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Title: Developing infant technologies in mature industries : a case study on renewable energy
Author: Odam, Neil
Awarding Body: University of Stirling
Current Institution: University of Stirling
Date of Award: 2011
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The purpose of this thesis is to investigate the development of new technologies in the energy industry and to explore how it is possible for these technologies to compete with incumbent technologies in a mature market. The pursuit of renewable energy has been at the forefront of national government and international institutional policy in recent years due to the desire to improve the security of energy supply and to reduce CO2e emissions. This thesis aims to contribute to this policy debate, particularly by focussing on the issue of governmental support for infant energy technologies. In order to conduct this investigation, two main topics have been analysed. Firstly, learning curves have been studied to establish whether support for new technologies can be justified by the potential cost reductions which arise from learning-by-doing. This research evolved into the investigation of econometric issues which affect learning curves. Patent counts are used to demonstrate an alternative output-based measurement of industry wide knowledge stock, which is used as a proxy for innovation. This alternative specification of knowledge stock corroborates recent findings in the literature, that learning curves which model cost using only cumulative capacity leads to the over-estimation of cost reductions from learning-by-doing and the failure to capture cost reductions resulting from innovation. This suggests that government support for infant technologies should form a dual strategy of incentivising the deployment of generators as well as encouraging innovation, instead of using feed-in tariffs or renewable obligations which narrowly focus on increasing deployment. A great deal of progress has been made in identifying further econometric problems affecting learning curves in recent years. In the progress of this study, it was identified that cumulative capacity, the cost of wind power and knowledge stock are all non-stationary time series variables. The hypothesis that these variables are cointegrated was rejected by the Westerlund test, which implies that learning curves produce spurious results. This has major consequences for government policy as it suggests that learning curves should not be used to justify support for infant technologies. Secondly, a choice experiment was conducted to determine Scottish households’ willingness to pay for electricity generated from renewable sources compared to conventional sources such as coal, oil and gas. A labelled choice experiment was used to determine whether households have preferences between onshore wind power, offshore wind power and wave power. The results of a latent class model reveal that the majority of households (76.5%) are willing to pay an additional £89-£196 per year to obtain electricity from renewable resources instead of conventional sources. However, there is no statistically significant difference in the willingness to pay between the renewable technologies included in the choice experiment. The latent class model also illustrated that there is a sizeable minority (23.5%) who are opposed to renewable energy development. Older respondents and those less concerned about CO2 emissions are significantly more likely to form part of this group at the 5% level of significance. The study also included a unique addition by identifying households which purchased a house in the previous seven years. Interacting the actual transaction prices of these houses in a multinomial logit model suggested that households may be concerned about renewable energy developments devaluing their properties or the additional expense required to power larger houses. Due to the increasing difficulty of conducting choice experiments in the UK, a novel method of eliciting choice experiment responses from online advertising was tested and was found to be a cost-effective method of eliciting choice experiment responses. Overall, the research indicates that caution should be exercised when interpreting the results of a choice experiment which elicits responses using Internet advertising. It can be observed that the pseudo R2 of the Internet-based sample is lower than the mail-based sample and that the mean respondent to the Internet-based choice experiment is willing to pay significantly more for renewable electricity than the mean respondent to the mail-based choice experiment at the 5% level of significance. Furthermore, the mean willingness to pay estimate in the Internet-based choice experiment appears to be unrealistically high. Further research investigating the elasticity of survey responses to the prize fund on offer would be valuable in identifying the most cost-effective strategy to obtain responses and to generate a more representative sample.
Supervisor: Hanley, Nick; de Vries, Frans Sponsor: ESRC ; MASTS
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Energy economics ; Wave power ; Learning curves ; Choice experiment ; Wind power ; Environmental economics. ; Renewable energy sources.