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Mobility of knowledge and local innovation activity

Author

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  • Drivas, Kyriakos
  • Economidou, Claire
  • Karkalakos, Sotiris
  • Tsionas, Efthymios G.

Abstract

This paper studies the diffusion of knowledge and its consequences for local innovation production. In a common framework, we analyze the geographic reach of different channels of knowledge flows that thus far have been studied separately in the literature. To jointly estimate these flows, we develop and apply novel econometric techniques appropriate to the nature of the data. We find that geographic along with technological proximity to be more essential to the operation of market than to non-market channels of knowledge flows. External accessible disembodied knowledge has a strong positive effect on local innovation production that is larger than that of embodied knowledge.

Suggested Citation

  • Drivas, Kyriakos & Economidou, Claire & Karkalakos, Sotiris & Tsionas, Efthymios G., 2016. "Mobility of knowledge and local innovation activity," European Economic Review, Elsevier, vol. 85(C), pages 39-61.
    • Handle: RePEc:eee:eecrev:v:85:y:2016:i:c:p:39-61
    DOI: 10.1016/j.euroecorev.2016.01.008
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    Cited by:

    1. Polemis, Michael & Tselekounis, Markos, 2019. "Does deregulation drive innovation intensity? Lessons learned from the OECD telecommunications sector," MPRA Paper 92770, University Library of Munich, Germany.
    2. Bechlioulis, Alexandros & Economidou, Claire & Karamanis, Dimitrios & Konstantios, Dimitrios, 2023. "How important are capital controls in shaping innovation activity?," Journal of International Money and Finance, Elsevier, vol. 131(C).
    3. Antonelli, Cristiano & Crespi, Francesco & Quatraro, Francesco, 2022. "Knowledge complexity and the mechanisms of knowledge generation and exploitation: The European evidence," Research Policy, Elsevier, vol. 51(8).
    4. Conti, C. & Mancusi, M.L. & Sanna-Randaccio, F. & Sestini, R. & Verdolini, E., 2018. "Transition towards a green economy in Europe: Innovation and knowledge integration in the renewable energy sector," Research Policy, Elsevier, vol. 47(10), pages 1996-2009.
    5. Kyriakos Drivas, 2021. "Which travels farther? Knowledge or rivalry?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(2), pages 299-333, October.
    6. Jaap W. B. Bos & Claire Economidou & Lu Zhang, 2020. "Specialization in the presence of trade and financial openness," Empirical Economics, Springer, vol. 58(6), pages 2783-2816, June.
    7. Xionghe Qin & Dong Zhang & Debin Du, 2025. "Understanding the Impact of Spatial Externalities on Two-Stage R&D Efficiency: Empirical Evidence from 285 Chinese Prefecture-Level Cities," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(2), pages 8308-8342, June.
    8. Tao Hu & Yin Zhang, 2021. "A spatial–temporal network analysis of patent transfers from U.S. universities to firms," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 27-54, January.
    9. Dominguez Lacasa, Iciar & Jindra, Björn & Radosevic, Slavo & Shubbak, Mahmood, 2019. "Paths of technology upgrading in the BRICS economies," Research Policy, Elsevier, vol. 48(1), pages 262-280.
    10. Kyriakos Drivas & Claire Economidou & Konstantinos N. Konstantakis & Panayotis G. Michaelides, 2022. "Technological Leaders, Laggards and Spillovers: A Network GVAR Analysis," Open Economies Review, Springer, vol. 33(2), pages 231-269, April.
    11. Drivas, Kyriakos & Economidou, Claire & Karamanis, Dimitrios & Sanders, Mark, 2020. "Mobility of highly skilled individuals and local innovation activity," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    12. Siwei Cao & Guangrong Ma & Hao Mao, 2024. "Is distance really dying? Transportation and knowledge spillovers," Journal of Regional Science, Wiley Blackwell, vol. 64(2), pages 355-405, March.

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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O51 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - U.S.; Canada

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