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Us Patent Citations Data And Industrial Knowledge Spillovers

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  • Francesco Schettino

Abstract

The aim of this paper is to empirically evaluate the US interindustry knowledge spillover using the NBER patents data file (1963-1999). Reputing the patent backward citations as a good proxy of the patent's knowledge spillover, we proceed by building a time series to each US manufacturing industry patent citations and their lags. Then, we generate the time series of the external and the internal knowledge flow indices, showing that traditional sectors are more technology-dependent from the others than the new one. Here, in the spirit of Pavitt [Pavitt, Research Policy 13, 343-73, 1984]. We derive a new taxonomy of innovation focusing on the ideas instead of the goods production in order to obtain the innovation linkage and trajectories. Once we determined that each sector's most cited patents are typically belong to the 'new' sectors, we evaluate the high- and low-tech sectors innovation effect on the whole economy innovation process. Confirming that the high-tech sectors, and its R&D expenditures, are the most important, we conclude that it is the giant's shoulders, substance of the whole economy.

Suggested Citation

  • Francesco Schettino, 2007. "Us Patent Citations Data And Industrial Knowledge Spillovers," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 16(8), pages 595-633.
  • Handle: RePEc:taf:ecinnt:v:16:y:2007:i:8:p:595-633
    DOI: 10.1080/10438590600925201
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. George Messinis, 2011. "Triadic citations, country biases and patent value: the case of pharmaceuticals," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 813-833, December.
    2. francesco schettino, 2009. "Scale effect on endogenous growth: an evaluation," Economics Bulletin, AccessEcon, vol. 29(1), pages 205-213.
    3. Claudio Cozza & Francesco Schettino, 2015. "Explaining the Patenting Propensity: A Regional Analysis Using EPO-OECD Data," AIEL Series in Labour Economics, in: Chiara Mussida & Francesco Pastore (ed.), Geographical Labor Market Imbalances, edition 127, chapter 0, pages 219-236, Springer.
    4. Alessandro Caiani, 2017. "Innovation Dynamics and Industry Structure Under Different Technological Spaces," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 307-341, November.
    5. Wonchang Hur, 2017. "The patterns of knowledge spillovers across technology sectors evidenced in patent citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 595-619, May.

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