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The size of patent categories: USPTO 1976-2006

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  • Lafond, F.

    (UNU-MERIT)

Abstract

Categorization is an important phenomenon in science and society, and classification systems reflect the mesoscale organization of knowledge. The Yule-Simon-Naranan model, which assumes exponential growth of the number of categories and exponential growth of individual categories predicts a power law Pareto size distribution, and a power law size-rank relation Zipfs law. However, the size distribution of patent subclasses departs from a pure power law, and is shown to be closer to a shifted power law. At a higher aggregation level patent classes, the rank-size relation deviates even more from a pure power law, and is shown to be closer to a generalized beta curve. These patterns can be explained by assuming a shifted exponential growth of individual categories to obtain a shifted power law size distribution for subclasses, and by assuming an asymmetric logistic growth of the number of categories to obtain a generalized beta size-rank relationship for classes. This may suggest a shift towards incremental more than radical innovation.

Suggested Citation

  • Lafond, F., 2014. "The size of patent categories: USPTO 1976-2006," MERIT Working Papers 2014-060, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    • Handle: RePEc:unm:unumer:2014060
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    File URL: https://unu-merit.nl/publications/wppdf/2014/wp2014-060.pdf
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    References listed on IDEAS

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    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    2. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
    3. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    4. Birgitte Andersen, 1999. "The hunt for S-shaped growth paths in technological innovation: a patent study," Journal of Evolutionary Economics, Springer, vol. 9(4), pages 487-526.
    5. Robert J. Gordon, 2012. "Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds," NBER Working Papers 18315, National Bureau of Economic Research, Inc.
    6. Pasinetti,Luigi L., 1983. "Structural Change and Economic Growth," Cambridge Books, Cambridge University Press, number 9780521274104, October.
    7. Pier P. Saviotti, 1996. "Technological Evolution, Variety and the Economy," Books, Edward Elgar Publishing, number 727.
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    Cited by:

    1. François Lafond & Daniel Kim, 2019. "Long-run dynamics of the U.S. patent classification system," Journal of Evolutionary Economics, Springer, vol. 29(2), pages 631-664, April.

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    More about this item

    Keywords

    Innovation; R&D; Learning; Knowledge; Classification; Categorization; Pareto distribution; Power law;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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