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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by FrancoAngeli Editore in its journal ECONOMIA E POLITICA INDUSTRIALE.
Volume (Year): 2010/1 (2010)
Issue (Month): 1 ()
Contact details of provider:
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
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; 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
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Angelo Ventriglia).
If references are entirely missing, you can add them using this form.