IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_1681.html
   My bibliography  Save this paper

Persistence of Innovation in Dutch Manufacturing: Is it Spurious?

Author

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

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.

Suggested Citation

  • Wladimir Raymond & Pierre Mohnen & Franz Palm & Sybrand Schim van der Loeff, 2006. "Persistence of Innovation in Dutch Manufacturing: Is it Spurious?," CESifo Working Paper Series 1681, CESifo.
  • Handle: RePEc:ces:ceswps:_1681
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp1681.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cefis, Elena & Orsenigo, Luigi, 2001. "The persistence of innovative activities: A cross-countries and cross-sectors comparative analysis," Research Policy, Elsevier, vol. 30(7), pages 1139-1158, August.
    2. 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.
    3. 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.
    4. 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, January.
    5. Jacques Mairesse & Pierre Mohnen, 2001. "To Be or Not To Be Innovative: An Exercise in Measurement," NBER Working Papers 8644, National Bureau of Economic Research, Inc.
    6. 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.
    7. Geroski, Paul A, 1989. "Entry, Innovation and Productivity Growth," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 572-578, November.
    8. repec:fth:harver:1473 is not listed on IDEAS
    9. 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 - Leibniz Centre for European Economic Research.
    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 243-263, May-June.
    11. Geroski, P. A. & Van Reenen, J. & Walters, C. F., 1997. "How persistently do firms innovate?," Research Policy, Elsevier, vol. 26(1), pages 33-48, March.
    12. 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.
    13. 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.
    14. Elena Cefis & Matteo Ciccarelli, 2005. "Profit differentials and innovation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(1-2), pages 43-61.
    15. 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.
    16. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
    17. Ekaterini Kyriazidou, 2001. "Estimation of Dynamic Panel Data Sample Selection Models," Review of Economic Studies, Oxford University Press, vol. 68(3), pages 543-572.
    18. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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.
    2. Mañez, J.A. & Love, J.H., 2020. "Quantifying sunk costs and learning effects in R&D persistence," Research Policy, Elsevier, vol. 49(7).
    3. Mairesse, Jacques & Mohnen, Pierre, 2010. "Using Innovation Surveys for Econometric Analysis," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1129-1155, Elsevier.
    4. Juan Máñez & María Rochina-Barrachina & Amparo Sanchis-Llopis & Juan Sanchis-Llopis, 2015. "The determinants of R&D persistence in SMEs," Small Business Economics, Springer, vol. 44(3), pages 505-528, March.
    5. Wladimir Raymond & Pierre Mohnen & Franz Palm & Sybrand Schim van der Loeff, 2009. "Innovative Sales, R&D and Total Innovation Expenditures: Panel Evidence on their Dynamics," CESifo Working Paper Series 2716, CESifo.
    6. Marta F. Arroyabe & Martin Schumann, 2022. "On the Estimation of True State Dependence in the Persistence of Innovation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 850-893, August.
    7. Triguero, Ángela & Córcoles, David, 2013. "Understanding innovation: An analysis of persistence for Spanish manufacturing firms," Research Policy, Elsevier, vol. 42(2), pages 340-352.
    8. Emmanuel Duguet & Stéphanie Monjon, 2004. "Is innovation persistent at the firm Level. An econometric examination comparing the propensity score and regression methods," Cahiers de la Maison des Sciences Economiques v04075, Université Panthéon-Sorbonne (Paris 1).
    9. Holl, Adelheid & Peters, Bettina & Rammer, Christian, 2020. "Local knowledge spillovers and innovation persistence of firms," ZEW Discussion Papers 20-005, ZEW - Leibniz Centre for European Economic Research.
    10. Mulkay, Benoît, 2019. "How does competition affect innovation behaviour in french firms?," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 237-251.
    11. Bianchini, Stefano & Pellegrino, Gabriele, 2019. "Innovation persistence and employment dynamics," Research Policy, Elsevier, vol. 48(5), pages 1171-1186.
    12. Cefis, Elena & Marsili, Orietta, 2015. "Crossing the innovation threshold through mergers and acquisitions," Research Policy, Elsevier, vol. 44(3), pages 698-710.
    13. Pere Arqué-Castells, 2013. "Persistence in R&D Performance and its Implications for the Granting of Subsidies," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 43(3), pages 193-220, November.
    14. Antonelli Cristiano & Crespi, Francesco & Scellato, Giuseppe, 2013. "Path Dependent Patterns of Persistence in Productivity Growth," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201310, University of Turin.
    15. Cappelen, Ådne & Raknerud, Arvid & Rybalka, Marina, 2012. "The effects of R&D tax credits on patenting and innovations," Research Policy, Elsevier, vol. 41(2), pages 334-345.
    16. Alessandra Colombelli & Francesco Quatraro, 2014. "The persistence of firms' knowledge base: a quantile approach to Italian data," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 23(7), pages 585-610, October.
    17. Labeaga, José M. & Martínez-Ros, Ester & Sanchis, Amparo & Sanchis, Juan A., 2021. "Does persistence in using R&D tax credits help to achieve product innovations?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    18. Bettina Peters & Christian Rammer, 2013. "Innovation panel surveys in Germany," Chapters, in: Fred Gault (ed.), Handbook of Innovation Indicators and Measurement, chapter 6, pages 135-177, Edward Elgar Publishing.
    19. Fontana, Roberto & Vezzulli, Andrea, 2016. "Technological leadership and persistence in product innovation in the Local Area Network industry 1990–1999," Research Policy, Elsevier, vol. 45(8), pages 1604-1619.
    20. Antonelli, Cristiano & Crespi, Francesco & Scellato, Giuseppe, 2010. "Universities look beyond the patent policy discourse in their intellectual property strategies," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201010, University of Turin.

    More about this item

    Keywords

    dynamic panel data type 2 tobit; innovation; spurious persistence;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_1681. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.