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Innovation and Productivity Across Four European Countries
Open accessAbstract
This paper compares the role innovation plays in productivity across four European countries, France, Germany, Spain, and the UK, using firm-level data from the internationally harmonized Community Innovation Surveys (CIS3). Despite a considerable number of national firm-level studies analysing this relationship, cross-country comparisons using micro data are still rare. We apply a structural model that describes the link between R&D expenditure, innovation output, and productivity (CDM model). Our econometric results suggest that overall the systems driving innovation and productivity are remarkably similar across these four countries, although we also find interesting differences, particularly in the variation in productivity that is associated with more or less innovative activities.
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Citations
Cited by
Gaglio, C., Kraemer-Mbula, E., & Lorenz, E. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121785 · Cited by 452
Amrago, E. C., Loughrey, J., Ryan, G., Crowley, F., & Doran, J. (2026) · Environmental and Sustainability Indicators · doi:10.1016/j.indic.2025.101064 · Cited by 1
Metadata
- Authors
- Griffith, R., Huergo, E., Mairesse, J., & Peters, B.
- Venue
- Oxford Review of Economic Policy
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-12-01
- Volume
- 22
- Issue
- 4
- Pages
- 483-498
- ISSN
- 0266-903X (ISSN-L)
- 1460-2121
- OpenAlex
- W1989169177
- Cited by
- 886
- References
- 0
- FWCI
- 56.54
- Type
- journal article
- Language
- en
- Open access
- gold
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- Griffith, R., Huergo, E., Mairesse, J., & Peters, B. (2006). Innovation and Productivity Across Four European Countries. Oxford Review of Economic Policy. https://doi.org/10.1093/oxrep/grj028
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
