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Developing science, technology and innovation indicators: What we can learn from the past

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  • Freeman, Christopher
  • Soete, Luc

Abstract

The science-technology-innovation system is one that is continuously and rapidly evolving. The dramatic growth over the last 20 years in the use of science, technology and innovation (STI) indicators appears first and foremost to be the result of a combination of, on the one hand, the ease of computerized access to an increasing number of measures of STI and, on the other hand, the interest in a growing number of public policy and private business circles in such indicators. Such growing interest might be expected in societies that increasingly use organised science and technology to achieve a wide variety of social and economic objectives and in which business competition is increasingly based on innovation. On the basis of 40 years of indicators work, we argue that frontiers and characteristics of STI indicators that were important last century may no longer be so relevant today and indeed may even be positively misleading.

Suggested Citation

  • Freeman, Christopher & Soete, Luc, 2009. "Developing science, technology and innovation indicators: What we can learn from the past," Research Policy, Elsevier, vol. 38(4), pages 583-589, May.
  • Handle: RePEc:eee:respol:v:38:y:2009:i:4:p:583-589
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    More about this item

    Keywords

    Science; Technology and Innovation (STI) R&D Data Indicators Economic Measurement Statistics;

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    Statistics

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