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Issues in Assessing the Contribution of Research and Development to Productivity Growth
Abstract
This article outlines the production function approach to the estimation of the returns to R&D and then proceeds to discuss in turn two very difficult problems: the measurement of output in R&D intensive industries and the definition and measurement of the stock R&D "capital." The latter concept leads to a discussion of modeling of the spillover effects of R&D and to suggestions for possible measurement of such effects via the concept of technological distance between firms and industries. Somewhat more familiar econometric problems (multicollinearity and simultaneity) are taken up in the next section and another section is devoted to estimation and inference problems arising more specifically in the R&D context. Several recent studies of returns to R&D are then surveyed, and the paper concludes with a plea for a lowering of expectations as to what the available data can tell us and with suggestions for ways of expanding the current data base in this field.
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Cited by
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Fankhauser, S., Bowen, A., Calel, R., Dechezleprêtre, A., Grover, D., Rydge, J., & Sato, M. (2013) · Global Environmental Change · doi:10.1016/j.gloenvcha.2013.05.007 · Cited by 204
The rise of the entrepreneurial economy and the future of dynamic capitalism
Thurik, A. R., Stam, E., & Audretsch, D. B. (2013) · Technovation · doi:10.1016/j.technovation.2013.07.003 · Cited by 182
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Metadata
- Authors
- Griliches, Z.
- Venue
- The Bell Journal of Economics
- Publisher
- JSTOR
- Published
- 1979
- Volume
- 10
- Issue
- 1
- Pages
- 92
- ISSN
- 0361-915X (ISSN-L)
- OpenAlex
- W1572691573
- Cited by
- 4,215
- References
- 0
- FWCI
- 34.91
- Type
- journal article
- Language
- en
- Open access
- closed
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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.