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Fits and misfits : technological matching and R&D networks

Author

Listed:
  • Robin Cowan

    (BETA - Bureau d'Économie Théorique et Appliquée - INRA - Institut National de la Recherche Agronomique - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, MERIT)

  • Nicolas Jonard

    (CREA - Center for Research in Economic Analysis - uni.lu - Université du Luxembourg = University of Luxembourg = Universität Luxemburg)

  • Bulat Sanditov

    (IMT-BS - DEFI - Département Droit, Économie et Finances - TEM - Télécom Ecole de Management - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - EESC-GEM - Grenoble Ecole de Management - UEVE - Université d'Évry-Val-d'Essonne - TEM - Télécom Ecole de Management, MERIT)

Abstract

Interest in social and economic networks of various types has grown dramatically in the last two decades. The manifold empirical studies emphasize that networks often share two properties. First, they are small worlds – sparse networks with both short distances between pairs of agents, and strong local clustering. Second, they have skewed link distributions, often with a fat right tail. These properties have been observed in a wide variety of networks. A challenge in the economic, mostly game theoretic literature on network formation has been to capture these properties in a sound model. What incentives do (a few) agents have to form shortcuts, and why should they cluster locally? Why do a few agents acquire many links whereas many others seem able to form only a few ?

Suggested Citation

  • Robin Cowan & Nicolas Jonard & Bulat Sanditov, 2013. "Fits and misfits : technological matching and R&D networks," Grenoble Ecole de Management (Post-Print) hal-01273321, HAL.
  • Handle: RePEc:hal:gemptp:hal-01273321
    DOI: 10.4324/9780203073414-26
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    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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