De Economist

, Volume 154, Issue 1, pp 85–105 | Cite as

A Classification of Dutch Manufacturing based on a Model of Innovation

  • Wladimir Raymond
  • Pierre Mohnen
  • Franz Palm
  • Sybrand Schim van der Loeff
Notes and Communications

Summary

The paper studies the degree of homogeneity of innovative behavior in order to determine empirically an industry classification of Dutch manufacturing that can be used for policy purposes. Defining homogeneity in terms of an economic model distinguishes our classification from existing taxonomies such as those of the OECD, Pavitt and the various classifications based on a principal components analysis. We use a two-limit tobit model with sample selection, which explains the decisions by business enterprises to innovate and the impact these decisions have on the share of innovative sales. The model is estimated for eleven industries based on the Dutch Standard Industrial Classification (SBI 1993). A likelihood ratio (LR) test is then performed to test for equality of the parameters across industries. We find that Dutch manufacturing consists of three groups of industries in terms of innovative behavior, a high-tech group, a low-tech group and the industry of wood. The same pattern shows up in the three Dutch Community Innovation Surveys.

Keywords

CIS industry classification innovation policy two-limit tobit model 

JEL Code(s)

C34 C51 O33 O38 

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References

  1. Baldwin, J.R., Gellatly, G. 2000

    ‘A Firm-based Approach to Industry Classification: Identifying the Knowledge-based Economy’

    Lefebvre, L.A.Lefebvre, E.Mohnen, P. eds. Doing Business in a Knowledge-Based Economy, Facts and Policy ChallengesKluwer Academic PublishersBoston, Mass
    Google Scholar
  2. Brouwer, E., Kleinknecht, A.H. 1996

    ‘Determinants of Innovation: A Micro Econometric Analysis of Three Alternative Innovative Output Indicators’

    Kleinknecht, A.H. eds. Determinants of Innovation: The Message from New IndicatorsMacmillanLondon
    Google Scholar
  3. Crépon, B., Duguet, E., Mairesse, J. 1998‘Research and Development, Innovation and Productivity: An Econometric Analysis at the Firm Level’Economics of Innovation and New Technology7115158Google Scholar
  4. Hatzichronoglou, T. (1997), ‘Revision of the High-technology Sector and Product Classification,’ Working Paper.Google Scholar
  5. Hollenstein, H. 1996‘A Composite Indicator of a Firm’s Innovativeness An Empirical Analysis Based on Survey Data for Swiss Manufacturing’Research Policy25633645CrossRefGoogle Scholar
  6. Janz, N., H. Loöf and B. Peters (2003), ‘Firm Level Innovation and Productivity: Is There a Common Story Across Countries,’ ZEW Discussion Paper, No. 03–26Google Scholar
  7. Janz, N. and B. Peters (2002), ‘Innovation and Innovation Success in the German Manufacturing Sector: Econometric Evidence at Firm Level,’ ZEW Working Paper.Google Scholar
  8. Klomp, L., Leeuwen, G. 2001‘Linking Innovation and Firm Performance: A New Approach’International Journal of the Economics of Business8343364Google Scholar
  9. Lach, S. 2002‘Do R&D Subsidies Stimulate or Displace Private R&D’Journal of Industrial Economics50369390CrossRefGoogle Scholar
  10. Maddala, G.S. 1983Limited-Dependent and Qualitative Variables in EconometricsCambridge University PressCambridgeGoogle Scholar
  11. Mairesse, J., Mohnen, P. 2001‘To Be or Not to Be Innovative: An Exercise in Measurement’STI Review Special Issue on New Science and Technology Indicators27103129Google Scholar
  12. Mohnen, P., Dagenais, M. 2001

    ‘Towards an Innovation Intensity Index. The Case of C is 1 in Denmark and Ireland

    Kleinknecht, A.Mohnen, P. eds. Innovation and Firm Performance: Econometric Explorations of Survey DataPalgraveLondon
    Google Scholar
  13. OECD1997OECD Proposed Guidelines for Collecting and Interpreting Technological Innovation Data, Oslo Manual2OECDParisGoogle Scholar
  14. OECD1998Technology, Productivity and Job Creation: Best Policy PracticesOECDParisGoogle Scholar
  15. OECD1999Science, Technology and Industry ScoreboardBenchmarking Knowledge-Based Economies. OECDParisGoogle Scholar
  16. Pavitt, K. 1984‘Sectoral Patterns of Technical Change: Towards a Taxonomy and a Theory’Research Policy13343373CrossRefGoogle Scholar
  17. Raymond, W., P. Mohnen, F. Palm and S. Schim van der Loeff (2004), ‘An Empirically-based Taxonomy of Dutch Manufacturing: Innovation Policy Implications,’ CESifo Working Paper, No. 1230.Google Scholar
  18. Rosett, R.N. 1959‘A Statistical Model of Friction in Economics’Econometrica27141146Google Scholar
  19. Thomas, A. 2000Econométrie des Variables QualitativesDunodParisGoogle Scholar
  20. van Leeuwen, G. (2002), ‘Linking Innovation to Productivity Growth Using Two Waves of the Community Innovation Survey,’ STI Working Paper.Google Scholar

Copyright information

© Springer 2006

Authors and Affiliations

  • Wladimir Raymond
    • 1
  • Pierre Mohnen
    • 2
  • Franz Palm
    • 3
  • Sybrand Schim van der Loeff
    • 1
  1. 1.University of MaastrichtNetherlands
  2. 2.University of Maastricht, MERIT and CIRANONetherlands
  3. 3.University of Maastricht and CESifo fellow Vakgroep Kwantitatieve EconomieMaastrichtNetherlands

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