IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v131y2024ics0140988324000987.html
   My bibliography  Save this article

Household's willingness to pay for renewable electricity: A meta-analysis

Author

Listed:
  • Wang, Yushi
  • Wu, Libo
  • Zhou, Yang

Abstract

Increasing the penetration of renewable electricity is a key solution to achieving the climate target. Demand-side payment is one crucial financial source to support the development of renewable electricity by influencing the cost-benefit tradeoff, which is usually measured by the willingness to pay. However, the willingness to pay estimation is mostly based on survey and hence incomparable due to different questions asked, assumptions made, and methods used. This paper reviewed 244 results from 134 empirical studies in 28 countries and applied a meta-regression to analyze how such features affect households' willingness to pay. We find that the willingness to pay turns scope-insensitive once the change in the penetration rate of renewables reaches the threshold (12%). Studies using contingent valuation methods yield higher estimation results compared with the other methods. Based on these results, we further calibrated previous willingness to pay results and provided a comparable worldwide dataset.

Suggested Citation

  • Wang, Yushi & Wu, Libo & Zhou, Yang, 2024. "Household's willingness to pay for renewable electricity: A meta-analysis," Energy Economics, Elsevier, vol. 131(C).
  • Handle: RePEc:eee:eneeco:v:131:y:2024:i:c:s0140988324000987
    DOI: 10.1016/j.eneco.2024.107390
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324000987
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.107390?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pazheri, F.R. & Othman, M.F. & Malik, N.H., 2014. "A review on global renewable electricity scenario," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 835-845.
    2. Simona Bigerna & Paolo Polinori, 2015. "Assessing the Determinants of Renewable Electricity Acceptance Integrating Meta-Analysis Regression and a Local Comprehensive Survey," Sustainability, MDPI, vol. 7(9), pages 1-24, August.
    3. Craig D. Broadbent, 2014. "Evaluating mitigation and calibration techniques for hypothetical bias in choice experiments," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 57(12), pages 1831-1848, December.
    4. Koundouri, Phoebe & Kountouris, Yiannis & Remoundou, Kyriaki, 2009. "Valuing a wind farm construction: A contingent valuation study in Greece," Energy Policy, Elsevier, vol. 37(5), pages 1939-1944, May.
    5. Edward Balistreri & Gary McClelland & Gregory Poe & William Schulze, 2001. "Can Hypothetical Questions Reveal True Values? A Laboratory Comparison of Dichotomous Choice and Open-Ended Contingent Values with Auction Values," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 18(3), pages 275-292, March.
    6. Garces-Voisenat, Juan-Pedro & Mukherjee, Zinnia, 2016. "Paying for green energy: The case of the Chilean Patagonia," Journal of Policy Modeling, Elsevier, vol. 38(2), pages 397-414.
    7. Mikołaj Czajkowski & Nick Hanley, 2009. "Using Labels to Investigate Scope Effects in Stated Preference Methods," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 44(4), pages 521-535, December.
    8. Diamond, Peter, 1996. "Testing the Internal Consistency of Contingent Valuation Surveys," Journal of Environmental Economics and Management, Elsevier, vol. 30(3), pages 337-347, May.
    9. Matthew J. Kotchen, 2006. "Green Markets and Private Provision of Public Goods," Journal of Political Economy, University of Chicago Press, vol. 114(4), pages 816-845, August.
    10. Emma J. Frew & David K. Whynes & Jane L. Wolstenholme, 2003. "Eliciting Willingness to Pay: Comparing Closed-Ended with Open-Ended and Payment Scale Formats," Medical Decision Making, , vol. 23(2), pages 150-159, March.
    11. Gianluca Grilli, 2017. "Renewable energy and willingness to pay: Evidences from a meta-analysis," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2017(1-2), pages 253-271.
    12. Borchers, Allison M. & Duke, Joshua M. & Parsons, George R., 2007. "Does willingness to pay for green energy differ by source?," Energy Policy, Elsevier, vol. 35(6), pages 3327-3334, June.
    13. Aldy, Joseph Edgar & Leiserowitz, Anthony A & Kotchen, Matthew J, 2012. "Willingness to Pay and Political Support for a U.S. National Clean Energy Standard," Scholarly Articles 8832942, Harvard Kennedy School of Government.
    14. Oerlemans, Leon A.G. & Chan, Kai-Ying & Volschenk, Jako, 2016. "Willingness to pay for green electricity: A review of the contingent valuation literature and its sources of error," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 875-885.
    15. Borriello, Antonio & Burke, Paul F. & Rose, John M., 2021. "If one goes up, another must come down: A latent class hybrid choice modelling approach for understanding electricity mix preferences among renewables and non-renewables," Energy Policy, Elsevier, vol. 159(C).
    16. Boxall, Peter C. & Adamowicz, Wiktor L. & Swait, Joffre & Williams, Michael & Louviere, Jordan, 1996. "A comparison of stated preference methods for environmental valuation," Ecological Economics, Elsevier, vol. 18(3), pages 243-253, September.
