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Selection Bias in Innovation Studies. A Simple Test

Author

Listed:
  • Gaétan de Rassenfosse

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; Intellectual Property Research Institute of Australia, The University of Melbourne)

  • Anja Schoen

    (Technische Universität München)

  • Annelies Wastyn

    (Department of Managerial Economics, Strategy and Innovation, KU Leuven)

Abstract
The study of the innovative output of organizations often relies on a count of patents filed at one single office of reference such as the European Patent Office (EPO). Yet, not all organizations file their patents at the EPO, raising the specter of a selection bias. Using novel datasets of the whole population of patents by Belgian firms and German universities, we show that the single-office count results in a selection bias that affects econometric estimates of invention production functions. We propose a methodology to evaluate whether estimates that rely on the single-office count are affected by a selection bias.

Suggested Citation

  • Gaétan de Rassenfosse & Anja Schoen & Annelies Wastyn, 2013. "Selection Bias in Innovation Studies. A Simple Test," Melbourne Institute Working Paper Series wp2013n08, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  • Handle: RePEc:iae:iaewps:wp2013n08
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    References listed on IDEAS

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    Cited by:

    1. Anja Schoen & Dominik Heinisch & Guido Buenstorf, 2014. "Playing the ‘Name Game’ to identify academic patents in Germany," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 527-545, October.
    2. Goossen, Martin C. & Paruchuri, Srikanth, 2022. "Measurement errors and estimation biases with incomplete social networks: replication studies on intra-firm inventor network analysis," Research Policy, Elsevier, vol. 51(1).
    3. Mueller, Elisabeth & Boeing, Philipp, 2024. "Global influence of inventions and technology sovereignty," ZEW Discussion Papers 24-024, ZEW - Leibniz Centre for European Economic Research, revised 2024.
    4. de Rassenfosse, Gaétan & Dernis, Hélène & Guellec, Dominique & Picci, Lucio & van Pottelsberghe de la Potterie, Bruno, 2013. "The worldwide count of priority patents: A new indicator of inventive activity," Research Policy, Elsevier, vol. 42(3), pages 720-737.
    5. Jérôme Danguy & Gaetan de Rassenfosse & Bruno van Pottelsberghe de la Potterie, 2014. "On the origins of the worldwide surge in patenting: an industry perspective on the R&D–patent relationship," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 23(2), pages 535-572.
    6. Bruns, Stephan B. & Kalthaus, Martin, 2020. "Flexibility in the selection of patent counts: Implications for p-hacking and evidence-based policymaking," Research Policy, Elsevier, vol. 49(1).
    7. Ernest Miguélez, 2018. "Inventor Diasporas and the Internationalization of Technology," The World Bank Economic Review, World Bank, vol. 32(1), pages 41-63.
    8. Herz, Benedikt & Mejer, Malwina, 2019. "Effects of the European Union trademark: Lessons for the harmonization of intellectual property systems," Research Policy, Elsevier, vol. 48(7), pages 1841-1854.
    9. Boeing, Philipp & Mueller, Elisabeth, 2016. "Measuring patent quality in cross-country comparison," Economics Letters, Elsevier, vol. 149(C), pages 145-147.
    10. Zwick, Thomas & Frosch, Katharina & Hoisl, Karin & Harhoff, Dietmar, 2017. "The power of individual-level drivers of inventive performance," Research Policy, Elsevier, vol. 46(1), pages 121-137.
    11. Hugo Confraria & Vitor Hugo Ferreira & Manuel Mira Godinho, 2021. "Emerging 21st Century technologies: Is Europe still falling behind?," Working Papers REM 2021/0188, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.

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    More about this item

    Keywords

    Knowledge production function; patent count; R&D; selection bias;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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