Capturing Change in Science, Technology, and Innovation Improving Indicators to Inform Policy (2014) / Chapter Skim
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3 Data Resources for Indicators
3 Data Resources for Indicators
Pages 29-40
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From page 29... ...
NCSES's surveys yield scores of data for variables Support to Universities, Colleges, and Nonprofit that are not released to the public for privacy and confiden Institutions; tiality reasons or because resources are inadequate to create • NSF Survey of Research and Development Expendidata series from all relevant survey questions. In other words, tures at Universities and Colleges/Higher Education NCSES has already collected or has access to some of the Research and Development Survey; information desired by users of STI indicators.
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From page 30... ...
is a database containing industrial R&D data 2 years prior.7 Given the importance of these surveys to published by NSF from 1953 through 2007. It comprises NCSES's indicators on innovation activities in the United more than 2,500 statistical tables, which are constructed from States and abroad, these declining response rates represent the Survey of Industrial Research and Development (SIRD)
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From page 31... ...
By contrast, there is relatively sparse coverage of resources surveys, the number of tables or data series pub- direct measures of innovation, public-sector R&D, and R&D lished by the agency appears to be more balanced. Figure conducted by nonprofit organizations -- areas of keen interest 3-2 shows the concentration of NCSES tables, with points for users of indicators and therefore areas in which NCSES closer to the center of the diagram indicating greater con- could improve its portfolio.
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From page 32... ...
NOTES: BRDIS = Business Research and Development and Innovation Survey; FFRDC = Federally Funded Research and Development Center; HERD = Higher Education Research and Development Survey; NCSES = National Center for Science and Engineering Statistics; NSCG = National Survey of College Graduates; NSRCG = National Survey of Recent3-1.eps Graduates; R&D = research and development; R02562 Fig College SDR = Survey of Doctorate Recipients; SED = Survey of Earned Doctorates. vector SOURCE: NCSES data.
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From page 33... ...
NOTES: BERD = business enterprise expenditure on R&D; BOP = balance of payments; GBAORD = government budget appropriations R02562 Fig 3-3.eps raster or outlays for research and development; GERD = gross domestic expenditure on research and development; GOVERD = government intramural expenditure on R&D; HERD = higher education expenditure on research and development; OECD = Organisation for Economic Co-operation and Development; R&D = research and development; SEH = science, engineering, and health; UNESCO = United Nations Educational, Scientific and Cultural Organization. SOURCES: Adapted from UNESCO, see http://www.uis.unesco.org/ScienceTechnology/Pages/default.aspx [November 2012]
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From page 34... ...
Certain users may want ables doctoral degrees in natural science, global high-value to understand levels of R&D expenditure to compare nations, patents, trade balance in knowledge-intensive services, and while others may want the same variable for subnational engineering journal articles as a share of total S&E journal comparisons (say, hot spots for innovation activities in dif- articles are not correlated at all with one another; and (4) the ferent areas of the United States)
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From page 35... ...
engi- edge and human capital outputs, although these measures are universally proxies that are related to the underlying neering journal articles as a share of total S&E journal concepts with substantial measurement error (e.g., degrees articles, trade balance in knowledge-intensive services and as a measure for the human capital of graduates; papers as a intangible assets, and global high-value patents and (2) share measure of new scientific knowledge; patents as a measure of region's/country's citations in international literature and
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From page 36... ...
. See Appendix F for details of heat map generation.
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From page 37... ...
R02562 Fig 3-6.eps mixed – raster & vector human capital. NCSES should focus first on cultivating mea- • knowledge stocks and flows in specific sectors, sures in areas in which the data already exist in its BRDIS including nanotechnology, information technology, and SESTAT databases and in which it has productive col- biotechnology and agriculture research, oil and gas laborations with other statistical agencies in the United States production, clean/green energy, space applications, and abroad.
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From page 38... ...
Innovation Policy Program, which also resides in NSF's Social, Behavioral, and Economic Sciences Directorate. Over time, NCSES should build capacity in house and Important as well is for NCSES to develop a roadmap or through its Grants and Fellowships Program to develop strategic plan for adding new indicators or case studies, measures that are of high priority for users but require because doing so will likely require curtailing the frequency deeper knowledge of how to obtain statistically valid data of some of its current measures.
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From page 39... ...
However, satisfying user demands and anticipating Program to develop measures that are high priorfuture demands on its databases and analytical products will ity for users but that require deeper knowledge require developing a strategic plan, whose execution will in to obtain statistically valid data or to use frontier turn require careful husbanding of existing resources and methods appropriately. NCSES should also develop possibly new financial and human capital resources as well.
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From page 40... ...
STI worldwide will require statistics derived from empirical Second, in contrast to human capital indicators, inter- research; experimental exercises that allow counterfactual national organizations such as OECD, Eurostat, UNESCO, analysis to reveal impacts of expenditures on R&D and and Statistics Canada have comparatively more developed innovation; and case studies that convey narratives regarding innovation indicators than NCSES. Improving international collaborative activities, networks, and other characteristics comparability could be a mutually beneficial collaborative of tacit knowledge that are key drivers of the international effort among these organizations.
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