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Investigating Cohort Similarity as an Ex Ante Alternative to Patent Forward Citations

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  • Jonathan H. Ashtor

Abstract

Forward citations are arguably the most widely used empirical metric for patents, including as indicators of patent information content, cumulative innovation, value, and knowledge flows. However, forward citations have major shortcomings. Citations require long time horizons to accrue, and therefore they cannot be observed until several years after a patent issues. Citation data are often noisy, discontinuous, and highly skewed, complicating empirical analysis. Moreover, recent studies have questioned the reliability of citation data. As such, the most widely used empirical metric of patents is also the most suspect. This study constructs a measure of patents that correlates with forward citations, but is observable ex ante, immediately upon patent issuance or even earlier upon publication of a patent application. In addition, this measure is continuous and evenly distributed, such that it is suitable for large‐scale patent analytics applications. Finally, unlike citations, the measure is portable across patent systems, facilitating cross‐border comparisons of portfolios and datasets. Specifically, I construct a measure of the similarity of a patent to its technological‐temporal cohort, based on linguistic analysis of claim text. I employ advanced computational linguistic techniques to analyze the claims of all U.S. patents issued in the period 1976–2017, over 6 million patents in total, and I calculate the average degree of conceptual similarity of each patented invention to all others in the same technology field and time period cohort. I then extend the methodology to all issued EP patents, over 1.6 million in total. I validate the resulting measures against multiple established patent metrics for U.S. and EP patents. I test the robustness of this measure as a forecast for future patent citations in empirical research and big‐data applications. I find that cohort similarity correlates significantly with forward citations received by both U.S. and EP patents. Cohort similarity also substitutes for citations in leading prior studies of R&D output and innovation. Finally, I demonstrate that, unlike citations, cohort similarity is comparable across the U.S. and EP patent systems. Accordingly, cohort similarity may be useful for empirical patent research, comparative studies of patent policy, and analytics of large‐scale patent portfolios.

