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A Penny for Your Quotes: Patent Citations and the Value of Innovations
Abstract
The use of patents in economic research has been seriously hindered by the fact that patents vary enormously in their importance or value, and hence, simple patent counts cannot be informative about innovative output. The purpose of this article is to put forward patent counts weighted by citations as indicators of the value of innovations, thereby overcoming the limitations of simple counts. The empirical analysis of a particular innovation (Computed Tomography scanners) indeed shows a close association between citation-based patent indices and independent measures of the social value of innovations in that field. Moreover, the weighting scheme appears to be nonlinear (increasing) in the number of citations, implying that the informational content of citations rises at the margin. As in previous studies, simple patent counts are found to be highly correlated with contemporaneous R&D; however, here the association is within a field over time rather than cross-sectional.
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Metadata
- Authors
- Trajtenberg, M.
- Venue
- The RAND Journal of Economics
- Publisher
- Wiley
- Published
- 1990
- Volume
- 21
- Issue
- 1
- Pages
- 172
- ISSN
- 0741-6261 (ISSN-L)
- OpenAlex
- W1976395435
- Cited by
- 2,956
- References
- 0
- FWCI
- 9.08
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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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.
