The impact of R&D on innovation for wind energy in Denmark, Germany and the United Kingdom

By G. Klaassen, Asami Miketa, K. Larsen, T. Sundqvist. 2005

443 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Finance

View Paper: https://www.semanticscholar.org/paper/4b143d4cd95a9cc349cc33d81ac4aa550c5ed349

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Citations in the corpus

On the Drivers of Eco-Innovations: Empirical Evidence from the UK (2012, background): “Indeed, regulations may be the only means to break out of existing technological lock-ins and move towards eco-technologies that usually have higher costs at least in the short term (Arthur, 1989; Klaassen et al., 2005).”
Empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies (2007, background): “[18] and extend this traditional learning curve concept by considering cumulative R&D expenses on wind energy in the model.”
A review of learning rates for electricity supply technologies (2015, background): “Other studies also find significant correlations between cumulative R&D expenditures (and/or R&D-based knowledge stock) and subsequent (time-lagged) cost reductions (Klaassen et al., 2005; Jamasb, 2007; Söderholm and Klaassen, 2007; Söderholm and Sundqvist, 2007).”
Wind Power in Europe: A Simultaneous Innovation–Diffusion Model (2007, background): “However, we also build on Klaassen et al. (2005) and extend this traditional learning curve concept by considering cumulative R&D expenses on wind energy in the model.”
A review of uncertainties in technology experience curves (2012, methodology): “There has been somework to validate this formulationwith empirical data (Jamasb, 2007; Klaassen et al., 2005; Söderholm and Klassen, 2007; Söderholm and Sundqvist, 2007).”
The experience curve theory and its application in the field of electricity generation technologies – A literature review (2018, background): “[124] Germany, Denmark, UK Installed capacity Investment costs 1986-2000 5 0.”
Combining Policies for Renewable Energy: Is the Whole Less than the Sum of its Parts? (2010, background): “Klaassen et al. (2005) focus specifically on the empirical effects of public R&D support in Denmark, Germany, and the United Kingdom.”
The Role of R&D and Technology Diffusion in Climate Change Mitigation: New Perspectives Using the Witch Model (2009, unknown): “This confirms the fact that mitigation policy costs are far more sensitive to the technology assumptions driving the future development of backstop technologies than to those underlying learning processes in existing renewable energies or energy efficiency improving R&D.”