the activity of individuals performing R&D on their own time and not under the auspices of a corporation, university, or other organization is omitted from official U.S. R&D statistics.

Statistics on R&D performance by state governments had only been sporadically collected until 2006 and 2007, when NSF and the U.S. Census Bureau first fielded a survey on this topic (now being conducted every 2 years; state government R&D performance totals only several hundred million dollars annually). Finally, NSF has not fielded a full survey on R&D performance by nonprofit organizations since 1998—the National Patterns performance figures for this sector in the national R&D totals are estimated.

The National Center for Science and Engineering Statistics has commissioned the National Research Council's Committee on National Statistics (CNSTAT) to form a panel to review the methodologies used in developing the National Patterns dataset. The panel began work in mid-2011.

Location of R&D Performance by State

Distribution of R&D expenditures among the U.S. states

In 2008, the 10 states with the largest R&D expenditure levels accounted for about 62% of U.S. R&D expenditures that can be allocated to the states: California, New Jersey, Texas, Massachusetts, Washington, New York, Maryland, Michigan, Pennsylvania, and Illinois (table 4-A).* California alone accounted for 22% of the U.S. total, exceeding the next-highest state, Massachusetts, by almost 4 times. The top 20 states accounted for 84% of the R&D total; the 20 lowest-ranking states, around 5% (see appendix tables 4-11 and 4-12).

The states with the biggest R&D expenditures are not necessarily those with the greatest relative concentration of R&D. Among those with the highest R&D/GDP ratios in 2008 were New Mexico, the District of Columbia, Maryland, and Massachusetts (table 4-A). New Mexico is the location of a number of major government research facilities. The District of Columbia is home to major federal science and technology agencies with intramural research labs and R&D management activities. Maryland is also the site of many government research facilities and growing research universities. Massachusetts benefits from both leading research universities and thriving high-technology industries. California has relatively high R&D intensity, but nonetheless is ninth from the top. (Chapter 8 provides additional information on R&D related activities in the states.)

U.S. R&D performance by sector and state

The proportion of R&D performed by each of the main R&D-performing sectors (business, universities and colleges, federal intramural and FFRDCs) varies across the states, but the states that lead in total R&D also tend to be well represented in each of these sectors (table 4-A).

In 2008, R&D performed by the business sector accounted for about 73% of the U.S. R&D total that could be allocated to specific states. Of the top 10 states in total R&D performance, 9 are also in the top 10 in industry R&D. Connecticut, 8th in business-sector R&D and home to substantial pharmaceutical R&D activity, surpasses Maryland in the business R&D ranking.

University-performed R&D accounts for 14% of the allocable U.S. total and mirrors the distribution of overall R&D performance. Only New Jersey and Washington fall out of the top 10 total R&D states, replaced by North Carolina and Ohio.

Federal R&D performance (including both intramural and FFRDCs)—about 12% of the U.S. total—is more concentrated geographically than that in other sectors. Only 5 states—Maryland, California, New Mexico, the District of Columbia, and Virginia—account for 65% of all federal R&D performance.** This figure rises to 80% when the other 5 of the top 10 states—Massachusetts, Tennessee, Washington, Illinois, and Alabama—are included.

Federal R&D accounts for the bulk of total R&D in several states, including New Mexico, which is home to the nation's two largest FFRDCs (Los Alamos and Sandia National Laboratories) and Tennessee (36%) home to Oak Ridge National Laboratory. The high figures for Maryland (55%), the District of Columbia (80%), and Virginia (37%) reflect the concentration of federal facilities and federal R&D administrative offices in the national capital area.

