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Nonparametric Approach to Patent Citations


  • Petr Mariel
  • Susan Orbe


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, University of Economics, Prague, vol. 2009(3), pages 251-266.
  • Handle: RePEc:prg:jnlpep:v:2009:y:2009:i:3:id:353:p:251-266

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    References listed on IDEAS

    1. Hall, Bronwyn H. & Jaffee, Adam & Trajtenberg, Manuel, 2000. "Market Value and Patent Citations: A First Look," Department of Economics, Working Paper Series qt1rh8k6z2, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. repec:fth:harver:1473 is not listed on IDEAS
    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


    GAM; patent benchmarking; USPTO;

    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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