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.
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References
J.R. Baldwin G. Gellatly (2000) ‘A Firm-based Approach to Industry Classification: Identifying the Knowledge-based Economy’ L.A. Lefebvre E. Lefebvre P. Mohnen (Eds) Doing Business in a Knowledge-Based Economy, Facts and Policy Challenges Kluwer Academic Publishers Boston, Mass
E. Brouwer A.H. Kleinknecht (1996) ‘Determinants of Innovation: A Micro Econometric Analysis of Three Alternative Innovative Output Indicators’ A.H. Kleinknecht (Eds) Determinants of Innovation: The Message from New Indicators Macmillan London
B. Crépon E. Duguet J. Mairesse (1998) ArticleTitle‘Research and Development, Innovation and Productivity: An Econometric Analysis at the Firm Level’ Economics of Innovation and New Technology 7 115–158
Hatzichronoglou, T. (1997), ‘Revision of the High-technology Sector and Product Classification,’ Working Paper.
H. Hollenstein (1996) ArticleTitle‘A Composite Indicator of a Firm’s Innovativeness An Empirical Analysis Based on Survey Data for Swiss Manufacturing’ Research Policy 25 633–645 Occurrence Handle10.1016/0048-7333(95)00874-8
Janz, N., H. Loöf and B. Peters (2003), ‘Firm Level Innovation and Productivity: Is There a Common Story Across Countries,’ ZEW Discussion Paper, No. 03–26
Janz, N. and B. Peters (2002), ‘Innovation and Innovation Success in the German Manufacturing Sector: Econometric Evidence at Firm Level,’ ZEW Working Paper.
L. Klomp G. Leeuwen Particlevan (2001) ArticleTitle‘Linking Innovation and Firm Performance: A New Approach’ International Journal of the Economics of Business 8 343–364
S. Lach (2002) ArticleTitle‘Do R&D Subsidies Stimulate or Displace Private R&D’ Journal of Industrial Economics 50 369–390 Occurrence Handle10.1111/1467-6451.00182
G.S. Maddala (1983) Limited-Dependent and Qualitative Variables in Econometrics Cambridge University Press Cambridge
J. Mairesse P. Mohnen (2001) ArticleTitle‘To Be or Not to Be Innovative: An Exercise in Measurement’ STI Review Special Issue on New Science and Technology Indicators 27 103–129
P. Mohnen M. Dagenais (2001) ‘Towards an Innovation Intensity Index. The Case of C is 1 in Denmark and Ireland A. Kleinknecht P. Mohnen (Eds) Innovation and Firm Performance: Econometric Explorations of Survey Data Palgrave London
InstitutionalAuthorNameOECD (1997) OECD Proposed Guidelines for Collecting and Interpreting Technological Innovation Data, Oslo Manual EditionNumber2 OECD Paris
InstitutionalAuthorNameOECD (1998) Technology, Productivity and Job Creation: Best Policy Practices OECD Paris
InstitutionalAuthorNameOECD (1999) Science, Technology and Industry Scoreboard Benchmarking Knowledge-Based Economies. OECD Paris
K. Pavitt (1984) ArticleTitle‘Sectoral Patterns of Technical Change: Towards a Taxonomy and a Theory’ Research Policy 13 343–373 Occurrence Handle10.1016/0048-7333(84)90018-0
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.
R.N. Rosett (1959) ArticleTitle‘A Statistical Model of Friction in Economics’ Econometrica 27 141–146
A. Thomas (2000) Econométrie des Variables Qualitatives Dunod Paris
van Leeuwen, G. (2002), ‘Linking Innovation to Productivity Growth Using Two Waves of the Community Innovation Survey,’ STI Working Paper.
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The empirical part of this study has been carried out at the Centre for Research of Economic Microdata at Statistics Netherlands. The authors wish to thank Statistics Netherlands, and in particular Bert Diederen, for helping us in accessing and using the Micronoom data set. The views expressed in this paper are solely those of the authors. The authors also wish to thank François Laisney, Patrick Waelbroek and participants at presentations in Maastricht, Strasbourg, Leuven and Lille for their helpful comments. The first author acknowledges financial support from METEOR.
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Raymond, W., Mohnen, P., Palm, F. et al. A Classification of Dutch Manufacturing based on a Model of Innovation. De Economist 154, 85–105 (2006). https://doi.org/10.1007/s10645-006-0005-z
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DOI: https://doi.org/10.1007/s10645-006-0005-z