Recent Developments in Innovation-Related Metrics

Innovation is defined as the introduction of new or significantly improved products (goods or services), processes, organizational methods, and marketing methods in internal business practices or in the open marketplace (OECD/Eurostat 2005). R&D and other intangible investments such as investments in software, higher education, and worker training are key inputs driving innovation. Improved and internationally comparable measurements of these inputs and associated outcomes have been identified as important components in evidence-based policymaking. New analytical and policy questions suggest the need for continuous enhancements (NRC 2005, 2007; OECD 2010c, 2010d). Questions include how innovation addresses ultimate social and economic goals, how it may affect (or be affected by) business cycles (economic downturns and recovery), business dynamics (new or small firms), and globalization (Filippetti and Archibugi 2011; Hasan and Tucci 2010; OECD 2010b, 2010c, 2010d; Stiglitz et al. 2009). Ongoing research and data development initiatives in innovation-related metrics include:

• As part of its Innovation Strategy in support of economic growth and recovery, the OECD* has been working on a measurement agenda for innovation, including links between innovation and macroeconomic performance (OECD 2010c). International statistical manuals have been updated or developed. The latter include an updated United Nations System of National Accounts (SNA) manual (EU et al. 2009), which recognizes R&D and other intangibles as investments or capital assets, and a new OECD Handbook on the treatment of intangibles in national economic accounts (OECD 2010a).
• In the United States, the Commerce Department's Bureau of Economic Analysis and NSF's National Center for Science and Engineering Statistics (NCSES) have jointly developed an R&D Satellite Account** which considers R&D as a capital investment with long-term benefits rather than an expense (that is, it capitalizes R&D). This work will guide the incorporation of R&D in U.S. GDP and other national income and product accounts (NIPAs) in 2013, consistent with the revised SNA manual (Aizcorbe et al. 2009; Jorgenson et al. 2006).
• NCSES's new Business R&D and Innovation Survey covers global activities of U.S.-located companies on a broad range of R&D, employment, intellectual property (IP), technology transfer, and innovation variables. See sidebar, "U.S. Business R&D and Innovation Survey."
• NSF Science of Science and Innovation Policy (SciSIP) program supports theoretical and empirical research designed to advance the scientific basis of science and innovation policy. SciSIP-funded research aims to develop, improve, and expand theories, models, analytical tools, data, and metrics bearing on science policy and innovation.
• STAR METRICS (Science and Technology for America's Reinvestment: Measuring the Effect of Research on Innovation, Competitiveness, and Science) is an interagency project conducted under the auspices of the White House Office of Science Technology and Policy (OSTP).*** It seeks to build an infrastructure to integrate data on R&D inputs, outputs, and outcomes in order to analyze the impacts of science investments (Lane and Bertuzzi 2011).

U.S. Business R&D and Innovation Survey

To better understand and measure how R&D is conducted in today's innovation- and global-based economy (NRC 2005), NSF and the U.S. Census Bureau launched a new Business R&D and Innovation Survey (BRDIS). BRDIS expands on R&D data collected by its predecessor, the Survey of Industrial Research and Development, to cover (among other areas) global R&D funding or expenses by U.S.-located businesses, and introduces preliminary innovation and intellectual property questions that will be further developed.

Chapters 3, 4, 6, and 8 in this edition of Science and Engineering Indicators include selected preliminary data from the 2008 pilot survey. Detailed 2008 estimates and data for subsequent survey cycles are available at http://www.nsf.gov/statistics/industry/. BRDIS questionnaires are available at http://www.nsf.gov/statistics/question.cfm#13. Listed below are the main data collection areas.

• Company information:
• Ownership
• Business activities

• Measures of R&D activity paid for by the company:
• Domestic and worldwide sales, revenue, and R&D activity
• Company-funded R&D by business activity, type of costs, and location
• Projected R&D costs
• Capital expenditures for R&D (buildings, software, equipment)

• Measures related to R&D management and strategy:
• Character of work (basic research, applied research, and development)
• R&D applications and R&D in new business areas
• R&D relationships with others outside the company

• Measures of company R&D activity funded by others:
• Funds for worldwide and domestic R&D activity
• R&D funded by others by business activity, type of organization, type of cost, state, and location (domestic vs. foreign)

• Measures of R&D employment:
• R&D headcount (domestic and worldwide) by occupation and sex
• Number of U.S. R&D employees working under a visa (H-1B, L-1, etc.)
• R&D full-time equivalent counts

• Measures of intellectual property (IP), technology transfer, and innovation:
• Participation in activities to introduce new or significantly improve existing goods, services, methods of production and distribution, or support systems
• Selected patenting and licensing information
• Participation in specific technology transfer activities and importance of types of IP protection

For more information see NSF 2008, 2010a, 2010b, and 2010c.

