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Employment Effect of Innovation

The present paper estimates and decomposes the employment e?ect of innovation by R&D intensity levels. Our micro-econometric analysis is based on a large international panel data set from the EU Industrial R&D Investment Scoreboard. Employing ?exible semi-parametric methods – the generalised propensity score – allows us to recover the full functional relationship between the R&D investment and ?rm employment, and to address important econometric issues, which is not possible in the standard estimation approach used in the previous literature. Our results suggest that modest innovators do not create and may even destruct jobs by raising their R&D expenditures. Most of the jobs in the economy are created by innovation followers: increasing innovation by 1% may increase employment up to 0.7%. The job creation e?ect of innovation reaches its peak when the R&D intensity is around 100% of the total capital expenditure, after which the positive employment e?ect declines and becomes statistically insigni?cant. Innovation leaders do not create jobs by further increasing their R&D expenditures, which are already very high.

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File URL: http://dx.doi.org/10.3929/ethz-a-010852605
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Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 17-428.

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Length: 38 pages
Date of creation: Feb 2017
Handle: RePEc:kof:wpskof:17-428
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  4. Becker, Sascha O. & Egger, Peter H. & von Ehrlich, Maximilian, 2012. "Too much of a good thing? On the growth effects of the EU's regional policy," European Economic Review, Elsevier, vol. 56(4), pages 648-668.
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  6. Francesco Di Comite & D'Artis Kancs & Wouter Torfs, 2015. "Macroeconomic Modelling of R&D and Innovation Policies," JRC Working Papers JRC89558, Joint Research Centre (Seville site).
  7. Francesco Bogliacino, 2014. "Innovation and employment: A firm level analysis with European R&D Scoreboard data," Economia, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 15(2), pages 141-154.
  8. Bogliacino, Francesco & Lucchese, Matteo & Pianta, Mario, 2013. "Job creation in business services: Innovation, demand, and polarisation," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 95-109.
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  14. Daria Ciriaci & Pietro Moncada-Paternò-Castello & Peter Voigt, 2016. "Innovation and job creation: a sustainable relation?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 6(2), pages 189-213, August.
  15. Francesco Di Comite & D'Artis Kancs, 2015. "Macro-Economic Models for R&D and Innovation Policies - A Comparison of QUEST, RHOMOLO, GEM-E3 and NEMESIS," JRC Working Papers JRC94323, Joint Research Centre (Seville site).
  16. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
  17. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
  18. Bun, Maurice J. G. & Kiviet, Jan F., 2003. "On the diminishing returns of higher-order terms in asymptotic expansions of bias," Economics Letters, Elsevier, vol. 79(2), pages 145-152, May.
  19. Tommaso Antonucci & Mario Pianta, 2002. "Employment Effects of Product and Process Innovation in Europe," International Review of Applied Economics, Taylor & Francis Journals, vol. 16(3), pages 295-307.
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