1
Introduction
The Science, Technology, and Economic Policy (STEP) Board of the National Research Council conducted a workshop to assess the utility and policy relevance of the government's data on industrial innovation. The meeting was held on February 28, 1997, at the National Academy of Sciences headquarters in Washington, D.C.
Objectives
The purpose of the workshop was to generate suggestions for improving measurement, data collection, and analysis through the consideration of policy needs and the assessment of existing sources of information and the feasibility of developing new ones. The participants included statisticians and economists concerned with industrial organization and innovation practices, industrial managers, association representatives, government officials representing diverse policy arenas and statistical agencies, and analysts from other industrialized countries and international organizations. This diverse group addressed issues ranging from problems of specific data sources to whether the coordination among agencies or the relationship between the government's and private analysts' data collection could be improved. They also discussed the integration of innovation-related information into measures of firm and national economic performance.
Scope
The workshop was part of a two-year assessment by the STEP Board of changing patterns of private-sector research and development (R&D) and inno-
vation, an effort sponsored by the National Aeronautics and Space Administration (NASA) and the National Science Foundation's (NSF's) Division of Science Resources Studies (SRS). At the NSF's request, the workshop focused on its survey of R&D spending, its recent pilot innovation survey, and the various industrial indicators (patents, patent citations, trade in goods and intangibles, etc.) that are reported every two years in Science and Engineering Indicators.1
The workshop nevertheless took as comprehensive a view as possible of innovation data needs and issues. The principal exception was that data on science and engineering personnel characteristics, as indicators of innovative activity and capacity, were reserved for later consideration. Because of the workshop's broad scope, a number of issues and questions were raised, but discussion was deferred to possible follow-on meetings and working groups. In this way the workshop served as an organizing tool for further efforts to improve the national collection and interpretation of innovation information.
Rationale
There were several reasons for holding this workshop. First, increasing importance is being attached to technology and innovation in national policy debates about economic performance and international competition. Second, major changes are under way in the structure of advanced industrial economies (for example, the growth of service industries relative to manufacturing industries) and in the composition, location, and organization of industrial science and technology activities. Third, changes in public-sector R&D investment and other microeconomics policies ranging from intellectual property protection to economic regulation and corporate taxation are also occurring. Finally, issues of measurement, data collection, and valuation are receiving more attention internationally, for example, in the Organization for Economic Cooperation and Development (OECD), which has sponsored work to improve understanding of the ''knowledge-based economy."
Challenges
However timely, this review poses major challenges. First, progress in developing a theoretical understanding of innovation has been hampered by difficulties in measuring and evaluating its outputs as determinants of industrial performance and economic growth. As a consequence, it is uncertain how to capture changes in a volatile industrial environment that gives off mixed signals. For example, on the one hand, U.S. industrial firms appear to be cutting back on long-term research and the infrastructure to support it. On the other hand, the competitive performance of much of U.S. industry appears to have improved significantly in recent years. Second, because of the distance between the language and decisions of policy makers and the language and practical constraints of analysts
and statisticians, it is no simple matter to determine what information is relevant to policy. Third, budget constraints and reporting burdens on the private-sector limit and may preclude some new data collection efforts, so there is a premium on deriving more value from existing sources, for example, by linking data sets, and on cooperation with academic researchers, businesses, industrial organizations, and for-profit research firms. For these reasons, the workshop was designed to elicit suggestions for incremental improvements as well as steps that would significantly advance understanding and to explore opportunities for public-private partnerships.