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Labor Mobility and Patenting Activity


  • Ulrich Kaiser

    (University of Zurich)

  • Hans Christian Kongsted

    (Department of Economics, University of Copenhagen)

  • Thomas Rønde

    (Department of Economics, University of Copenhagen)


We measure the quantitative importance of labor mobility as a vehicle for the transmission of knowledge and skills across firms. For this purpose we create a unique data set that matches all applications of Danish firms at the European Patent Office to linked employer-employee register data for the years 1999-2002. The Danish workforce is split into "R&D workers", who hold a bachelor's or a master's degree in a technical field, and "non{R&D workers". We find that mobile R&D workers ("R&D joiners"') contribute more to patenting activity than immobile R&D workers. Furthermore, R&D workers who have previously been employed by a patenting firm ("patent exposed workers") have a larger effect on patenting activity than R&D workers without this experience. Patent exposed R&D joiners constitute the most productive group of workers: for firms that patented prior to 1999, one additional worker of this type relates to an increase in the number of patent applications of the new employer by 0.0646. This corresponds to a 14 percent increase in the mean number of yearly patent applications. We also find that mobility of R&D workers increases the joint patenting activity of the donor and recipient firms, confirming the importance of labor mobility for innovation in the economy.

Suggested Citation

  • Ulrich Kaiser & Hans Christian Kongsted & Thomas Rønde, 2008. "Labor Mobility and Patenting Activity," CAM Working Papers 2008-07, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  • Handle: RePEc:kud:kuieca:2008_07

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    References listed on IDEAS

    1. Bruce Fallick & Charles A. Fleischman & James B. Rebitzer, 2006. "Job-Hopping in Silicon Valley: Some Evidence Concerning the Microfoundations of a High-Technology Cluster," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 472-481, August.
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    Cited by:

    1. Wolf, Katja & Stockinger, Bastian, 2016. "The productivity effects of worker mobility between heterogenous firms," Annual Conference 2016 (Augsburg): Demographic Change 145750, Verein für Socialpolitik / German Economic Association.
    2. Ann-Kathrine Ejsing & Ulrich Kaiser & Hans Christian Kongsted & Keld Laursen, 2013. " The Role of University Scientist Mobility for Industrial Innovation," Working Papers 332, University of Zurich, Department of Business Administration (IBW).
    3. Andrey Stoyanov & Nikolay Zubanov, 2012. "Productivity Spillovers across Firms through Worker Mobility," American Economic Journal: Applied Economics, American Economic Association, vol. 4(2), pages 168-198, April.
    4. Toivanen, Otto & Väänänen, Lotta, 2010. "Returns to Inventors," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 309, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    5. Eriksson, Tor & Qin, Zhihua & Wang, Wenjing, 2014. "Firm-level innovation activity, employee turnover and HRM practices — Evidence from Chinese firms," China Economic Review, Elsevier, vol. 30(C), pages 583-597.
    6. Andreas Reinstaller & Isabel Stadler & Fabian Unterlass, 2012. "Mobility of University Research Staff in the EU and Austria," WIFO Monatsberichte (monthly reports), WIFO, vol. 85(2), pages 105-119, February.
    7. repec:spr:anresc:v:58:y:2017:i:3:d:10.1007_s00168-017-0807-8 is not listed on IDEAS

    More about this item


    labor mobility; dynamic count data; patents;

    JEL classification:

    • 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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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