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The Effects of Expert Selection, Elicitation Design, and R&D Assumptions on Experts’ Estimates of the Future Costs of Photovoltaics

Author

Listed:
  • Elena Verdolini

    (Fondazione Eni Enrico Mattei and Centro Euro-Mediterraneo sui Cambiamenti Climatici)

  • Laura Diaz Anadon

    (John F. Kennedy School of Government, Harvard University)

  • Jiaqi Lu

    (La Follette School of Public Affairs, University of Wisconsin-Madison, USA)

  • Gregory F. Nemet

    (La Follette School of Public Affairs and Nelson Institute Center for Sustainability and the Global Environment (SAGE), University of Wisconsin-Madison, USA)

Abstract

Expert elicitations of future energy technology costs can improve energy policy design by explicitly characterizing uncertainty. However, the recent proliferation of expert elicitation studies raises questions about the reliability and comparability of the results. In this paper, we standardize disparate expert elicitation data from five EU and US studies, involving 65 experts, of the future costs of photovoltaics (PV) and evaluate the impact of expert and study characteristics on the elicited metrics. The results for PV suggest that in-person elicitations are associated with more optimistic 2030 PV cost estimates and in some models with a larger range of uncertainty than online elicitations. Unlike in previous results on nuclear power, expert affiliation type and nationality do not affect central estimates. Some specifications suggest that EU experts are more optimistic about breakthroughs, but they are also less confident in that they provide larger ranges of estimates than do US experts. Higher R&D investment is associated with lower future costs. Rather than increasing confidence, high R&D increases uncertainty about future costs, mainly because it improves the base case (low cost) outcomes more than it improves the worst case (high cost) outcomes.

Suggested Citation

  • Elena Verdolini & Laura Diaz Anadon & Jiaqi Lu & Gregory F. Nemet, 2015. "The Effects of Expert Selection, Elicitation Design, and R&D Assumptions on Experts’ Estimates of the Future Costs of Photovoltaics," Working Papers 2015.01, Fondazione Eni Enrico Mattei.
    • Handle: RePEc:fem:femwpa:2015.01
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    References listed on IDEAS

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    Cited by:

    1. Ma, Rufei & Cai, Huan & Ji, Qiang & Zhai, Pengxiang, 2021. "The impact of feed-in tariff degression on R&D investment in renewable energy: The case of the solar PV industry," Energy Policy, Elsevier, vol. 151(C).
    2. Gregory F. Nemet & Laura Diaz Anadon & Elena Verdolini, 2017. "Quantifying the Effects of Expert Selection and Elicitation Design on Experts’ Confidence in Their Judgments About Future Energy Technologies," Risk Analysis, John Wiley & Sons, vol. 37(2), pages 315-330, February.
    3. Laura Diaz Anadon & Erin Baker & Valentina Bosetti & Lara Aleluia Reis, 2016. "Expert views - and disagreements - about the potential of energy technology R&D," Climatic Change, Springer, vol. 136(3), pages 677-691, June.
    4. Elena Verdolini & Laura Díaz Anadón & Erin Baker & Valentina Bosetti & Lara Aleluia Reis, 2018. "Future Prospects for Energy Technologies: Insights from Expert Elicitations," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 133-153.
    5. Martins, Florinda, 2017. "PV sector in the European Union countries – Clusters and efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 173-177.
    6. Feldman, David & Jones-Albertus, Rebecca & Margolis, Robert, 2020. "Quantifying the impact of R&D on PV project financing costs," Energy Policy, Elsevier, vol. 142(C).
    7. Levi, Peter G. & Pollitt, Michael G., 2015. "Cost trajectories of low carbon electricity generation technologies in the UK: A study of cost uncertainty," Energy Policy, Elsevier, vol. 87(C), pages 48-59.
    8. Benjamin K. Sovacool & Chad M. Baum & Sean Low, 2022. "Determining our climate policy future: expert opinions about negative emissions and solar radiation management pathways," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(8), pages 1-50, December.
    9. Zhou, Fan & Page, Lionel & Perrons, Robert K. & Zheng, Zuduo & Washington, Simon, 2019. "Long-term forecasts for energy commodities price: What the experts think," Energy Economics, Elsevier, vol. 84(C).
    10. Martínez-Cruz, Adán L. & Juárez-Torres, Miriam & Guerrero, Santiago, 2017. "Assessing Impacts From Climate Change on Local Social-ecological Systems in Contexts Where Information is Lacking: An Expert Elicitation in the Bolivian Altiplano," Ecological Economics, Elsevier, vol. 137(C), pages 70-82.
    11. Sakti, Apurba & Azevedo, Inês M.L. & Fuchs, Erica R.H. & Michalek, Jeremy J. & Gallagher, Kevin G. & Whitacre, Jay F., 2017. "Consistency and robustness of forecasting for emerging technologies: The case of Li-ion batteries for electric vehicles," Energy Policy, Elsevier, vol. 106(C), pages 415-426.

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    More about this item

    Keywords

    Photovoltaic Costs; Energy R&D; Expert Elicitation; Survey Design; Heuristics;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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