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Quantifying the social costs of nuclear energy: Perceived risk of accident at nuclear power plants

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  • Huhtala, Anni
  • Remes, Piia

Abstract

The preferences expressed in voting on nuclear reactor licenses and the risk perceptions of citizens provide insights into social costs of nuclear power and decision making in energy policy. We show analytically that these costs consist of disutility caused by unnecessary anxiety - due to misperceived risks relating to existing reactors - and where licenses for new nuclear reactors are not granted, delayed or totally lost energy production. Empirical evidence is derived from Finnish surveys eliciting explicitly the importance of risk perceptions on preferences regarding nuclear power and its environmental and economic impacts. We show that the estimated marginal impact of a high perceived risk of nuclear accident is statistically significant and that such a perception considerably decreases the probability of a person supporting nuclear power. This result holds across a number of robustness checks including an instrumental variable estimation and a model validation by observed voting behavior of the members of Parliament. The public's risk perceptions translate into a significant social cost, and are likely to affect the revenues, costs and financing conditions in the nuclear power sector in the future.

Suggested Citation

  • Huhtala, Anni & Remes, Piia, 2017. "Quantifying the social costs of nuclear energy: Perceived risk of accident at nuclear power plants," Energy Policy, Elsevier, vol. 105(C), pages 320-331.
  • Handle: RePEc:eee:enepol:v:105:y:2017:i:c:p:320-331
    DOI: 10.1016/j.enpol.2017.02.052
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    2. Groh, Elke D. & Möllendorff, Charlotte v., 2020. "What shapes the support of renewable energy expansion? Public attitudes between policy goals and risk, time, and social preferences," Energy Policy, Elsevier, vol. 137(C).
    3. Bieber, Niclas & Ker, Jen Ho & Wang, Xiaonan & Triantafyllidis, Charalampos & van Dam, Koen H. & Koppelaar, Rembrandt H.E.M. & Shah, Nilay, 2018. "Sustainable planning of the energy-water-food nexus using decision making tools," Energy Policy, Elsevier, vol. 113(C), pages 584-607.
    4. Joel Rasmussen & Jens Ewald, 2022. "The Relation Between Socioeconomic Status and Risk Attitudes: A Nuclear Accident Scenario in Sweden," Economics of Disasters and Climate Change, Springer, vol. 6(3), pages 541-555, November.
    5. André D. Thess & Philipp Lengsfeld, 2022. "Side Effects of Wind Energy: Review of Three Topics—Status and Open Questions," Sustainability, MDPI, vol. 14(23), pages 1-17, December.
    6. Ding, Xiaowen & Tian, Wei & Chen, Qingwei & Wei, Guoliang, 2019. "Policies on water resources assessment of coastal nuclear power plants in China," Energy Policy, Elsevier, vol. 128(C), pages 170-178.
    7. Hu, Xiaoli & Zhu, Weiwei & Wei, Jiuchang, 2021. "Effects of information strategies on public acceptance of nuclear energy," Energy, Elsevier, vol. 231(C).
    8. Lappi, Pauli & Lintunen, Jussi, 2021. "From cradle to grave? On optimal nuclear waste disposal," Energy Economics, Elsevier, vol. 103(C).
    9. Jang, Yeonju & Park, Eunil, 2020. "Social acceptance of nuclear power plants in Korea: The role of public perceptions following the Fukushima accident," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    10. Wang, Shanyong & Wang, Jing & Lin, Shoufu & Li, Jun, 2020. "How and when does information publicity affect public acceptance of nuclear energy?," Energy, Elsevier, vol. 198(C).

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    More about this item

    Keywords

    Economics; Vote; Nuclear accident; Subjective risks; Probabilities; Instrumental variable;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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