Analysing innovative output in a CIS database: taking account of some nasty details
AbstractRecent 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.
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Bibliographic InfoArticle provided by FrancoAngeli Editore in its journal ECONOMIA E POLITICA INDUSTRIALE.
Volume (Year): 2010/1 (2010)
Issue (Month): 1 ()
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Web page: http://www.francoangeli.it/riviste/sommario.asp?IDRivista=13
Find related papers by JEL classification:
- O31 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
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- 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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- Daria Ciriaci, 2011. "Intangible resources: the relevance of training for European firms’ innovative performance," JRC-IPTS Working Papers on Corporate R&D and Innovation 2011-06, Institute of Prospective Technological Studies, Joint Research Centre.
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