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Nonparametric Approach to Patent Citations

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  • Petr Mariel
  • Susan Orbe

Abstract

The present article reexamines some of the issues regarding the benchmarking of patents using the NBER data base on U.S. patents by generalizing a parametric citation model and by estimating it using Generalized Additive Models (GAM) methodology. The main conclusion is that the estimated effects differ considerably from sector to sector, and the differences can be estimated nonparametrically but not by the parametric dummy variable approach.

Suggested Citation

  • Petr Mariel & Susan Orbe, 2009. "Nonparametric Approach to Patent Citations," Prague Economic Papers, Prague University of Economics and Business, vol. 2009(3), pages 251-266.
    • Handle: RePEc:prg:jnlpep:v:2009:y:2009:i:3:id:353:p:251-266
    DOI: 10.18267/j.pep.353
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    References listed on IDEAS

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    1. repec:fth:harver:1473 is not listed on IDEAS
    2. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2000. "Market Value and Patent Citations: A First Look," NBER Working Papers 7741, National Bureau of Economic Research, Inc.
    3. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    4. Basberg, Bjorn L., 1987. "Patents and the measurement of technological change: A survey of the literature," Research Policy, Elsevier, vol. 16(2-4), pages 131-141, August.
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    More about this item

    Keywords

    GAM; patent benchmarking; USPTO;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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