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Knowledge spillovers in US patents: A dynamic patent intensity model with secret common innovation factors

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  • Blazsek, Szabolcs
  • Escribano, Alvaro

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 competitive 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 patent 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 US 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

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 159 (2010)
Issue (Month): 1 (November)
Pages: 14-32

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Handle: RePEc:eee:econom:v:159:y:2010:i:1:p:14-32

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: Point process Conditional intensity Latent factor R&D spillovers Patents Secret innovations;

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References

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  1. Richard, Jean-Francois & Zhang, Wei, 2007. "Efficient high-dimensional importance sampling," Journal of Econometrics, Elsevier, vol. 141(2), pages 1385-1411, December.
  2. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-38, July.
  3. Manuel Trajtenberg & Adam B. Jaffe & Michael S. Fogarty, 2000. "Knowledge Spillovers and Patent Citations: Evidence from a Survey of Inventors," American Economic Review, American Economic Association, vol. 90(2), pages 215-218, May.
  4. Holly, S. & Pesaran, M.H. & Yamagata. T., 2006. "A Spatio-Temporal Model of House Prices in the US," Cambridge Working Papers in Economics 0654, Faculty of Economics, University of Cambridge.
  5. Cincera, Michele, 1997. "Patents, R&D, and Technological Spillovers at the Firm Level: Some Evidence from Econometric Count Models for Panel Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 265-80, May-June.
  6. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
  7. Philippe Aghion & Nicholas Bloom & Richard Blundell & Rachel Griffith & Peter Howitt, 2002. "Competition and innovation: an inverted U relationship," IFS Working Papers W02/04, Institute for Fiscal Studies.
  8. Crepon, B. & Duguet, E. & Mairesse, J., 1998. "Research Investment, Innovation and Productivity: An Econometric Analysis at the Firm Level," Papiers d'Economie Mathématique et Applications 98.15, Université Panthéon-Sorbonne (Paris 1).
  9. Iain Cockburn & Zvi Griliches, 1987. "Industry Effects and Appropriability Measures in the Stock Markets Valuation of R&D and Patents," NBER Working Papers 2465, National Bureau of Economic Research, Inc.
  10. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
  11. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
  12. Aghion, P. & Howitt, P., 1989. "A Model Of Growth Through Creative Destruction," UWO Department of Economics Working Papers 8904, University of Western Ontario, Department of Economics.
  13. Lanjouw, Jean O & Pakes, Ariel & Putnam, Jonathan, 1998. "How to Count Patents and Value Intellectual Property: The Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Wiley Blackwell, vol. 46(4), pages 405-32, December.
  14. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth Through Creative Destruction," Scholarly Articles 12490578, Harvard University Department of Economics.
  15. Jovanovic, B. & MacDonald, G.M., 1991. "Competitive Diffusion," Papers 92-08, Rochester, Business - Financial Research and Policy Studies.
  16. Bruno Cassiman & Reinhilde Veugelers, 2002. "R&D Cooperation and Spillovers: Some Empirical Evidence from Belgium," American Economic Review, American Economic Association, vol. 92(4), pages 1169-1184, September.
  17. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
  18. Iain M. Cockburn & Stefan Wagner, 2007. "Patents and the Survival of Internet-related IPOs," NBER Working Papers 13146, National Bureau of Economic Research, Inc.
  19. Fung, Michael K. & Chow, William W., 2002. "Measuring the intensity of knowledge flow with patent statistics," Economics Letters, Elsevier, vol. 74(3), pages 353-358, February.
  20. Bruno Crépon & Emmanuel Duguet & Jacques Mairesse, 1998. "Research, Innovation and Productivity : An Econometric Analysis at the Firm Level," Working Papers 98-33, Centre de Recherche en Economie et Statistique.
  21. Adam B. Jaffe & Michael S. Fogarty & Bruce A. Banks, 1997. "Evidence from Patents and Patent Citations on the Impact of NASA and Other Federal Labs on Commercial Innovation," NBER Working Papers 6044, National Bureau of Economic Research, Inc.
  22. Michael K. Fung, 2005. "Are Knowledge Spillovers Driving the Convergence of Productivity among Firms?," Economica, London School of Economics and Political Science, vol. 72(286), pages 287-305, 05.
  23. William Greene, 2001. "Estimating Econometric Models With Fixed Effects," Working Papers 01-10, New York University, Leonard N. Stern School of Business, Department of Economics.
  24. Christian GOURIEROUX & Alain MONFORT, 1991. "Simulation Based Inference in Models with Heterogeneity," Annales d'Economie et de Statistique, ENSAE, issue 20-21, pages 69-107.
  25. Jacques Mairesse & Bronwyn H. Hall, 1996. "Estimating the Productivity of Research and Development: An Exploration of GMM Methods Using Data on French & United States Manufacturing Firms," NBER Working Papers 5501, National Bureau of Economic Research, Inc.
  26. BAUWENS, Luc & HAUTSCH, Nikolaus, . "Stochastic conditional intensity processes," CORE Discussion Papers RP -1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  27. Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, vol. 28(4), pages 1661-1707, December.
  28. Ariel Pakes & Mark Schankerman, 1984. "The Rate of Obsolescence of Patents, Research Gestation Lags, and the Private Rate of Return to Research Resources," NBER Chapters, in: R & D, Patents, and Productivity, pages 73-88 National Bureau of Economic Research, Inc.
  29. 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.
  30. Mansfield, Edwin & Schwartz, Mark & Wagner, Samuel, 1981. "Imitation Costs and Patents: An Empirical Study," Economic Journal, Royal Economic Society, vol. 91(364), pages 907-18, December.
  31. Escribano, Alvaro & Fosfuri, Andrea & Tribó, Josep A., 2009. "Managing external knowledge flows: The moderating role of absorptive capacity," Research Policy, Elsevier, vol. 38(1), pages 96-105, February.
  32. Pakes, Ariel, 1985. "On Patents, R & D, and the Stock Market Rate of Return," Scholarly Articles 3436409, Harvard University Department of Economics.
  33. Jean O. Lanjouw & Mark Schankerman, 1999. "The Quality of Ideas: Measuring Innovation with Multiple Indicators," NBER Working Papers 7345, National Bureau of Economic Research, Inc.
  34. repec:fth:harver:1473 is not listed on IDEAS
  35. Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
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Citations

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Cited by:
  1. 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.
  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. Waters, James, 2011. "The effect of the Sarbanes-Oxley Act on innovation," MPRA Paper 28072, University Library of Munich, Germany.

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