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How Well Do Patent Citations Measure Flows of Technology? Evidence from French Innovation Surveys

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  • DUGUET Emmanuel

    (EPEE - University of Evry)

  • MacGARVIE Megan

    (University of Boston)

Abstract

Patent citation data are used in a growing body of economics and business research on technological diffusion. Research in this area uses “backward” citations to measure technological knowledge acquired by the patenting entities studied. “Forward” citations (citations to the firm’s patents made by other patents) have been interpreted as a measure of the knowledge diffusing outward from the patenting entity. Until now, there exists little evidence on whether or not patent citations are a good measure of knowledge flows. Our paper assesses the legitimacy of using European patent citations as a measure of technology flows. It uses information from the Community Innovation Survey (CIS) collected by the French Service des Statistiques Industrielles (SESSI), which contain firms’ responses to questions about their innovative activity. We show that patent citations are indeed related to firms’ statements about their acquisition and dispersion of new technology, but that the strength and statistical significance of this relationship varies across geographical regions and across channels of knowledge diffusion.

Suggested Citation

  • DUGUET Emmanuel & MacGARVIE Megan, 2004. "How Well Do Patent Citations Measure Flows of Technology? Evidence from French Innovation Surveys," Development and Comp Systems 0411018, EconWPA.
  • Handle: RePEc:wpa:wuwpdc:0411018
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    References listed on IDEAS

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    4. Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, Oxford University Press, vol. 108(3), pages 577-598.
    5. Hall, B. & Jaffe, A. & Trajtenberg, M., 2001. "The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools," Papers 2001-29, Tel Aviv.
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    Keywords

    patent; citation; Community Innovation Survey; innovation; spillovers; count data;

    JEL classification:

    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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