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Who\'s Who in Patents. A Bayesian approach

Author

Listed:
  • Nicolas CARAYOL
  • Lorenzo CASSI

Abstract

This paper proposes a bayesian methodology to treat the who’s who problem arising in individual level data sets such as patent data. We assess the usefullness of this methodology on the set of all French inventors appearing on EPO applications from 1978 to 2003.

Suggested Citation

  • Nicolas CARAYOL & Lorenzo CASSI, 2009. "Who\'s Who in Patents. A Bayesian approach," Cahiers du GREThA (2007-2019) 2009-07, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    • Handle: RePEc:grt:wpegrt:2009-07
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    File URL: http://cahiersdugretha.u-bordeaux.fr/2009/2009-07.pdf
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    Cited by:

    1. Bergé, Laurent & Carayol, Nicolas & Roux, Pascale, 2018. "How do inventor networks affect urban invention?," Regional Science and Urban Economics, Elsevier, vol. 71(C), pages 137-162.
    2. Carayol, Nicolas & Bergé, Laurent & Cassi, Lorenzo & Roux, Pascale, 2019. "Unintended triadic closure in social networks: The strategic formation of research collaborations between French inventors," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 218-238.
    3. Lorenzo Cassi & Anne Plunket, 2014. "Proximity, network formation and inventive performance: in search of the proximity paradox," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(2), pages 395-422, September.
    4. Michele Pezzoni & Francesco Lissoni & Gianluca Tarasconi, 2014. "How to kill inventors: testing the Massacrator© algorithm for inventor disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 477-504, October.
    5. Deyun Yin & Kazuyuki Motohashi & Jianwei Dang, 2020. "Large-scale name disambiguation of Chinese patent inventors (1985–2016)," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 765-790, February.
    6. Pascal Cuxac & Jean-Charles Lamirel & Valerie Bonvallot, 2013. "Efficient supervised and semi-supervised approaches for affiliations disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 47-58, October.
    7. Julie Le Gallo & Anne Plunket, 2016. "Technological gatekeepers, regional inventor networks and inventive performance," Working Papers hal-01422916, HAL.
    8. Li, Guan-Cheng & Lai, Ronald & D’Amour, Alexander & Doolin, David M. & Sun, Ye & Torvik, Vetle I. & Yu, Amy Z. & Fleming, Lee, 2014. "Disambiguation and co-authorship networks of the U.S. patent inventor database (1975–2010)," Research Policy, Elsevier, vol. 43(6), pages 941-955.
    9. Ernest Miguélez & Ismael Gómez-Miguélez, 2011. "Singling out individual inventors from patent data," Working Papers XREAP2011-03, Xarxa de Referència en Economia Aplicada (XREAP), revised May 2011.
    10. Gallo, Julie Le & Plunket, Anne, 2020. "Regional gatekeepers, inventor networks and inventive performance: Spatial and organizational channels," Research Policy, Elsevier, vol. 49(5).
    11. Ventura, Samuel L. & Nugent, Rebecca & Fuchs, Erica R.H., 2015. "Seeing the non-stars: (Some) sources of bias in past disambiguation approaches and a new public tool leveraging labeled records," Research Policy, Elsevier, vol. 44(9), pages 1672-1701.
    12. YIN Deyun & Kazuyuki MOTOHASHI, 2018. "Inventor Name Disambiguation with Gradient Boosting Decision Tree and Inventor Mobility in China (1985-2016)," Discussion papers 18018, Research Institute of Economy, Trade and Industry (RIETI).

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    Keywords

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    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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