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The identification of important innovations using tail estimators

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  • Carolina Castaldi

    ()

  • Bart Los

    ()

Abstract

International differences in economic performance are often attributed to differences in innovative performance. Much empirical work supports this contention, but problems in quantifying innovative output prevent researchers from drawing a clear picture. Innovations are very heterogeneous regarding their importance, with only very few innovations yielding substantial returns. Citation frequencies are one measure of the value of innovations. We use a recently introduced technique based on results from Extreme Value Theory to estimate the characteristics of the tail of the distribution of citations. We identify important innovations as those that receive a number of citations higher than the ‘cutoff point’ of the tail of the distributions of citations. The data come from the NBER Patent-Citations Database. We provide estimates of the proportions of important patents for 31 technological categories and discuss emerging patterns. Possible implications for technology policy and innovation management are also drawn.

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Bibliographic Info

Paper provided by Utrecht University, Department of Innovation Studies in its series Innovation Studies Utrecht (ISU) working paper series with number 08-07.

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Date of creation: Feb 2008
Date of revision: Feb 2008
Handle: RePEc:uis:wpaper:0807

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Web page: http://www.uu.nl/faculty/geosciences/EN/research/institutesandgroups/researchinstitutes/copernicusinstitute/research/Innovation/Pages/default.aspx

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References

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  1. Jaffe, Adam B & Trajtenberg, Manuel & Henderson, Rebecca, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, MIT Press, vol. 108(3), pages 577-98, August.
  2. Bulat Sanditov, 2005. "Patent Citations, the Value of Innovations and Path-Dependency," KITeS Working Papers 177, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Nov 2005.
  3. Bronwyn H. Hall & Manuel Trajtenberg, 2004. "Uncovering GPTS with Patent Data," NBER Working Papers 10901, National Bureau of Economic Research, Inc.
  4. Silverberg, G. & Verspagen, B., 2004. "The size distribution of innovations revisited: an application of extreme value statistics to citation and value measures of patent significance," Working Papers 04.17, Eindhoven Center for Innovation Studies.
  5. F. M. Scherer & Dietmar Harhoff & J, rg Kukies, 2000. "Uncertainty and the size distribution of rewards from innovation," Journal of Evolutionary Economics, Springer, vol. 10(1), pages 175-200.
  6. Rosenberg, Nathan, 1969. "The Direction of Technological Change: Inducement Mechanisms and Focusing Devices," Economic Development and Cultural Change, University of Chicago Press, vol. 18(1), pages 1-24, Part I Oc.
  7. Manuel Trajtenberg & Adam B. Jaffe & Michael S. Fogarty, 2000. "Knowledge Spillovers and Patent Citations: Evidence from a Survey of Inventors," American Economic Review, American Economic Association, vol. 90(2), pages 215-218, May.
  8. Dahlin, Kristina B. & Behrens, Dean M., 2005. "When is an invention really radical?: Defining and measuring technological radicalness," Research Policy, Elsevier, vol. 34(5), pages 717-737, June.
  9. Drees, Holger & Kaufmann, Edgar, 1998. "Selecting the optimal sample fraction in univariate extreme value estimation," Stochastic Processes and their Applications, Elsevier, vol. 75(2), pages 149-172, July.
  10. Hall, Bronwyn H & Jaffe, Adam B & Trajtenberg, Manuel, 2001. "The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools," CEPR Discussion Papers 3094, C.E.P.R. Discussion Papers.
  11. Utterback, James M & Abernathy, William J, 1975. "A dynamic model of process and product innovation," Omega, Elsevier, vol. 3(6), pages 639-656, December.
  12. Haupt, Reinhard & Kloyer, Martin & Lange, Marcus, 2007. "Patent indicators for the technology life cycle development," Research Policy, Elsevier, vol. 36(3), pages 387-398, April.
  13. Thomas Lux, 2001. "The limiting extremal behaviour of speculative returns: an analysis of intra-daily data from the Frankfurt Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 11(3), pages 299-315.
  14. Silverberg, G. & Verspagen, B., 2003. "Brewing the future: stylized facts about innovation and their confrontation with a percolation model," Working Papers 03.06, Eindhoven Center for Innovation Studies.
  15. Akkermans, Dirk & Castaldi, Carolina & Los, Bart, 2007. "Do ‘Liberal Market Economies’ Really Innovate More Radically than ‘Coordinated Market Economies’? Hall & Soskice Reconsidered," GGDC Research Memorandum GD-91, Groningen Growth and Development Centre, University of Groningen.
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Cited by:
  1. Akkermans, Dirk & Castaldi, Carolina & Los, Bart, 2009. "Do 'liberal market economies' really innovate more radically than 'coordinated market economies'?: Hall and Soskice reconsidered," Research Policy, Elsevier, vol. 38(1), pages 181-191, February.

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