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

This paper examines the impact of public research and development (R&D) support on cost reducing innovation for wind turbine farms in Denmark, Germany and the United Kingdom (UK). First we survey the literature in this field. The literature indicates that in Denmark R&D policy has been more successful than in Germany or the UK in promoting innovation of wind turbines. Furthermore, such studies point out that (subsidy-induced) capacity expansions were more effective in the UK and Denmark in promoting cost-reducing innovation than in Germany. The second part of the paper describes the quantitative analysis of the impact of R&D and capacity expansion on innovation. This is calculated using the two-factor learning curve (2FLC) model, in which investment cost reductions are explained by cumulative capacity and the R&D based knowledge stock. Time-series data were collected for the three countries and organized as a panel data set. The parameters of the 2FLC model were estimated, focusing on the homogeneity and heterogeneity of the parameters across countries. We arrived at robust estimations of a learning-by-doing rate of 5.4% and a learning-by-searching rate of 12.6%. The analysis underlines the homogeneity of the learning parameters, enhancing the validity of the 2FLC formulation.