Foreign Direct Investment in R&D

Foreign direct investment (FDI) is one of several channels for the creation, exploitation, and diffusion of new knowledge along with international trade, licensing, and technology partnerships (Saggi 2002). Direct investment is defined as ownership or control of 10% or more of the voting securities of a business (affiliate) in another country. The cross-country location of R&D activities via FDI is driven by factors ranging from costs and long-term market and technological opportunities to infrastructure and policy considerations, such as human resources and intellectual property protection.

Statistics on R&D by affiliates of foreign companies located in the United States, and by foreign affiliates of U.S. MNCs and their parent companies, are from BEA's Survey of Foreign Direct Investment in the United States (FDIUS) and BEA's Survey of U.S. Direct Investment Abroad (USDIA). Affiliate data presented in this section cover majority-owned affiliates, that is, those in which the ownership stake of parent companies totals more than 50%. Annual changes in FDI R&D reflect a combination of mergers and acquisitions; newly built factories, service centers, or laboratories; and activities in existing facilities. Data exclude commercial banks, savings institutions, credit unions, bank holding companies, and financial holding companies

Linking MNC Data from International Investment and Business R&D Surveys

In 2007, the nature of R&D carried out by U.S. affiliates of foreign-owned MNCs was very similar to U.S.-based R&D of U.S. MNC parents: 4.4%–4.5% of R&D expenditures was devoted to basic research, 19.4%–19.9% to applied research, and 75.8%–76.1% to development.

This new insight into the distribution of character of work of MNCs R&D is made possible by linking and comparing reports for 2004–07 from the same set of companies responding to NSF/Census Survey of Industrial Research and Development (SIRD),* the predecessor of BRDIS, with two different BEA surveys: Foreign Direct Investment in the United States and U.S. Direct Investment Abroad.

Federal Budgetary Concepts and Related Terms

Budget authority. This refers to the funding authority conferred by federal law to incur financial obligations that will result in outlays. The basic forms of budget authority are appropriations, contract authority, and borrowing authority.

Obligations. Federal obligations represent the dollar amounts for orders placed, contracts and grants awarded, services received, and similar transactions during a given period, regardless of when funds were appropriated or payment was required.

Outlays. Federal outlays represent the dollar amounts for checks issued and cash payments made during a given period, regardless of when funds were appropriated or obligated.

R&D plant. In general, R&D plant refers to the acquisition of, construction of, major repairs to, or alterations in structures, works, equipment, facilities, or land for use in R&D activities. Data included in this section refer to obligated federal dollars for R&D plant.

Tracking R&D: The Gap between Performer- and Source-Reported Expenditures

In the United States—and in some other OECD countries—the figures for total government support of R&D reported by government agencies differ from those reported by the performers of R&D. In keeping with international guidance and standards, most countries provide totals and time series of national R&D expenditures based primarily on data reported by R&D performers (OECD 2002). Differences in the data provided by funders and performers can arise for numerous reasons, such as the different calendars for reporting government obligations (fiscal years) and performance expenditures (calendar years). In the U.S., there has been a sizable gap between performer and funder data for federal R&D over the past decade or more.

In the mid-1980s, performer-reported federal R&D in the United States exceeded federal reports of funding by $3 billion to $4 billion annually (5%–10% of the government total). This pattern reversed itself, however at the end of the decade: in 1989, the government-reported R&D total exceeded performer reports by almost $1 billion. The government-reported excess increased noticeably from then through to 2007, when federal agencies reported obligating $127 billion in total R&D to all R&D performers ($55 billion to the business sector) compared with $106 billion in federal funding reported by the performers of R&D ($27 billion by businesses). In other words, the business-reported total was some 50% smaller than the federally reported R&D support to industry in FY 2007 (see figure 4-A and appendix table 4-32). These differences in federal R&D totals were seen primarily in DOD funding of development activities by industry. The figures for 2008 and 2009 suggest a narrowing of the federal agency reporting excess, but are primarily the result of a manual imputation procedure for business R&D performers in these years.

