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Drivers of People's Preferences for Spatial Proximity to Energy Infrastructure Technologies: A Cross-country Analysis

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  • Jason Harold, Valentin Bertsch, Thomas Lawrence, and Magie Hall

Abstract

Many countries plan to decarbonise their energy systems by increasing energy efficiency and expanding the use of renewable energy sources (RES). Such actions require significant investments in new energy infrastructures. While people are generally accepting of these infrastructures, opposition sometimes arises when these developments are sited at close proximity to people's residences. Therefore, it is important to understand what actually drives people's preferences for spatial proximity to different energy infrastructure technologies. This study examines the factors influencing people's proximity preferences to a range of different energy technologies using a cross-country econometric analysis of the stated preference data from an unprecedented survey conducted on nationally representative samples of the population in Ireland, the U.S. and Germany. The survey involved more than 4,500 participants in total. This paper presents the data and selected results from a generalised ordered logit model for each energy technology surveyed. These are; wind turbines, solar power technology, biomass power plant, coal-fired power plant and natural gas power plant. The results show that, in general, German and Irish citizens are willing to accept energy infrastructures at smaller distances to their homes than their U.S. counterparts. Moreover, attitudinal factors are found to shape people's preferences more consistently than any of the socio-demographic characteristics.

Suggested Citation

  • Jason Harold, Valentin Bertsch, Thomas Lawrence, and Magie Hall, 2021. "Drivers of People's Preferences for Spatial Proximity to Energy Infrastructure Technologies: A Cross-country Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    • Handle: RePEc:aen:journl:ej42-4-harol
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    Cited by:

    1. Bertsch, Valentin & Di Cosmo, Valeria, 2020. "Are renewables profitable in 2030 and do they reduce carbon emissions effectively? A comparison across Europe," MPRA Paper 101822, University Library of Munich, Germany.
    2. David Huckebrink & Valentin Bertsch, 2021. "Integrating Behavioural Aspects in Energy System Modelling—A Review," Energies, MDPI, vol. 14(15), pages 1-26, July.
    3. Alina Wilke & Zhiwei Shen & Matthias Ritter, 2021. "How Much Can Small-Scale Wind Energy Production Contribute to Energy Supply in Cities? A Case Study of Berlin," Energies, MDPI, vol. 14(17), pages 1-20, September.
    4. Bertsch, Valentin & Di Cosmo, Valeria, "undated". "Are Renewables Profitable in 2030? A Comparison between Wind and Solar across Europe," ESP: Energy Scenarios and Policy 276178, Fondazione Eni Enrico Mattei (FEEM).
    5. Vivien Fisch-Romito & Marc Jaxa-Rozen & Xin Wen & Evelina Trutnevyte, 2025. "Multi-country evidence on societal factors to include in energy transition modelling," Nature Energy, Nature, vol. 10(4), pages 460-469, April.
    6. Tong Koecklin, Manuel & Fitiwi, Desta & de Carolis, Joseph F. & Curtis, John, 2020. "Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland," Papers WP653, Economic and Social Research Institute (ESRI).
    7. Greaker, Mads & Hagem, Cathrine & Skulstad, Andreas, 2024. "Offsetting schemes and ecological taxes for wind power production," Ecological Economics, Elsevier, vol. 224(C).
    8. Longoria, Genaro & Lynch, Muireann & Farrell, Niall & Curtis, John, 2024. "The impact of extended decision times in planning and regulatory processes for energy infrastructure," Utilities Policy, Elsevier, vol. 91(C).
    9. Plaga, Leonie Sara & Lynch, Muireann & Curtis, John & Bertsch, Valentin, 2024. "How public acceptance affects power system development—A cross-country analysis for wind power," Applied Energy, Elsevier, vol. 359(C).
    10. Ladenburg, Jacob & Kim, Jiwon & Zuch, Matteo & Soytas, Ugur, 2024. "Taking the carbon capture and storage, wind power, PV or other renewable technology path to fight climate change? Exploring the acceptance of climate change mitigation technologies – A Danish national," Renewable Energy, Elsevier, vol. 220(C).

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    JEL classification:

    • F0 - International Economics - - General

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