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Article

Innovation Modelling and Multi-Factor Learning in Wind Energy Technology

Citation
Odam N & de Vries FP (2020) Innovation Modelling and Multi-Factor Learning in Wind Energy Technology. Energy Economics, 85, Art. No.: 104594. https://doi.org/10.1016/j.eneco.2019.104594

Abstract
Learning curves are frequently cited to justify the subsidization of new technologies to facilitate market competitiveness. The main literature has focused on improving the specification of the basic learning curve model by augmenting it to control for technological development measured by public R&D expenditures. In addition to employing R&D expenditures, the purpose of this paper is to assess the robustness of an augmented multi-factor learning curve model by estimating learning rates in a panel framework utilising patent data on relevant wind power technologies in Germany, Denmark, Spain and the UK. Results indicate that both innovation proxies are qualitatively identical and generate consistent learning estimates. The paper also aims at exploring the presence of unit roots in learning curves and alerts to the possibility of spurious estimations. Renewable energy policy guided by learning curve estimates should therefore be implemented with caution.

Keywords
Technical change; R&D; Learning curves; Renewables; Patents; Knowledge stock; Unit roots

Journal
Energy Economics: Volume 85

StatusPublished
Author(s)Odam, Neil; de Vries, Frans P
FundersEconomic and Social Research Council
Publication date01/01/2020
Publication date online21/11/2019
Date accepted by journal17/11/2019
URLhttp://hdl.handle.net/1893/30495
PublisherElsevier BV
ISSN0140-9883
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