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Persistence of Innovation in Dutch Manufacturing: Is it Spurious?

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  • Raymond Wladimir
  • Mohnen, Pierre
  • Palm, Franz
  • Schim, van der Loeff, Sybrand

    (METEOR)

Abstract

This paper studies the persistence of innovation and the dynamics of innovation output in Dutch manufacturing using firm data from three waves of the Community Innovation Surveys (CIS), pertaining to the periods 1994-1996, 1996-1998, and 1998-2000. We estimate by maximum likelihood a dynamic panel data type 2 tobit model accounting for individual effects and handling the initial conditions problem. We find that there is no evidence of true persistence in achieving technological product or process innovations, while past shares of innovative sales condition, albeit to a small extent, current shares of innovative sales.

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Bibliographic Info

Paper provided by Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR) in its series Research Memorandum with number 009.

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Date of creation: 2006
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Handle: RePEc:unm:umamet:2006009

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Keywords: Economics ;

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  1. 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.
  2. Luuk Klomp & George Van Leeuwen, 2001. "Linking Innovation and Firm Performance: A New Approach," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 8(3), pages 343-364.
  3. Bruno Crepon & Emmanuel Duguet & Jacques Mairessec, 1998. "Research, Innovation And Productivi[Ty: An Econometric Analysis At The Firm Level," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(2), pages 115-158.
  4. Peters, Bettina, 2005. "Persistence of Innovation: Stylised Facts and Panel Data Evidence," ZEW Discussion Papers 05-81, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  5. 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.
  6. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
  7. Janz, Norbert & Lööf, Hans & Peters, Bettina, 2004. "Firm Level Innovation and Productivity - Is there a Common Story Across Countries?," Working Paper Series in Economics and Institutions of Innovation 24, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
  8. Geroski, Paul A, 1989. "Entry, Innovation and Productivity Growth," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 572-78, November.
  9. repec:fth:harver:1473 is not listed on IDEAS
  10. Crepon, Bruno & Duguet, Emmanuel, 1997. "Estimating the Innovation Function from Patent Numbers: GMM on Count Panel Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 243-63, May-June.
  11. Malerba, Franco & Orsenigo, Luigi, 1999. "Technological entry, exit and survival: an empirical analysis of patent data," Research Policy, Elsevier, vol. 28(6), pages 643-660, August.
  12. Kyriazidou, Ekaterini, 2001. "Estimation of Dynamic Panel Data Sample Selection Models," Review of Economic Studies, Wiley Blackwell, vol. 68(3), pages 543-72, July.
  13. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
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