Technology learning in the presence of public R&D : the case of European wind power

By Kristina Ek, Patrik Söderholm. 2010

119 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/26c5eabd9bfec6e01f4ff81308a1254186f47973

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In Economics and Econometrics

Citations in the corpus

Future capacity growth of energy technologies: are scenarios consistent with historical evidence? (2013, background): “R&D investments can also reduce a technology’s future cost and its availability for widespread diffusion (Ek and Soderholm 2010).”
Up-scaling, formative phases, and learning in the historical diffusion of energy technologies (2012, background): “Two-factor experience curves, for example, explicitly represent the influence of cumulative R&D expenditure and the resulting R&D-based knowledge stock on unit cost reductions (Söderholm and Klaassen, 2007; Ek and Soderholm, 2010).”
Expert elicitation survey on future wind energy costs (2016, background): “│2 costs [13-14], and for simplifying the many causal mechanisms that lead to cost reduction [14-19].”
The experience curve theory and its application in the field of electricity generation technologies – A literature review (2018, background): “If learning is assumed to be mostly industry-wide and global in nature, as in the case of PV module manufacture [55,56] and wind turbine manufacture [14,57], global data, or at least data from as many countries as possible, should preferably be considered.”
A review of learning rates for electricity supply technologies (2015, background): “…Global Turbine LBD¼9.73%, LBR¼10% 0.8 Investment cost ($/kW) Cumulative capacity (GW) and knowledge stock (cumulative R&D minus depreciation) Ek and Söderholm (2010) 1986–2002 Global Wind farm LBD¼17%, LBR¼20% 0.88 Investment Price ($/kW) R&D ($) and cumulative capacity (MW) Söderholm and…”