IDEAS home Printed from https://ideas.repec.org/p/ein/tuecis/0417.html
   My bibliography  Save this paper

The size distribution of innovations revisited: an application of extreme value statistics to citation and value measures of patent significance

Author

Listed:
  • Silverberg, G.

    (MERIT, Maastricht University)

  • Verspagen, B.

    (ECIS, Eindhoven University of Technology)

Abstract

This paper focuses on the analysis of size distributions of innovations, which are known to be highly skewed. We use patent citations as one indicator of innovation significance, constructing two large datasets from the European and US Patent Offices at a high level of aggregation, and the Trajtenberg (1990) dataset on CT scanners at a very low one. We also study self-assessed reports of patented innovation values using two very recent patent valuation datasets from the Netherlands and the UK, as well as a small dataset of patent license revenues of Harvard University. Statistical methods are applied to analyse the properties of the empirical size distributions, where we put special emphasis on testing for the existence of ‘heavy tails’, i.e., whether or not the probability of very large innovations declines more slowly than exponentially. While overall the distributions appear to resemble a lognormal, we argue that the tails are indeed fat. We invoke some recent results from extreme value statistics and apply the Hill (1975) estimator with data-driven cut-offs to determine the tail index for the right tails of all datasets except the NL and UK patent valuations. On these latter datasets we use a maximum likelihood estimator for grouped data to estimate the Pareto exponent for varying definitions of the right tail. We find significantly and consistently lower tail estimates for the returns data than the citation data (around 0.7 vs. 3-5). The EPO and US patent citation tail indices are roughly constant over time (although the US one does grow somewhat in the last periods) but the latter estimates are significantly lower than the former. The heaviness of the tails, particularly as measured by financial indices, we argue, has significant implications for technology policy and growth theory, since the second and possibly even the first moments of these distributions may not exist. (JEL Codes: C16, O31, O33 Keywords: returns to invention, patent citations, extreme-value
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • 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.
  • Handle: RePEc:ein:tuecis:0417
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Simon Kuznets, 1962. "Inventive Activity: Problems of Definition and Measurement," NBER Chapters, in: The Rate and Direction of Inventive Activity: Economic and Social Factors, pages 19-52, National Bureau of Economic Research, Inc.
    2. Manuel Trajtenberg, 1990. "A Penny for Your Quotes: Patent Citations and the Value of Innovations," RAND Journal of Economics, The RAND Corporation, vol. 21(1), pages 172-187, Spring.
    3. Hall, Bronwyn H. & Jaffee, Adam & Trajtenberg, Manuel, 2000. "Market Value and Patent Citations: A First Look," Department of Economics, Working Paper Series qt1rh8k6z2, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. 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.
    5. Adam B. Jaffe & Manuel Trajtenberg & Michael S. Fogarty, 2000. "The Meaning of Patent Citations: Report on the NBER/Case-Western Reserve Survey of Patentees," NBER Working Papers 7631, National Bureau of Economic Research, Inc.
    6. 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.
    7. De Vany, Arthur S. & Walls, W. David, 2004. "Motion picture profit, the stable Paretian hypothesis, and the curse of the superstar," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1035-1057, March.
    8. Silverberg, Gerald & Verspagen, Bart, 2005. "A percolation model of innovation in complex technology spaces," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 225-244, January.
    9. repec:adr:anecst:y:1998:i:49-50:p:19 is not listed on IDEAS
    10. F. M. Scherer, 1998. "The Size Distribution of Profits from Innovation," Annals of Economics and Statistics, GENES, issue 49-50, pages 495-516.
    11. Dietmar Harhoff & Francis Narin & F. M. Scherer & Katrin Vopel, 1999. "Citation Frequency And The Value Of Patented Inventions," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 511-515, August.
    12. Hall, Peter, 1990. "Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 177-203, February.
    13. 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.
    14. Scherer, F. M. & Harhoff, Dietmar, 2000. "Technology policy for a world of skew-distributed outcomes," Research Policy, Elsevier, vol. 29(4-5), pages 559-566, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gerald Silverberg & Bart Verspagen, 2007. "Self-organization of R&D search in complex technology spaces," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(2), pages 211-229, December.
    2. Per Botolf Maurseth, 2005. "Lovely but dangerous: The impact of patent citations on patent renewal," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(5), pages 351-374.
    3. 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.
    4. Silverberg, Gerald & Verspagen, Bart, 2005. "A percolation model of innovation in complex technology spaces," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 225-244, January.
    5. Laura Magazzini & Fabio Pammolli & Massimo Riccaboni, 2008. "Patent Value and R&D Competition," Working Papers 51/2008, University of Verona, Department of Economics.
    6. Silverberg, Gerald & Verspagen, Bart, 2002. "A Percolation Model of Innovation in Complex Technology," Research Memorandum 032, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    7. Takanori Ida & Naomi Fukuzawa, 2013. "Effects of large-scale research funding programs: a Japanese case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1253-1273, March.
    8. Carolina Castaldi & Bart Los, 2008. "The identification of important innovations using tail estimators," Innovation Studies Utrecht (ISU) working paper series 08-07, Utrecht University, Department of Innovation Studies, revised Feb 2008.
    9. Nicolas van Zeebroeck, 2011. "The puzzle of patent value indicators," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 20(1), pages 33-62.
    10. Leila Tahmooresnejad & Catherine Beaudry, 2019. "Collaboration or funding: lessons from a study of nanotechnology patenting in Canada and the United States," The Journal of Technology Transfer, Springer, vol. 44(3), pages 741-777, June.
    11. Kilponen, Juha & Santavirta, Torsten, 2004. "Competition and Innovation - Microeconometric Evidence using Finnish Data," Research Reports 113, VATT Institute for Economic Research.
    12. Quentin Plantec & Pascal Le Masson & Benoit Weil, 2020. "Impact of knowledge search practices on the originality of inventions: a study in the oil & gas industry," Post-Print hal-02613665, HAL.
    13. Gianluca Baio & Laura Magazzini & Claudia Oglialoro & Fabio Pammolli & Massimo Riccaboni, 2005. "Medical Devices: Competitiveness and Impact on Public Health Expenditure," Working Papers CERM 05-2005, Competitività, Regole, Mercati (CERM).
    14. Ufuk Akcigit, 2009. "Firm Size, Innovation Dynamics and Growth," 2009 Meeting Papers 1267, Society for Economic Dynamics.
    15. Bruno Van Pottelsberghe & Eleftherios Sapsalis & Ran Navon, 2006. "Academic vs. industry patenting: an in-depth analysis of what determines patent value," Working Papers CEB 05-008.RS, ULB -- Universite Libre de Bruxelles.
    16. Emmanuel Duguet & Megan MacGarvie, 2005. "How well do patent citations measure flows of technology? Evidence from French innovation surveys," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(5), pages 375-393.
    17. 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.
    18. Hagedoorn, John & Cloodt, Myriam, 2003. "Measuring innovative performance: is there an advantage in using multiple indicators?," Research Policy, Elsevier, vol. 32(8), pages 1365-1379, September.
    19. Michele Cincera & Ela Ince, 2019. "Types of Innovation and Firm performance," Working Papers TIMES² 2019-032, ULB -- Universite Libre de Bruxelles.
    20. Mu-Hsuan Huang & Dar-Zen Chen & Danqi Shen & Mona S. Wang & Fred Y. Ye, 2015. "Measuring technological performance of assignees using trace metrics in three fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 61-86, July.

    More about this item

    Keywords

    distribution; patent; innovation;
    All these keywords.

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ein:tuecis:0417. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/ectuenl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.