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A novel technology-industry concordance table based on linked inventor-establishment data

Author

Listed:
  • Dorner, Matthias

    (Institute for Employment Research (IAB), Nuremberg, Germany ; Institute for Employment Research, Nuremberg ; Max Planck Institute for Innovation and Competition, Munich)

  • Harhoff, Dietmar

    (Centre for Economic Policy Research (CEPR), London ; Institute for Employment Research, Nuremberg ; LMU, Munich)

Abstract

"Mapping technologies into industries is frequently required in empirical innovation studies, but many concordances only provide coarse mappings. We develop novel concordance tables between industries and technologies making use of linked inventor-employee patent data for Germany. The data comprise 235,933 patents filed between 1999 and 2011 at the European Patent Office. Data on inventors are matched and disambiguated with social security records available at the Institute for Employment Research. Employment data recorded in this database include detailed industry codes describing the industrial activities of the inventors' establishments. The linked inventor-establishment microdata allow us to identify the precise industry of origin of inventions, combine them with technology classifications from the inventors' patents and to generate novel concordance tables. We evaluate our approach by comparing the concordance tables with existing work, and we discuss the validity of patent statistics by industries as indicators for innovation." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Dorner, Matthias & Harhoff, Dietmar, 2017. "A novel technology-industry concordance table based on linked inventor-establishment data," FDZ-Methodenreport 201707 (en), Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    • Handle: RePEc:iab:iabfme:201707(en)
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    Cited by:

    1. is not listed on IDEAS
    2. Xiaoli Wang & Yun Liu & Lingdi Chen & Yifan Zhang, 2022. "Correlation Monitoring Method and model of Science-Technology-Industry in the AI Field: A Case of the Neural Network," SAGE Open, , vol. 12(4), pages 21582440221, December.
    3. Hötte, Kerstin, 2023. "Demand-pull, technology-push, and the direction of technological change," Research Policy, Elsevier, vol. 52(5).
    4. Jasmin Joecks & Kerstin Pull & Katrin Scharfenkamp, 2023. "Women directors and firm innovation: The role of women directors' representative function," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 1203-1214, March.
    5. Alexander M. Danzer & Carsten Feuerbaum & Fabian Gaessler, 2020. "Labor Supply and Automation Innovation," Working Papers 198, Bavarian Graduate Program in Economics (BGPE).
    6. Adelheid Holl & Bettina Peters & Christian Rammer, 2023. "Local knowledge spillovers and innovation persistence of firms," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(6), pages 826-850, August.
    7. Bernhard Dachs & Robert Stehrer & Anna Wolfmayr, 2025. "Global value chains, technology sovereignty and the role of China in international knowledge diffusion," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 52(3), pages 753-773, September.
    8. Benoit, Florence & Belderbos, René, 2024. "International connection, local disconnection: The (heterogeneous) role of global cities in local and global innovation networks," Journal of International Management, Elsevier, vol. 30(3).
    9. repec:iab:iabfda:201803(en is not listed on IDEAS
    10. Gugler, Klaus & Szücs, Florian & Wiedenhofer, Thomas, 2024. "Environmental Policies and directed technological change," Journal of Environmental Economics and Management, Elsevier, vol. 124(C).
    11. Rahko, Jaana, 2025. "Vertical spillovers and the energy intensity of European industries," Energy Economics, Elsevier, vol. 141(C).
    12. Dorner, Matthias & Harhoff, Dietmar & Gaessler, Fabian & Hoisl, Karin & Poege, Felix, 2019. "Linked Inventor Biography Data 1980-2014 : (INV-BIO ADIAB 8014)," FDZ Datenreport. Documentation on Labour Market Data 201803_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    13. Anastasios Evgenidis & Apostolos Fasianos, 2025. "AI news shocks and the macroeconomy: evidence from UK patent data," IFS Working Papers W25/48, Institute for Fiscal Studies.

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    JEL classification:

    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - General
    • 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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