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  • Jonathan H. Ashtor, 2019. "Investigating Cohort Similarity as an Ex Ante Alternative to Patent Forward Citations," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 16(4), pages 848-880, December.
    • Handle: RePEc:wly:empleg:v:16:y:2019:i:4:p:848-880
    DOI: 10.1111/jels.12237
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    as
    1. Lanjouw, Jean O & Schankerman, Mark, 2001. "Characteristics of Patent Litigation: A Window on Competition," RAND Journal of Economics, The RAND Corporation, vol. 32(1), pages 129-151, Spring.
    2. Juan Alcácer & Michelle Gittelman, 2006. "Patent Citations as a Measure of Knowledge Flows: The Influence of Examiner Citations," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 774-779, November.
    3. van Zeebroeck, Nicolas & van Pottelsberghe de la Potterie, Bruno & Guellec, Dominique, 2009. "Claiming more: the Increased Voluminosity of Patent Applications and its Determinants," Research Policy, Elsevier, vol. 38(6), pages 1006-1020, July.
    4. Adam B. Jaffe & Benjamin F. Jones, 2015. "The Changing Frontier: Rethinking Science and Innovation Policy," NBER Books, National Bureau of Economic Research, Inc, number jaff13-1.
    5. 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.
    6. Bhaven N. Sampat, 2010. "When Do Applicants Search for Prior Art?," Journal of Law and Economics, University of Chicago Press, vol. 53(2), pages 399-416, May.
    7. Bronwyn H. Hall & Adam Jaffe & Manuel Trajtenberg, 2005. "Market Value and Patent Citations," RAND Journal of Economics, The RAND Corporation, vol. 36(1), pages 16-38, Spring.
    8. Hall, B. & Jaffe, A. & Trajtenberg, M., 2001. "The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools," Papers 2001-29, Tel Aviv.
    9. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    10. Lei, Zhen & Wright, Brian D., 2017. "Why weak patents? Testing the examiner ignorance hypothesis," Journal of Public Economics, Elsevier, vol. 148(C), pages 43-56.
    11. Leonid Kogan & Dimitris Papanikolaou & Amit Seru & Noah Stoffman, 2017. "Technological Innovation, Resource Allocation, and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(2), pages 665-712.
    12. Ricardo J. Caballero & Adam B. Jaffe, 1993. "How High Are the Giants' Shoulders: An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth," NBER Chapters, in: NBER Macroeconomics Annual 1993, Volume 8, pages 15-86, National Bureau of Economic Research, Inc.
    13. repec:bla:jindec:v:46:y:1998:i:4:p:405-32 is not listed on IDEAS
    14. Deborah Strumsky & José Lobo & Sander van der Leeuw, 2012. "Using patent technology codes to study technological change," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 21(3), pages 267-286, April.
    15. Jaffe, Adam B. & Jones, Benjamin F. (ed.), 2015. "The Changing Frontier," National Bureau of Economic Research Books, University of Chicago Press, number 9780226286723, September.
    16. Strumsky, Deborah & Lobo, José, 2015. "Identifying the sources of technological novelty in the process of invention," Research Policy, Elsevier, vol. 44(8), pages 1445-1461.
    17. Alberto Galasso & Mark Schankerman, 2014. "Patents and Cumulative Innovation: Causal Evidence from the Courts," NBER Working Papers 20269, National Bureau of Economic Research, Inc.
    18. Antonin Bergeaud & Yoann Potiron & Juste Raimbault, 2017. "Classifying patents based on their semantic content," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-22, April.
    19. Michael Roach & Wesley M. Cohen, 2013. "Lens or Prism? Patent Citations as a Measure of Knowledge Flows from Public Research," Management Science, INFORMS, vol. 59(2), pages 504-525, October.
    20. Marco, Alan C., 2007. "The dynamics of patent citations," Economics Letters, Elsevier, vol. 94(2), pages 290-296, February.
    21. David S. Abrams & Ufuk Akcigit & Jillian Grennan, 2013. "Patent Value and Citations: Creative Destruction or Strategic Disruption?," NBER Working Papers 19647, National Bureau of Economic Research, Inc.
    22. Bruno Cassiman & Reinhilde Veugelers & Pluvia Zuniga, 2008. "In search of performance effects of (in)direct industry science links," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 17(4), pages 611-646, August.
    23. Jean O. Lanjouw & Ariel Pakes & Jonathan Putnam, 1998. "How to Count Patents and Value Intellectual Property: The Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Wiley Blackwell, vol. 46(4), pages 405-432, December.
    24. Manuel Trajtenberg & Rebecca Henderson & Adam Jaffe, 1997. "University Versus Corporate Patents: A Window On The Basicness Of Invention," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 5(1), pages 19-50.
    25. Tong, Xuesong & Frame, J. Davidson, 1994. "Measuring national technological performance with patent claims data," Research Policy, Elsevier, vol. 23(2), pages 133-141, March.
    26. Ashish Arora & Sharon Belenzon & Honggi Lee, 2018. "Reversed citations and the localization of knowledge spillovers," Journal of Economic Geography, Oxford University Press, vol. 18(3), pages 495-521.
    27. Harhoff, Dietmar & Scherer, Frederic M. & Vopel, Katrin, 2003. "Citations, family size, opposition and the value of patent rights," Research Policy, Elsevier, vol. 32(8), pages 1343-1363, September.
    28. Corredoira, Rafael A. & Banerjee, Preeta M., 2015. "Measuring patent's influence on technological evolution: A study of knowledge spanning and subsequent inventive activity," Research Policy, Elsevier, vol. 44(2), pages 508-521.
    29. Jean O. Lanjouw & Mark Schankerman, 2004. "Patent Quality and Research Productivity: Measuring Innovation with Multiple Indicators," Economic Journal, Royal Economic Society, vol. 114(495), pages 441-465, April.
    30. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
    31. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
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    3. Neil Gandal & Michal Shur-Ofry & Michael Crystal & Royee Shilony, 2021. "Out of sight: patents that have never been cited," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2903-2929, April.

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