The Race for World Leadership of Science and Technology: Status and Forecasts

1. The Race for World Leadership of Science and Technology: Status and Forecasts R. D. Shelton and P. Foland WTEC Baltimore, Maryland, USA Word version in Proceedings of the 12th International Conference On Scientometrics and Informetrics, pp. 369-380. Rio de Janeiro, July 14-17, 2009. Both posted at itri2.org/Rpaper/

2. Outline • Purposes • Input Indicators (Table 1 in paper) • Output Indicators (Table 2) • Current National Positions with Extrapolation Forecasts • Focus on Forecasting Scientific Paper Shares • Conclusions

3. Purposes • Provide a set of indicators to evaluate current national leadership of S&T (2005 data mostly). • Provide forecasts based on recent trends to predict which country will lead in the near future. • Provide detailed forecasts of numbers of scientific publications in SCI, with confirmation from other databases.

4. Model of a National Scientific Enterprise “The Black Box” S&T Outputs Resources In Indicators measure inputs and outputs Multiple linear regression can identify which inputs are most important

5. S&T Input Indicators (2005) Number of researchers and GERD are key INPUTS, but can drive outputs, like publications. GERD is much more significant than researchers. Average annual percentage rates of change in parentheses. Red emphasizes very rapid growth. Data from OECD (2008/1).

6. Population (thousands)

7. ResearchersOECD This pattern will be seen in several indicators: the US and EU curves are close together, with China below, but gaining quickly.

8. GDP, Constant Year 2000 $, PPP This format de-emphasizes China’s rapid gain compared to the other two. Its GDP has trebled over this interval.

9. GERD, Constant Year 2000$, PPP (R&D Investments)

10. GERD SHARE of OECD Group “World” share of R&D investment China’s gain comes at the expense of the other two. This is a key driver for scientific publication share, since both are zero-sum.

11. GERD Real Increases Over the Previous Year China’s spectacular increases in R&D investments make its rapid gains in output indicators more understandable.

12. GERD Share WithForecasts Based on 5-year Average This is based on a linear extrapolation of GERD, then shares of all OECD countries are constrained to add to 100%.

13. S&T Output Indicators (2005) Average annual percentage rates of change in parentheses. Red emphasizes rapid growth.

14. SCI Publications (Fractional Count) From NSF S&EI 2008. NSF thinks U.S. plateau has ended; I disagree.

15. S&E Doctoral Degrees EU = Germany and UK only; EU27 curve would be far above the US one.

16. Increase of S&E Doctoral Degrees Over the Previous Year

17. Triadic Patent Share

18. PRC Triadic Patent Share Growing fast from a very small base.

19. Hi-Tech Exports (Market Share)EC (2007) EU-27 doesn’t include BG and RO

21. Summary of National Positions • Who’s ahead depends on indicators chosen • In 2005 data the leader was: • US: GERD, researchers, impacts, patents, hi-tech exports • EU: papers in SCI, S&E PhDs, Nobels • PRC: trade balance • But linear forecasts show the PRC will gain: • Lead hi-tech exports and researchers by 2010 • Pass EU in GERD by 2015 (US will still lead) • Pass US in S&E PhDs by 2015 (EU will still lead) • Lead in papers in SCI by 2017 (more later) 2005 snapshot shows US leading, as the gurus have stated, BUT…

22. Focus on Scientific Papers • While growing fast in the Science Citation Index (SCI), China is far behind, however the Shelton Model forecasts that it will soon pass the US and EU to lead the world • Some confirmation comes from other databases, where China is already a contender: • Inspec • Scopus • Compendix

23. More Detailed Model of Publication System (Inside the Black Box) $ Inputs Papers Published p1 g1 US EU Journal Editors AT ROW G (total) P (total) mi = pi/P Paper share wi = gi/G GERD share National Research Systems -- Fairly Independent Highly Interdependent Paper Selection

24. A Simple Model for Country i mi = k iwi • mi is share of papers published (fractional basis) • wi is the share of GERD for the OECD Group • k i is a "constant" of proportionality; it differs by country. • k i is also the efficiency of country i in producing papers per $1 million in GERD, normalized by the OECD average efficiency. • For data in a single year the equation is an identity, but it is most useful over a range of years when k i is approximately constant

25. Since 1998, ki Has Been Fairly Constant for THESE Countries Ki Relative Efficiency 1.6 1.4 1.2 1.0 US EU27 0.8 PRC 0.6 0.4 0.2 0.0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 EU is 40% more efficient than average. US and PRC are not so different, at about 20% below average.

26. Paper Share in Science Citation IndexForecast Based on Shelton Model The PRC is likely to soon lead the world in scientific publications. This is based on R&D investments ( the GERD share driver), not an linear forecast of publications.

27. Scientific PublicationsINSPEC China is already taking the lead in this physical science database.

28. Scientific PublicationsSCOPUS China has already passed the EU in this database.

29. Scientific PublicationsCOMPENDEX China is already taking the lead in this physical science database.

30. Conclusions • 2005 indicators show the US and EU about even, with China well below • However, China is growing rapidly • Linear forecasts predict that China will soon pass the US and EU in key indicators • Perhaps most significant to scientometricians is the forecast that they will soon lead the world in the SCI • I predict that, if present trends continue, the PRC will lead the world in S&T by 2017.

31. Appendix: Extra Slides More info at http://itri2.org/Rpaper/

32. Demonstration that the end of U.S. plateau in publications is an artifact of the increases in the total SCI database

33. Linear Extrapolation Details Some indicators are zero sum--GERD share, for example. Results need to be constrained to add to 100%.