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Are Patent Citations Driven by Quality?

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  • Christian Ghiglino

    ()

  • Nicole Kuschy

    ()

Abstract

The present paper builds a simple model of patent citations not based on the rich-get-richer aspect of preferential attachment. In our model the dynamics of citations are driven by known heterogeneities in the applicability of existing patents and aging. The model matches closely the hazard rates of citations for the vast majority of patents in a random sample of patents granted by the USPTO between 1975 and 1999. Furthermore, we show that the long run distribution of patent citations is well fitted when the distribution of applicability across patents follows a Gamma-distribution.We also discuss the possibility that popularity of patents might influence citation decisions if innovators are not perfectly informed about patents' applicability. We find that popularity matters but the size of the effect is very small. Finally, the possibility to distinguish between citations to patents within the same class and to different classes allows us to show that the magnitude of the influence of popularity is increasing in technological distance.

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Paper provided by University of Essex, Department of Economics in its series Economics Discussion Papers with number 692.

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Date of creation: 29 Oct 2010
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Handle: RePEc:esx:essedp:692

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  1. Marco, Alan C., 2007. "The dynamics of patent citations," Economics Letters, Elsevier, vol. 94(2), pages 290-296, February.
  2. Dietmar Harhoff & Francis Narin & F. M. Scherer & Katrin Vopel, 1999. "Citation Frequency And The Value Of Patented Inventions," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 511-515, August.
  3. Ghiglino, Christian, 2012. "Random walk to innovation: Why productivity follows a power law," Journal of Economic Theory, Elsevier, vol. 147(2), pages 713-737.
  4. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
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Cited by:
  1. Lafond, Francois, 2012. "Learning and the structure of citation networks," MERIT Working Papers 071, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

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