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Renewable energy innovations in Europe: a dynamic panel data approach

  • Nadia Ayari
  • Szabolcs Blazsek
  • Pedro Mendi

We investigate the determinants of renewable energy R&D intensity and the impact of renewable energy innovations on firm performance, using several dynamic panel data models. We estimate these models using a large data set of European firms from 19 different countries, with some patenting activity in areas related to renewable energies during the 1987 to 2007 period. Our results confirm our priors on the determinants of the rapid development of renewable energy R&D intensity during the past decades. Additionally, we find evidence that renewable patent intensity has a significant dynamic impact on the stock market value of firms.

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File URL: http://hdl.handle.net/10.1080/00036846.2011.570720
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Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 44 (2012)
Issue (Month): 24 (August)
Pages: 3135-3147

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Handle: RePEc:taf:applec:44:y:2012:i:24:p:3135-3147
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  1. Jacques Mairesse & Bronwyn H. Hall, 1996. "Estimating the Productivity of Research and Development: An Exploration of GMM Methods Using Data on French & United States Manufacturing Firms," NBER Working Papers 5501, National Bureau of Economic Research, Inc.
  2. Nick Johnstone & Ivan Haščič & David Popp, 2010. "Renewable Energy Policies and Technological Innovation: Evidence Based on Patent Counts," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 45(1), pages 133-155, January.
  3. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
  4. repec:fth:harver:1473 is not listed on IDEAS
  5. Gil-Alana, Luis Alberiko & Moreno, Antonio, 2009. "Technology Shocks And Hours Worked: A Fractional Integration Perspective," Macroeconomic Dynamics, Cambridge University Press, vol. 13(05), pages 580-604, November.
  6. Michael Binder, Cheng Hsiao, and M. Hashem Pesaran, 2001. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Computing in Economics and Finance 2001 36, Society for Computational Economics.
  7. Jeffrey M Wooldridge, 2002. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," CeMMAP working papers CWP18/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. Lanjouw, Jean O & Pakes, Ariel & Putnam, Jonathan, 1998. "How to Count Patents and Value Intellectual Property: The Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Wiley Blackwell, vol. 46(4), pages 405-32, December.
  9. Bruno Van Pottelsberghe & Herman Denis & Dominique Guellec, 2001. "Using patent counts for cross-country comparisons of technology output," ULB Institutional Repository 2013/6227, ULB -- Universite Libre de Bruxelles.
  10. David Popp, 2002. "Induced Innovation and Energy Prices," American Economic Review, American Economic Association, vol. 92(1), pages 160-180, March.
  11. Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, vol. 28(4), pages 1661-1707, December.
  12. David Popp, 2003. "Lessons from Patents: Using Patents To Measure Technological Change in Environmental Models," NBER Working Papers 9978, National Bureau of Economic Research, Inc.
  13. Margolis, Robert M. & Kammen, Daniel M., 1999. "Evidence of under-investment in energy R&D in the United States and the impact of Federal policy," Energy Policy, Elsevier, vol. 27(10), pages 575-584, October.
  14. Ragwitz, Mario & Miola, Apollonia, 2005. "Evidence from RD&D spending for renewable energy sources in the EU," Renewable Energy, Elsevier, vol. 30(11), pages 1635-1647.
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