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Knowledge spillovers in U.S. patents: A dynamic patent intensity model with secret common innovation factors

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Author Info

  • Szabolcs Blazsek

    ()
    (Department of Business Administration - Universidad de Navarra)

  • Alvaro Escribano

    ()
    (Universidad Carlos III de Madrid - Universidad Carlos III de Madrid)

Abstract

During the past two decades, innovations protected by patents have played a key role in business strategies. This fact enhanced studies of the determinants of patents and the impact of patents on innovation and competitive advantage. Sustaining competitive advantages is as important as creating them. Patents help sustaining competivite advantages by increasing the production cost of competitors, by signaling a better quality of products and by serving as barriers to entry. If patents are rewards for innovation, more R&D should be reflected in more patents applications but this is not the end of the story. There is empirical evidence showing that patents through time are becoming easier to get and more valuable to the firm due to increasing damage awards from infringers. These facts question the constant and static nature of the relationship between R&D and patents. Furthermore, innovation creates important knowledge spillovers due to its imperfect appropriability. Our paper investigates these dynamic effects using U.S. patent data from 1979 to 2000 with alternative model specifications for patent counts. We introduce a general dynamic count panel data model with dynamic observable and unobservable spillovers, which encompasses previous models, is able to control for the endogeneity of R&D and therefore can be consistently estimated by maximum likelihood. Apart from allowing for firm specific fixed and random effects, we introduce a common unobserved component, or secret stock of knowledge, that affects differently the propensity to patent of each firm across sectors due to their different absorptive capacity.

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Bibliographic Info

Paper provided by HAL in its series Post-Print with number peer-00732533.

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Date of creation: 15 Sep 2010
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Publication status: Published, Journal of Econometrics, 2010, 159, 1, 14
Handle: RePEc:hal:journl:peer-00732533

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Related research

Keywords: C15; C31; C32; C33; C41; Point process; Conditional intensity; Latent factor; R&D spillovers; Patents; Secret innovations;

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References

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Citations

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Cited by:
  1. Waters, James, 2011. "The effect of the Sarbanes-Oxley Act on innovation," MPRA Paper 28072, University Library of Munich, Germany.
  2. Alvaro Escribano & Szabolcs Blazsek, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," Economics Working Papers we1202, Universidad Carlos III, Departamento de Economía.
  3. Jesús Manuel Plaza Llorente, 2012. "Innovación y caos determinista: un modelo predictivo para Europa," EKONOMIAZ, Gobierno Vasco / Eusko Jaurlaritza / Basque Government, vol. 80(02), pages 260-289.

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