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From the 19 th to the 21 st century: Indicators for the knowledge economy

From the 19 th to the 21 st century: Indicators for the knowledge economy. Anthony Arundel MERIT Disclaimer: The views expressed in this presentation do not necessarily represent those of the Commission or any other funding agency. Is this a good shoe for sitting?.

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From the 19 th to the 21 st century: Indicators for the knowledge economy

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  1. From the 19th to the 21st century: Indicators for the knowledge economy Anthony Arundel MERIT Disclaimer: The views expressed in this presentation do not necessarily represent those of the Commission or any other funding agency.

  2. Is this a good shoe for sitting?

  3. What is a knowledge economy?

  4. Features of a knowledge economy? • Knowledge as an additional input to labour and capital. • Codification increases the buying and selling of knowledge. • Diffusion of Information and Communication Technologies (ICT).

  5. What has not happened

  6. Average hours worked per week by employed men 47 France Germany 46 Italy United Kingdom 45 United States 44 43 Average hours worked 42 41 40 39 38 37 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Source: ILO, LABORSTA, 2005. Germany, UK= hours paid; France, Italy, US = hours actually worked.

  7. Life satisfaction and GDP in the UK Source: Nic Marks, Measuring what matters: Assessing people’s quality of life and well-being across Europe, NEF, London, 2005

  8. Income and happiness in the US Source: Richard Layard, Happiness: Has social science a clue?, Lionel Robbins Memorial Lectures, March 2003.

  9. Challenges for the future

  10. Manufacturing employment as a share of total employment 35.0 30.0 25.0 20.0 Percent of total employment 15.0 France Germany 10.0 Italy United Kingdom 5.0 United States 0.0 1976 1980 1985 1990 1995 2000 2004 Source: UIS, 2005: laborsta.ilo.org

  11. Off-shoring of service sector jobs • Off-shoring ‘susceptibility’ based on intensive ICT use, output can be delivered using ICT, high information or knowledge content, face-to-face contact not needed: • Canada 18.6% • United States 18.1% • EU-15 19.2% Source: van Welsum D and Vickery G. Potential off-shoring of ICT-intensive using occupations, OECD, Paris, December 2004.

  12. China and India GERD (Billion US PPP$) 80 70 US = 277 billion EU = 206 billion EU = 206 billion US = 277 billion 60 50 40 30 China 20 India 10 0 1996 1997 1998 1999 2000 2001 2002 Source: China = OECD MSTI data (2005); India = UNESCO Institute for Statistics, stats.uis.unesco.org

  13. East Asian S&E PhDs awarded in the US versus total PhDs awarded in China 6000 12000 5000 10000 4000 8000 East Asian US S&E PhDs Chinese PhDs 3000 6000 2000 4000 1000 2000 0 0 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 East Asian S&E PhDs in US Doctoral degrees awarded in China Source: Wyckoff & Schaaper, The changing dynamics of the global market for the highly-skilled, OECD, 2004, table 4 and figure 8.

  14. Times Higher Education Supplement, October 21, 2005

  15. Why we need better indicators

  16. Indicator distortions • Data on education levels: addresses qualifications but not necessarily skills. • Data on patents: promotes expensive IP instead of moving quickly to market. • Data on R&D: stresses more R&D spending instead of marketable innovations.

  17. Source: MERIT, Preliminary results

  18. European policy for the knowledge economy

  19. The 60 year development of R&D indicators Origins in development of formal research divisions in German chemical firms in the 1880s. • First R&D survey in 1917, with further experimentation up until the late 1930s. • First large-scale American survey in 1953. • First international survey in 1963. • OECD considers R&D data comparability acceptable in 1981.

  20. Sector-based estimates of BERD/GDP: EU 13 2.5 2.02 2 1.5 1.35 1.22 Percent BERD/GDP 1 0.5 0 2002 BERD intensity 2015 BERD estimate at 2015 BERD estimate at maximum current national growth rates observed growth rates

  21. Data Source: Eurostat Structural Business Statistics

  22. Is high R&D/GDP desirable?Example of Merck in the early 1990s:Ranking in top 20 pharma firms Market share 2nd US patents (1990-94) 1st Drugs in pipeline 2nd Products in top 50 sellers 1st R&D intensity 17th Source: Sharp & Patel, Europe’s pharmaceutical industry: An innovation profile, EIMS report, Luxembourg, 1996.

  23. “Any policymaker… who relies on R&D intensity and R&D budgets as a meaningful metric to assess global competitiveness virtually guarantees shoddy analysis and distorted decisions. Few things reveal less about a company’s ability to innovate cost-effectively than its R&D budget. … …What is not fine – what is deceptive and destructive – is perpetuating a myth that the economic health of a country …can be measured by how much it spends on R&D... Europe should pay far more attention to the innovation value it creates rather than the level of corporate R&D funding. Its economic future depends on it.” Source: For innovation Success, do not follow the money, FT November 7 2005.

  24. Percentage of Innovative and R&D Performing Firms by Size: CIS-1 Estimates for 8 Countries Combined 100 90 80 70 60 50 Innovators 40 R&D performers 30 20 10 0 < 20 20-99 100-249 250-499 500-999 1000-1999 > 2000 Number of Employees Countries: Germany, Italy, Belgium, Netherlands, Luxembourg, Ireland, Denmark, Norway Source: Arundel A. The Knowledge Economy, Innovation Diffusion, and the CIS. Proceedings of the 21st CEIES Seminar, Innovation Statistics – More than R&D Indicators, 2003 .

  25. “What is important is that a country participates in the newest technologies and innovations, not whether it innovates itself. To raise GDP through technology-related activities, a country needs to achieve value-added at some stage of the process, not necessarily the inventive stage”. Source: Porter et al, Global Competitiveness Report, World Economic Forum, 2000.

  26. New indicators for the knowledge economy: the CIS

  27. How firms innovate Source: Eurostat CIS-3 data

  28. Output Production Function Organisational Change ICT 1...M ZK Z1 … O TFP v  u unobservables K observables R&D CIS Innovation Knowledge Production Function Non-R&D Innovation Expenditure P v1 Knowledge Flows v0 Source: Chiara Criscuolo, OECD presentation November 28, 2005

  29. “ The CIS delivers data that prove that R&D and innovation are not the same, but the CIS has had little impact on specific policy instruments. It has had a major effect on developing innovation policy in general and influenced a major programme that explicitly focuses on innovation and not on R&D. This is a breakthrough and the most significant recognition to date of the value of the CIS”. Source: MERIT interviews, June 2005

  30. Conclusions

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