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Statistical patent analysis indicators as a means of determining country technological specialisation

Author

Listed:
  • Ekaterina Khramova

    (Research Fellow, Institute for Statistical Studies and Economics of Knowledge)

  • Dirk Meissner

    (Deputy Head, Laboratory for Science and Technology Studies, Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics)

  • Galina Sagieva

    (Senior Research Fellow, Institute for Statistical Studies and Economics of Knowledge; Department Head, Department for Research of Intellectual Property and Technology Transfer)

Abstract

Patent data provide a rich set of information which can be used for comparative studies and trend analysis. The paper presents a systematic overview of the most appropriate tools methodologies that are available for determining the technological specialization of countries. Such analysis includes a discussion of databases, approaches, and indexes appropriate for this kind of analysis. This paper discusses different indicators of technological specialisation, concentration, and patent quality are analysed, including Revealed Technological Advantage (RTA) index, patent share, C20 concentration index, and Gini concentration index. the main available patent databases, especially those with open access, and summarizes arguments for the study of technological specialisation based on assignee and inventor patent data. Also the limits and potentials of the statistics on resident / nonresident patenting on internal and external markets are discussed in the paper.

Suggested Citation

  • Ekaterina Khramova & Dirk Meissner & Galina Sagieva, 2013. "Statistical patent analysis indicators as a means of determining country technological specialisation," HSE Working papers WP BRP 09/STI/2013, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:wpbrp09sti2013
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    Citations

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    Cited by:

    1. Nan Yu, 2017. "Innovation of renewable energy generation technologies at a regional level in China: a study based on patent data analysis," International Economics and Economic Policy, Springer, vol. 14(3), pages 431-448, July.
    2. Nan Yu, 2016. ": Innovation of renewable energy generation technologies at a regional level in China:A study based on patent data analysis," EIIW Discussion paper disbei230, Universitätsbibliothek Wuppertal, University Library.
    3. Bruno Brandão Fischer & Maxim Kotsemir & Dirk Meissner & Ekaterina Streltsova, 2020. "Patents for evidence-based decision-making and smart specialisation," The Journal of Technology Transfer, Springer, vol. 45(6), pages 1748-1774, December.
    4. Rhoden, Imke, 2020. "Innovating in Krugman’s Footsteps – Where and How Innovation Differs in Europe: Static Innovation Indicators for Identifying Regional Policy Leverages," EconStor Preprints 218875, ZBW - Leibniz Information Centre for Economics.
    5. Maxim Kotsemir, 2013. "Measuring National Innovation Systems Efficiency - A Review of DEA Approach," Post-Print hal-00865875, HAL.
    6. Patrick Herron & Aashish Mehta & Cong Cao & Timothy Lenoir, 2016. "Research diversification and impact: the case of national nanoscience development," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 629-659, November.
    7. Elias G. Carayannis & Dirk Meissner & Anastasia Edelkina, 2017. "Targeted innovation policy and practice intelligence (TIP2E): concepts and implications for theory, policy and practice," The Journal of Technology Transfer, Springer, vol. 42(3), pages 460-484, June.
    8. Ekaterina Streltsova & Gleb Kuzmin, 2019. "Russian Technograds: The Technological Profiles of the Cities," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(3), pages 41-49.
    9. Yamashita, Andre S. & Fujii, Hidemichi, 2022. "Trend and priority change of climate change mitigation technology in the global mining sector," Resources Policy, Elsevier, vol. 78(C).

    More about this item

    Keywords

    Revealed Technological Advantage (RTA) index; patent share; C20 concentration index; Gini concentration index; country technological position;
    All these keywords.

    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
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries
    • L24 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Contracting Out; Joint Ventures

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