Several investigations into the possible causes for the data gap have produced insights but no conclusive explanation. According to a General Accounting Office investigation (GAO 2001):

Because the gap is the result of comparing two dissimilar types of financial data [federal obligations and performer expenditures], it does not necessarily reflect poor quality data, nor does it reflect whether performers are receiving or spending all the federal R&D funds obligated to them. Thus, even if the data collection and reporting issues were addressed, a gap would still exist.

Echoing this assessment, the National Research Council (2005) noted that comparing federal outlays for R&D (as opposed to obligations) to performer expenditures results in a smaller discrepancy. (In FY 2009, federal agencies reported total R&D outlays of $127 billion, compared to a total R&D figure of $124 billion reported by all performers that year. In FY 2007, federal agencies reported R&D outlays of $109 billion, compared to the performer-reported total of $106 billion.)

Major Federal Legislation Related to Technology Transfer and Commercializing R&D

Technology Innovation Act of 1980 (Stevenson-Wydler Act) (Public Law 96-480)—established technology transfer as a federal government mission by directing federal labs to facilitate the transfer of federally-owned and originated technology to nonfederal parties.

University and Small Business Patent Procedures Act of 1980 (Bayh-Dole Act) (Public Law 96-517)—permitted small businesses, universities, and nonprofits to obtain titles to inventions developed with federal funds. Also permitted government-owned and government-operated laboratories to grant exclusive patent rights to commercial organizations.

Small Business Innovation Development Act of 1982 (Public Law 97-219)—established the Small Business Innovation Research (SBIR) program, which required federal agencies to set aside funds for small businesses to engage in R&D connected to agency missions.

National Cooperative Research Act of 1984 (Public Law 98-462)—encouraged U.S. firms to collaborate in generic precompetitive research by establishing a rule of reason for evaluating the antitrust implications of research joint ventures.

Patent and Trademark Clarification Act of 1984 (Public Law 98-620)—provided further amendments to the Stevenson-Wydler Act and the Bayh-Dole Act regarding the use of patents and licenses to implement technology transfer.

Federal Technology Transfer Act of 1986 (Public Law 99-502)—enabled federal laboratories to enter cooperative research and development agreements (CRADAs) with outside parties and to negotiate licenses for patented inventions made at the laboratory.

Executive Order 12591, Facilitating Access to Science and Technology (1987)—issued by President Reagan, this executive order sought to ensure that the federal laboratories implemented technology transfer.

Omnibus Trade and Competitiveness Act of 1988 (Public Law 100-418)—in addition to measures on trade and intellectual property protection, the act directed attention to public-private cooperation on R&D, technology transfer, and commercialization. It also established NIST's Manufacturing Extension Partnership (MEP) program.

National Competitiveness Technology Transfer Act of 1989 (Public Law 101-189)—amended the Federal Technology Transfer Act to expand the use of CRADAs to include government-owned, contractor-operated federal laboratories and to increase nondisclosure provisions.

Small Business Innovation Development Act of 1992 (Public Law 102-564)—extended the existing SBIR program, increased the percentage of an agency's budget to be devoted to SBIR, and increased the amounts of the awards. Also established the Small Business Technology Transfer (STTR) program to enhance the opportunities for collaborative R&D efforts between government-owned/contractor-operated federal laboratories and small businesses, universities, and nonprofit partners.

National Cooperative Research and Production Act of 1993 (Public Law 103-42)—relaxed restrictions on cooperative production activities, which enable research joint venture participants to work together in the application of technologies that they jointly acquire.

National Technology Transfer and Advancement Act of 1995 (Public Law 104-113)—amended the Stevenson-Wydler Act to make CRADAs more attractive to federal laboratories, scientists, and private industry.

