IDEAS home Printed from https://ideas.repec.org/p/hal/cesptp/hal-00631750.html
   My bibliography  Save this paper

Who's Who in Patents. A Bayesian approach

Author

Listed:
  • Lorenzo Cassi

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Nicolas Carayol

    (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)

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

  • Lorenzo Cassi & Nicolas Carayol, 2009. "Who's Who in Patents. A Bayesian approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00631750, HAL.
    • Handle: RePEc:hal:cesptp:hal-00631750
    Note: View the original document on HAL open archive server: https://paris1.hal.science/hal-00631750
    as

    Download full text from publisher

    File URL: https://paris1.hal.science/hal-00631750/document
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Zvi Griliches, 1984. "R&D, Patents, and Productivity," NBER Books, National Bureau of Economic Research, Inc, number gril84-1.
    2. Manuel Trajtenberg & Gil Shiff & Ran Melamed, 2009. "The "Names Game": Harnessing Inventors, Patent Data for Economic Research," Annals of Economics and Statistics, GENES, issue 93-94, pages 67-77.
    3. Nicolas Carayol & Pascale Roux, 2007. "The Strategic Formation of Interindividual Collaboration Networks. Evidence from Co-invention Patterns," Annals of Economics and Statistics, GENES, issue 87-88, pages 275-301.
    4. Francesco Lissoni & Bulat Sanditov & Gianluca Tarasconi, 2006. "The Keins Database on Academic Inventors: Methodology and Contents," KITeS Working Papers 181, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Sep 2006.
    5. repec:adr:anecst:y:2007:i:87-88:p:13 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Gallo, Julie Le & Plunket, Anne, 2020. "Regional gatekeepers, inventor networks and inventive performance: Spatial and organizational channels," Research Policy, Elsevier, vol. 49(5).
    5. 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.
    6. Ernest Miguélez & Ismael Gómez-Miguélez, 2011. "“Singling out individual inventors from patent data”," IREA Working Papers 201105, University of Barcelona, Research Institute of Applied Economics, revised May 2011.
    7. 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.
    8. YIN Deyun & MOTOHASHI Kazuyuki, 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).
    9. 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.
    10. 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.
    11. Julie Le Gallo & Anne Plunket, 2016. "Technological gatekeepers, regional inventor networks and inventive performance," Working Papers hal-01422916, HAL.
    12. 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.

    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. 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.
    2. Paul Almeida & Anupama Phene & Sali Li, 2010. "Communities, Knowledge, and Innovation: Indian Immigrants in the US Semiconductor Industry," Working Papers 58, globADVANTAGE, Polytechnic Institute of Leiria.
    3. 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.
    4. Stefano Breschi & Camilla Lenzi, 2010. "Spatial patterns of inventors' mobility: Evidence on US urban areas," Papers in Regional Science, Wiley Blackwell, vol. 89(2), pages 235-250, June.
    5. Ernest Miguelez & Carsten Fink, 2013. "Measuring the International Mobility of Inventors: A New Database," WIPO Economic Research Working Papers 08, World Intellectual Property Organization - Economics and Statistics Division, revised May 2013.
    6. Herrera, Liliana & Muñoz-Doyague, Maria Felisa & Nieto, Mariano, 2010. "Mobility of public researchers, scientific knowledge transfer, and the firm's innovation process," Journal of Business Research, Elsevier, vol. 63(5), pages 510-518, May.
    7. Ernest Miguélez & Rosina Moreno & Jordi Suriñach, 2010. "Inventors on the move: Tracing inventors' mobility and its spatial distribution," Papers in Regional Science, Wiley Blackwell, vol. 89(2), pages 251-274, June.
    8. Olof Ejermo, 2009. "Regional Innovation Measured by Patent Data—Does Quality Matter?," Industry and Innovation, Taylor & Francis Journals, vol. 16(2), pages 141-165.
    9. repec:wip:wpaper:8 is not listed on IDEAS
    10. 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.
    11. Favaro, Donata & Ninka, Eniel & Turvani, Margherita, 2014. "Knowledge externalities and knowledge creation: the role of inventors’ working relationships and mobility," MPRA Paper 64527, University Library of Munich, Germany.
    12. Marc Gruber & Dietmar Harhoff & Karin Hoisl, 2013. "Knowledge Recombination Across Technological Boundaries: Scientists vs. Engineers," Management Science, INFORMS, vol. 59(4), pages 837-851, April.
    13. Dirk Czarnitzki & Hanna Hottenrott & Susanne Thorwarth, 2011. "Industrial research versus development investment: the implications of financial constraints," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 35(3), pages 527-544.
    14. Sheikh, Shahbaz, 2018. "The impact of market competition on the relation between CEO power and firm innovation," Journal of Multinational Financial Management, Elsevier, vol. 44(C), pages 36-50.
    15. Kelly D. Edmiston, 2007. "The role of small and large businesses in economic development," Economic Review, Federal Reserve Bank of Kansas City, vol. 92(Q II), pages 73-97.
    16. Diégo Legros & Fabrice Galia, 2012. "Are innovation and R&D the only sources of firms’ knowledge that increase productivity? An empirical investigation of French manufacturing firms," Journal of Productivity Analysis, Springer, vol. 38(2), pages 167-181, October.
    17. Matthias Firgo & Peter Mayerhofer, 2015. "Wissens-Spillovers und regionale Entwicklung - welche strukturpolitische Ausrichtung optimiert des Wachstum?," Working Paper Reihe der AK Wien - Materialien zu Wirtschaft und Gesellschaft 144, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik.
    18. Martin Andersson & Hans Lööf, 2009. "Learning‐by‐Exporting Revisited: The Role of Intensity and Persistence," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(4), pages 893-916, December.
    19. Cilem Selin Hazir & Corinne Autant-Bernard, 2012. "Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation Some empirical evidence from EU Framework Programs in biotechnology," Working Papers 1212, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    20. de Rassenfosse, Gaétan & Schoen, Anja & Wastyn, Annelies, 2014. "Selection bias in innovation studies: A simple test," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 287-299.
    21. Yu-Shan Chen & Ke-Chiun Chang, 2009. "Using neural network to analyze the influence of the patent performance upon the market value of the US pharmaceutical companies," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(3), pages 637-655, September.

    More about this item

    Keywords

    Patents; homonymy; Bayes rule;
    All these keywords.

    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

    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:hal:cesptp:hal-00631750. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.