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Producing Innovations: Determinants of Innovativity and Efficiency

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  • Jaap W.B. Bos
  • Ryan C.R. van Lamoen
  • Mark W.J.L. Sanders

Abstract

In this paper we estimate, using stochastic frontier estimation techniques, the relationship between R&D inputs a innovative output in a sample of Dutch firms. We find that over 63% of between firm variation in observed "innovativeness" can be attributed to inefficiency in the innovation process. The remainder is due to differences in the innovation production process itself. We derive our results including the usual controls and find in addition that large firms tend to look more innovative. But when considered more carefully large firms turn out to be less efficient. With standard estimation techniques this inefficiency is masked by a more productive innovation technology. We thus find evidence of economies of scale in line with the Schumpeter mark II hypothesis (large firms are more innovative), but also show that large firms tend to operate at lower levels of efficiency.

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Bibliographic Info

Paper provided by DEGIT, Dynamics, Economic Growth, and International Trade in its series DEGIT Conference Papers with number c016_060.

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Length: 17 pages
Date of creation: Sep 2011
Date of revision:
Handle: RePEc:deg:conpap:c016_060

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Related research

Keywords: Innovation; Scale Economies; Frontier;

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References

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  1. Aghion, P. & Howitt, P., 1990. "A Model Of Growth Through Creative Destruction," DELTA Working Papers 90-12, DELTA (Ecole normale supérieure).
  2. Daron Acemoglu, 2002. "Directed Technical Change," Review of Economic Studies, Oxford University Press, vol. 69(4), pages 781-809.
  3. Philippe Aghion & Nick Bloom & Richard Blundell & Rachel Griffith & Peter Howitt, 2005. "Competition and Innovation: An Inverted-U Relationship," The Quarterly Journal of Economics, MIT Press, vol. 120(2), pages 701-728, May.
  4. Acemoglu, D., 1997. "Why Do New Technologies Complement Skills? Directed Technical Change and Wage Inequality," Working papers 97-14, Massachusetts Institute of Technology (MIT), Department of Economics.
  5. Daron Acemoglu, 2000. "Technical Change, Inequality, and the Labor Market," NBER Working Papers 7800, National Bureau of Economic Research, Inc.
  6. Erik Brouwer & Tom Poot & Kees Montfort, 2008. "The Innovation Threshold," De Economist, Springer, vol. 156(1), pages 45-71, March.
  7. Baltagi, Badi H & Griffin, James M, 1988. "A General Index of Technical Change," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 20-41, February.
  8. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
  9. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  10. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(03), December.
  11. Dinopoulos, Elias & Thompson, Peter, 1998. " Schumpeterian Growth without Scale Effects," Journal of Economic Growth, Springer, vol. 3(4), pages 313-35, December.
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Cited by:
  1. Daria Ciriaci & Pietro Moncada-Paternò-Castello & Peter Voigt, 2012. "Does size or age of innovative firms affect their growth persistence? -Evidence from a panel of innovative Spanish firms-," JRC-IPTS Working Papers on Corporate R&D and Innovation 2012-03, Institute of Prospective Technological Studies, Joint Research Centre.
  2. Bucci, Alberto, 2013. "Returns to specialization, competition, population, and growth," Journal of Economic Dynamics and Control, Elsevier, vol. 37(10), pages 2023-2040.

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