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International patent families: from application strategies to statistical indicators

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  • Antoine Dechezleprêtre

    (CERNA i3 - Centre d'économie industrielle i3 - MINES ParisTech - École nationale supérieure des mines de Paris - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique)

  • Yann Ménière

    () (CERNA i3 - Centre d'économie industrielle i3 - MINES ParisTech - École nationale supérieure des mines de Paris - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique)

  • Myra Mohnen

Abstract

This paper provides an in-depth analysis of the characteristics of international patent families, including their domestic component. The authors exploit a relatively under-studied feature of patent families, namely the number of patents covering the same invention within a given jurisdiction. Using this information, they highlight common patterns in the structure of international patent families, which reflect both the patenting strategies of innovators and the peculiarities of the different patent systems. While the literature has extensively used family size – i.e. the number of countries in which a given invention is protected – as a measure of patent value, the authors’ results suggest that the number of patent filings in the priority country within a patent family, as well as the time span between the first and last filings within a family, are other insightful indicators of the value of patented innovations.
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Suggested Citation

  • Antoine Dechezleprêtre & Yann Ménière & Myra Mohnen, 2017. "International patent families: from application strategies to statistical indicators," Post-Print hal-01693881, HAL.
  • Handle: RePEc:hal:journl:hal-01693881
    DOI: 10.1007/s11192-017-2311-4
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-01693881
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    4. Viju Raghupathi & Wullianallur Raghupathi, 2019. "Exploring science-and-technology-led innovation: a cross-country study," Journal of Innovation and Entrepreneurship, Springer, vol. 8(1), pages 1-45, December.
    5. Stuart J. H. Graham & Alan C. Marco & Amanda F. Myers, 2018. "Patent transactions in the marketplace: Lessons from the USPTO Patent Assignment Dataset," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 27(3), pages 343-371, September.
    6. Dechezlepretre, Antoine & Hemous, David & Olsen, Morten & Zanella, Carlo, 2020. "Automating labor: evidence from firm-level patent data," LSE Research Online Documents on Economics 108420, London School of Economics and Political Science, LSE Library.
    7. Dechezleprêtre, Antoine & Hémous, David & olsen, morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    8. Francesco Pasimeni & Alessandro Fiorini & Aliki Georgakaki, 2018. "Patent-based Estimation Procedure of Private R&D: The Case of Climate Change and Mitigation Technologies in Europe," SPRU Working Paper Series 2018-06, SPRU - Science Policy Research Unit, University of Sussex Business School.

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    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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