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Analysing innovative output in a CIS database: taking account of some nasty details

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  • Mikko Paananen
  • Alfred Kleinknecht

Abstract

Recent analyses of Community Innovation Survey (CIS) data suffer from methodological shortcomings. Using Finnish CIS data, we illustrate the potential consequences of these shortcomings and propose ways of dealing with them. We show how the neglect of lag structures between dependent and independent variables has certain consequences on the results. It is also important to check and identify any differences in the typical lifecycle durations between industries. Finally, the precise definition of ?innovators? to be included in the estimate also has a significant impact on the results, as does the non-normal distribution of shares in the sales of innovative products. Earlier studies have not been too explicit on some of these problems.

Suggested Citation

  • Mikko Paananen & Alfred Kleinknecht, 2010. "Analysing innovative output in a CIS database: taking account of some nasty details," ECONOMIA E POLITICA INDUSTRIALE, FrancoAngeli Editore, vol. 2010(1), pages 13-31.
    • Handle: RePEc:fan:polipo:v:html10.3280/poli2010-001002
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    Citations

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    Cited by:

    1. Daria Ciriaci, 2011. "Intangible resources: the relevance of training for European firms innovative performance," JRC Working Papers on Corporate R&D and Innovation 2011-06, Joint Research Centre.
    2. Daria Ciriaci, 2017. "Intangible resources: the relevance of training for European firms’ innovative performance," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(1), pages 31-54, April.

    More about this item

    Keywords

    Determinanti dell?innovazione; output innovativo; collaborazione R&S; community innovation survey (CIS);
    All these keywords.

    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
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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