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Persistence of Innovation in Dutch Manufacturing: Is It Spurious?

  • Wladimir Raymond

    (University of Maastricht)

  • Pierre Mohnen

    (University of Maastricht, UNU-MERIT and CIRANO)

  • Franz Palm

    (University of Maastricht and CESifo)

  • Sybrand Schim van der Loeff

    (University of Maastricht)

This paper studies the persistence of innovation in Dutch manufacturing using an unbalanced panel of firm data from four waves of the Community Innovation Survey between 1994 and 2002. We estimate by maximum likelihood a dynamic type 2 tobit model accounting for individual effects and handling the initial conditions problem. We find true persistence in the probability of innovating in the high-tech category of industries and spurious persistence in the low-tech category. Furthermore, past innovation output intensity affects, albeit to a small extent, current innovation output intensity in the high-tech category, while no such evidence is found in the low-tech category. © 2010 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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Article provided by MIT Press in its journal The Review of Economics and Statistics.

Volume (Year): 92 (2010)
Issue (Month): 3 (August)
Pages: 495-504

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Handle: RePEc:tpr:restat:v:92:y:2010:i:3:p:495-504
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  1. Bettina Peters, 2009. "Persistence of innovation: stylised facts and panel data evidence," The Journal of Technology Transfer, Springer, vol. 34(2), pages 226-243, April.
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  4. repec:fth:harver:1473 is not listed on IDEAS
  5. Peters, Bettina & Lööf, Hans & Janz, Norbert, 2003. "Firm Level Innovation and Productivity: Is there a Common Story Across Countries?," ZEW Discussion Papers 03-26, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
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  8. Bruno Crepon & Emmanuel Duguet & Jacques Mairesse, 1998. "Research, Innovation And Productivity: An Econometric Analysis At The Firm Level," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(2), pages 115-158.
  9. 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.
  10. 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.
  11. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
  12. 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.
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