Technology Transfer Commercialization Act of 2000 (Public Law 106-404)—broadened CRADA licensing authority to make such agreements more attractive to private industry and increase the transfer of federal technology. Established procedures for performance reporting and monitoring by federal agencies on technology transfer activities.

America COMPETES Act of 2007 (America Creating Opportunities to Meaningfully Promote Excellence in Technology, Education, and Sciences [COMPETES] Act) (Public Law 110-69)—authorized increased investment in R&D; strengthened educational opportunities in science, technology, engineering, and mathematics from elementary through graduate school; and further developed the nation's innovation infrastructure. Among other measures, the act established NIST's Technology Innovation Program (TIP) and called for a President's Council on Innovation and Competitiveness.

America COMPETES Reauthorization Act of 2010 (Public Law 111–358)—updates the America COMPETES Act of 2007 and authorizes additional funding to science, technology, and education programs over the succeeding 3 years. The Act's numerous provisions broadly directed strengthening the foundation of the U.S. economy, creating new jobs, and increasing U.S. competitiveness abroad.

Federal Technology Transfer: Activities and Metrics

Federal technology transfer can take a variety of forms (FLC 2006), including the following:

Commercial transfer. Movement of knowledge or technology developed by a federal lab to private organizations in the commercial marketplace.

Scientific dissemination. Publications, conference papers, and working papers, distributed through scientific/technical channels; other forms of data dissemination.

Export of resources. Federal lab personnel made available to outside organizations with R&D needs through collaborative agreements or other service mechanisms.

Import of resources. Outside technology or expertise brought in by a federal lab to enhance the existing internal capabilities.

Dual use. Development of technologies, products, or families of products with both commercial and federal applications.

Federal tech transfer metrics cover activities among three main classes of intellectual asset management and transfer:

Invention disclosure and patenting. Counts of invention disclosures filed (typically, an inventing scientist or engineer filing a written notice of the invention with the lab's technology transfer office), patent applications filed with the U.S. Patent and Trademark Office (or abroad), and patents granted.

Licensing. Licensing of intellectual property, such as patents or copyrights, to outside parties.

Collaborative relationships for R&D. Including, but not limited to, Cooperative Research and Development Agreements (CRADAs)

In addition, the statutory annual tech transfer performance reporting by agencies with federal labs, established by the Technology Transfer Commercialization Act of 2000, provides data on downstream outcomes and impacts.

Comparing International R&D Expenditures

Comparisons of international R&D statistics are hampered by the lack of R&D-specific exchange rates. Two approaches are commonly used to facilitate international R&D comparisons: (1) express national R&D expenditures as a percentage of GDP or (2) convert all expenditures to a single currency. The first method is straightforward but permits only gross comparisons of R&D intensity. The second method permits absolute level-of-effort comparisons and finer-grain analyses but entails choosing an appropriate method of currency conversion. The choice is between market exchange rates (MERs) and purchasing power parities (PPPs), both of which are available for a large number of countries over an extended period.

MERs represent the relative value of currencies for cross-border trade of goods and services but may not accurately reflect the cost of non-traded goods and services. They are also subject to currency speculation, political events, wars or boycotts, and official currency intervention.

PPPs were developed to overcome these shortcomings (Ward 1985). They take into account the cost differences of buying a similar market basket of goods and services covering tradables and nontradables. The PPP basket is assumed to be representative of total GDP across countries. PPPs are the preferred international standard for calculating cross-country R&D comparisons and are used in all official R&D tabulations of the OECD.*

Because MERs tend to understate the domestic purchasing power of developing countries' currencies, PPPs can produce substantially larger R&D estimates than MERs for these countries. For example, China's 2006 R&D expenditures (as reported to the OECD) are $38 billion using MERs but $87 billion using PPPs. (Appendix table 4-2 lists the relative difference between MERs and PPPs for a number of countries.)

