The DOI matches its Crossref record.
How High Are the Giants' Shoulders: An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth
Open accessAbstract
The pace of industrial innovation and growth is shaped by many forces that interact in complicated ways. Profit-maximizing firms pursue new ideas to obtain market power, but the pursuit of the same goal by others means that even successful inventions are eventually superseded by others; this is known as creative destruction. New ideas not only yield new goods but also enrich the stock of knowledge of society and its potential to produce new ideas. To a great extent, this knowledge is nonexcludable, making research and inventions the source of powerful spillovers. The extent of spillovers depends on the rate at which new ideas outdate old ones, i.e., on the endogenous technological obsolescence of ideas, and on the rate at which knowledge diffuses among inventors. In this paper we build a simple model that allows us to organize our search for the empirical strength of the concepts emphasized in the preceding. We then use data on patents and patent citations as empirical counterparts of new ideas and knowledge spillovers, respectively, to estimate the model parameters. We find estimates of the average annual rate of creative destruction in the range of 2-7% for the decade of the 1970s, with rates for individual sectors as high as 25%. For technological obsolescence, we find an increase over the century from about 3% per year to about 12% per year in 1990, with a noticeable plateau in the 1970s. We find the rate of diffusion of knowledge to be quite rapid, with the mean lag between one and two years. Last, we find that the potency of spillovers from old ideas to new knowledge generation (as evidenced by patent citation rates) has been declining over the century; the resulting decline in the effective public stock of knowledge available to new inventors is quite consistent with the observed decline in the average private productivity of research inputs.
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
R & D-Based Models of Economic Growth
Jones, C. I. (1995) · Journal of Political Economy · doi:10.1086/262002 · Cited by 3,059
Competition and Innovation: An Inverted U Relationship
Aghion, P., Bloom, N., Blundell, R. W., Griffith, R., & Howitt, P. (2004) · SSRN Electronic Journal · doi:10.2139/ssrn.1306944 · Cited by 2,117
Competition and innovation: an inverted U relationship
Blundell, R., Howitt, P., Griffith, R., Aghion, P., & Bloom, N. (2002) · Working Paper Series · doi:10.1920/wp.ifs.2002.0204 · Cited by 2,109
Solow, R. M. (1994) · Journal of Economic Perspectives · doi:10.1257/jep.8.1.45 · Cited by 803
Labor- and Capital-Augmenting Technical Change
Acemoglu, D. (2003) · Journal of the European Economic Association · doi:10.1162/154247603322256756 · Cited by 747
Metadata
- Authors
- Caballero, R. J., & Jaffe, A. B.
- Venue
- NBER Macroeconomics Annual
- Publisher
- JSTOR
- Published
- 1993
- Volume
- 8
- Pages
- 15
- ISSN
- 0889-3365 (ISSN-L)
- OpenAlex
- W3125010103
- Cited by
- 419
- References
- 0
- FWCI
- 17.12
- Type
- journal article
- Language
- en
- Open access
- bronze
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: How High Are the Giants' Shoulders: An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth. https://app.cochat.ai/papers/10.2307/3585017
- The paper
- Caballero, R. J., & Jaffe, A. B. (1993). How High Are the Giants' Shoulders: An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth. NBER Macroeconomics Annual. https://doi.org/10.2307/3585017
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.