Technology diffusion and innovation in the European wind power sector : the impact of energy and R&D policies

The purpose of this paper is to provide an econometric analysis of innovation and diffusion in the European wind power sector. We derive models of wind power innovation and diffusion, which combine a rational choice model of technological diffusion and a learning curve model of cost reductions. The learning model attempts to account for the presence of both domestic learning-by-doing as well as international knowledge spillovers (global learning), and test the extent to which the respective learning-by-doing rates differ. The models are estimated using pooled annual time series data for five European countries (Denmark, Germany, Spain, Swe-den and the United Kingdom) over the time period 1986-2001. The empirical results indicate that reductions in investment costs are an important determinant of increased diffusion of wind power, and these cost reductions are in turn explained by both domestic and global learning-by-doing but less so by knowledge accumulating as a result of public R&D support. Feed-in tariffs also play a role in the innovation and diffusion processes. The higher is the feed-in price the higher is, ceteris paribus, the rate of diffusion, and we also test the hypothesis that the impact on diffusion of a marginal increase in the feed-in tariff will differ depending on the support system used. The results support the notion that the UK competitive bidding system was (ceteris paribus) less effective in inducing wind power diffusion compared to the other countries' fixed tariff support schemes. Overall the estimates generated by the learning models are sensitive to the way in which learning-by-doing impacts are included, and the results indicate that the global learning-by-doing rate is significantly higher than the domestic rate. The analysis also indicates that empirically it is difficult to separate the impacts of R&D and learning-by-doing on cost reductions, respectively.Godkänd; 2008; 20081023 (kris_e