However, PPPs for large, developing countries such as India and China are often rough approximations and have other shortcomings. For example, structural differences and income disparities between developing and developed countries may result in PPPs based on markedly different sets of goods and services. In addition, the resulting PPPs may have very different relationships to the cost of R&D in different countries.

R&D performance in developing countries often is concentrated geographically in the most advanced cities and regions in terms of infrastructure and level of educated workforce. The costs of goods and services in these areas can be substantially greater than for the country as a whole.

R&D Intensity and the Composition of Gross Domestic Product

The structure of a nation's economy can be a consideration in interpreting and comparing national R&D intensity statistics. That is, the relative prominence of major sectors such as agriculture, manufacturing, and services can directly influence the ratio of overall R&D expenditures to gross domestic product. Businesses and organizations differ widely in their relative need for investment in the latest science and technology. So, countries whose overall GDP depends more heavily on advanced technology industries will typically exhibit higher R&D/GDP ratios than other countries.

Agriculture is a comparatively small component (6% or less) for all but 2 of the top 14 R&D performing countries (figure 4-B). The exceptions are India, where agriculture currently accounts for about 16% of its GDP, and China, where it is 10%. Industrial production (manufacturing) is 20%–30% of GDP for all but three of the countries. China is a much higher 47%; South Korea is 39% and Russia 34%. Services are 60%–70% of national GDP for all but 2 of the 14 countries. China is substantially less services-dependent, at 44% of GDP, and India is somewhat less so, at 55%.

Global R&D Expenses of Public Corporations

Most firms that make significant investments in R&D track their R&D expenses separately in their accounting records and financial statements. The annual reports of public corporations often include data on these R&D expenses. Research organizations and consulting companies interested in tracking and ranking businesses compile R&D expenditures and related operations and performance data. According to one such ranking, the 20 public corporations with the largest reported worldwide R&D expenditures spent $129 billion on R&D in 2009 (Booz & Company 2010). The six companies with the largest reported R&D expenses—Roche Holding, Microsoft, Nokia, Toyota, Pfizer, and Novartis—each spent between $7.4 billion and $9.1 billion (table 4-B). Eight companies in the computing and electronic sector spent a total of $50.4 billion (39% of the total for the top 20). Seven companies in the health sector spent a total of $49.5 billion (38% of the total). The remaining five companies on the list are automobile manufacturers and they reported combined spending of $29.1 billion on R&D (23% of the total). The top 20 companies are headquartered in 8 countries, with 9 headquartered in the United States. In addition, most companies in this list have production, distribution, and/or research and technical facilities in multiple countries. (For related industry-level information, see "R&D by Multinational Companies" in this chapter and chapter 6.)

Government Funding Mechanisms for Academic Research

U.S. universities generally do not maintain data on departmental research (i.e., research that is not separately budgeted and accounted). As such, U.S. R&D totals are understated relative to the R&D effort reported for other countries. The national totals for Europe, Canada, and Japan include the research component of general university fund (GUF) block grants provided by all levels of government to the academic sector. These funds can support departmental R&D programs that are not separately budgeted. GUF is not equivalent to basic research. The U.S. federal government does not provide research support through a GUF equivalent, preferring instead to support specific, separately budgeted R&D projects. However, some state government funding probably does support departmental research, not separately accounted, at U.S. public universities.

The treatment of GUF is one of the major areas of difficulty in making international R&D comparisons. In many countries, governments support academic research primarily through large block grants that are used at the discretion of each higher education institution to cover administrative, teaching, and research costs. Only the R&D component of GUF is included in national R&D statistics, but problems arise in identifying the amount of the R&D component and the objective of the research. Moreover, government GUF support is in addition to support provided in the form of earmarked, directed, or project-specific grants and contracts (funds that can be assigned to specific socioeconomic categories).

In several large European countries (France, Germany, Italy, and the United Kingdom), GUF accounts for 50% or more of total government R&D funding to universities. In Canada, GUF accounts for about 38% of government academic R&D support. Thus, international data on academic R&D reflect not only the relative international funding priorities but also the funding mechanisms and philosophies regarded as the best methods for financing academic research.