TABLE F-4 Selected Science and Technology Variables from OECD, UNESCO, and Eurostat Database Used in the Panel’s Analysis

Variable Label Variable
EURO_GERD Gross domestic expenditure on R&D (millions of current PPP dollars)
EURO_HRST Human resources in science and technology
EURO_HTEC_EMPL Employment in high-tech sectors
EURO_HTEC_TRD_EU Trade with EU partners in high-tech sectors
EURO_HTEC_TRD_NONEU Trade with non-EU partners in high-tech sectors
EURO_KIS_EMPL Employment in high-tech knowledge-intensive services
EURO_OSS_FTE Other supporting staff—full-time equivalent
EURO_OSS_HC Other supporting staff—head count
EURO_RD_HR_FTE R&D personnel—full-time equivalent
EURO_RD_HR_HC R&D personnel—head count
EURO_RES_FTE Researchers—full-time equivalent
EURO_RES_HC Researchers—head count
EURO_SE Scientists and engineers
EURO_TECH_FTE Technicians—full-time equivalent
EURO_TECH_HC Technicians—head count
OECD_AERO_BALANCE Trade balance: aerospace industry (millions of current dollars)

 

(1)   successfully completed education at the third level in an S&T field of study; and

(2)   were not formally qualified as above, but are employed in S&T occupations in which the above qualifications are normally required.18

Eurostat refers to scientists and engineers as persons who use or create scientific knowledge and engineering and technological principles, i.e., persons with scientific or technological training who are engaged in professional work on S&T activities and high-level administrators and personnel who direct the execution of S&T activities. UNESCO publishes information on researchers, technical professionals, and other supporting staff. OECD, Eurostat, and UNESCO produce human capital statistics by head count and FTEs.

Table F-7 shows various human capital variables for the United States that are published by NCSES and other international organizations. Figures F-12 and F-13 show results of the cluster analysis performed on the data in Table F-7. Doctoral scientists and engineers is the only NCSES variable that is closely related to the variables reported by Eurostat and OECD.

Single Nation Analysis: Innovation Statistics—Levels versus Percentages

Table F-8 provides a comparative view of innovation data by industry classification that are available from the three surveys on innovation—the CIS, BRDIS, and Canada’s Survey of Innovation. SIBS 2009 has more recent data on the status of innovation activity in Canada, but the data are not available by industry classification; hence the 2003 Survey of Innovation data are presented here. NCSES data cover the period 2006-2008, because companies were asked to report on innovation activity for those years. The EU innovation data are taken from CIS 2006 and 2008. In Tables 1 and 2 of InfoBrief NSF 11-300, data on firms producing innovative products and processes are presented as percentages—for example, the percentage of innovative firms reporting that they produced a new/significantly improved product. This is also the case with innovation data produced by Statistics Canada, while data from the CIS are available in both level and percentage form. Staff of the Committee on National

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18See http://epp.eurostat.ec.europa.eu/cache/ITY_SDDS/Annexes/hrst_st_esms_an1.pdf, page 1 [December 2012].



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