The DOI matches its Crossref record.
Fundamental Stocks of Knowledge and Productivity Growth
Abstract
This paper develops new indicators of accumulated academic science and tests their explanatory power on productivity data from manufacturing industries. Knowledge is found to be a major contributor to productivity growth. Furthermore, a lag in effect of roughly 20 years is found between the appearance of research in the academic community and its effect on productivity in the form of knowledge absorbed by an industry. Academic technology and academic science filtered through interindustry spillovers exhibit lags of roughly 10 and 30 years each. Thus implied search and gestation times far exceed developmental periods in studies of R & D. A clear implication is that basic research declines relative to development in the face of an exogenous rise in the real of interest.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Is public R&D a complement or substitute for private R&D? A review of the econometric evidence
David, P. A., Hall, B. H., & Toole, A. A. (2000) · Research Policy · doi:10.1016/s0048-7333(99)00087-6 · Cited by 1,634
Fifty Years of Empirical Studies of Innovative Activity and Performance
Cohen, W. M. (2010) · Handbook of the Economics of Innovation · doi:10.1016/s0169-7218(10)01004-x · Cited by 962
Thursby, J. G., Jensen, R., & Thursby, M. C. (2001) · The Journal of Technology Transfer · doi:10.1023/a:1007884111883 · Cited by 709
The impact of public R&D expenditure on business R&D*
Guellec, D., & Van Pottelsberghe De La Potterie, B. (2003) · Economics of Innovation and New Technology · doi:10.1080/10438590290004555 · Cited by 404
Public R&D Investments and Private-sector Patenting: Evidence from NIH Funding Rules
Azoulay, P., Graff Zivin, J. S., Li, D., & Sampat, B. N. (2019) · The Review of Economic Studies · doi:10.1093/restud/rdy034 · Cited by 349
Metadata
- Authors
- Adams, J. D.
- Venue
- Journal of Political Economy
- Publisher
- University of Chicago Press
- Published
- 1990-08
- Volume
- 98
- Issue
- 4
- Pages
- 673-702
- ISSN
- 0022-3808 (ISSN-L)
- 1537-534X
- OpenAlex
- W2020388947
- Cited by
- 704
- References
- 0
- FWCI
- 16.42
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Fundamental Stocks of Knowledge and Productivity Growth. https://app.cochat.ai/papers/10.1086/261702
- The paper
- Adams, J. D. (1990). Fundamental Stocks of Knowledge and Productivity Growth. Journal of Political Economy. https://doi.org/10.1086/261702
Data sources
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.