    17. Carlo Andrea Bollino, 2009. "The Willingness to Pay for Renewable Energy Sources: The Case of Italy with Socio-demographic Determinants," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 81-96.
    18. Katherine Silz Carson & Susan M. Chilton & W. George Hutchinson & Riccardo Scarpa, 2020. "Public resource allocation, strategic behavior, and status quo bias in choice experiments," Public Choice, Springer, vol. 185(1), pages 1-19, October.
    19. Chaikumbung, Mayula, 2021. "Institutions and consumer preferences for renewable energy: A meta-regression analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    20. Richard C. Ready & Patricia A. Champ & Jennifer L. Lawton, 2010. "Using Respondent Uncertainty to Mitigate Hypothetical Bias in a Stated Choice Experiment," Land Economics, University of Wisconsin Press, vol. 86(2), pages 363-381.
    21. Ma, Chunbo & Rogers, Abbie A. & Kragt, Marit E. & Zhang, Fan & Polyakov, Maksym & Gibson, Fiona & Chalak, Morteza & Pandit, Ram & Tapsuwan, Sorada, 2015. "Consumers’ willingness to pay for renewable energy: A meta-regression analysis," Resource and Energy Economics, Elsevier, vol. 42(C), pages 93-109.
    22. Xie, Bai-Chen & Zhao, Wei, 2018. "Willingness to pay for green electricity in Tianjin, China: Based on the contingent valuation method," Energy Policy, Elsevier, vol. 114(C), pages 98-107.
    23. Nick Hanley & Robert Wright & Vic Adamowicz, 1998. "Using Choice Experiments to Value the Environment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 11(3), pages 413-428, April.
    24. Bente Halvorsen & Kjartan Sœlensminde, 1998. "Differences between Willingness-to-Pay Estimates from Open-Ended and Discrete-Choice Contingent Valuation Methods: The Effects of Heteroscedasticity," Land Economics, University of Wisconsin Press, vol. 74(2), pages 262-282.
    25. Joseph E. Aldy & Matthew J. Kotchen & Anthony A. Leiserowitz, 2012. "Willingness to pay and political support for a US national clean energy standard," Nature Climate Change, Nature, vol. 2(8), pages 596-599, August.
    26. Kahneman, Daniel & Knetsch, Jack L., 1992. "Valuing public goods: The purchase of moral satisfaction," Journal of Environmental Economics and Management, Elsevier, vol. 22(1), pages 57-70, January.
    27. Zhao, Xiaoli & Cai, Qiong & Li, Shujie & Ma, Chunbo, 2018. "Public preferences for biomass electricity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 242-253.
    28. Sundt, Swantje & Rehdanz, Katrin, 2015. "Consumers' willingness to pay for green electricity: A meta-analysis of the literature," Energy Economics, Elsevier, vol. 51(C), pages 1-8.
    29. Isabell Goldberg & Jutta Roosen, 2007. "Scope insensitivity in health risk reduction studies: A comparison of choice experiments and the contingent valuation method for valuing safer food," Journal of Risk and Uncertainty, Springer, vol. 34(2), pages 123-144, April.
    30. Akcura, Elcin, 2015. "Mandatory versus voluntary payment for green electricity," Ecological Economics, Elsevier, vol. 116(C), pages 84-94.
    31. Jorge Araña & Carmelo León, 2007. "Repeated Dichotomous Choice Formats for Elicitation of Willingness to Pay: Simultaneous Estimation and Anchoring Effect," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(4), pages 475-497, April.
    32. Mozumder, Pallab & Vásquez, William F. & Marathe, Achla, 2011. "Consumers' preference for renewable energy in the southwest USA," Energy Economics, Elsevier, vol. 33(6), pages 1119-1126.
    33. Cicia, Gianni & Cembalo, Luigi & Del Giudice, Teresa & Palladino, Andrea, 2012. "Fossil energy versus nuclear, wind, solar and agricultural biomass: Insights from an Italian national survey," Energy Policy, Elsevier, vol. 42(C), pages 59-66.
    34. Abdullah, Sabah & Jeanty, P. Wilner, 2011. "Willingness to pay for renewable energy: Evidence from a contingent valuation survey in Kenya," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2974-2983, August.
    35. Guo, Xiurui & Liu, Haifeng & Mao, Xianqiang & Jin, Jianjun & Chen, Dongsheng & Cheng, Shuiyuan, 2014. "Willingness to pay for renewable electricity: A contingent valuation study in Beijing, China," Energy Policy, Elsevier, vol. 68(C), pages 340-347.
    36. Chan, Kai-Ying & Oerlemans, Leon A.G. & Volschenk, Jako, 2015. "On the construct validity of measures of willingness to pay for green electricity: Evidence from a South African case," Applied Energy, Elsevier, vol. 160(C), pages 321-328.
    37. Nkansah, Kofi & Collins, Alan R, 2019. "Willingness to Pay for Wind versus Natural Gas Generation of Electricity," Agricultural and Resource Economics Review, Cambridge University Press, vol. 48(1), pages 44-70, April.
    38. John Loomis, 2011. "What'S To Know About Hypothetical Bias In Stated Preference Valuation Studies?," Journal of Economic Surveys, Wiley Blackwell, vol. 25(2), pages 363-370, April.
    39. Soon, Jan-Jan & Ahmad, Siti-Aznor, 2015. "Willingly or grudgingly? A meta-analysis on the willingness-to-pay for renewable energy use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 877-887.
    40. Aravena, Claudia & Hutchinson, W. George & Longo, Alberto, 2012. "Environmental pricing of externalities from different sources of electricity generation in Chile," Energy Economics, Elsevier, vol. 34(4), pages 1214-1225.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Oerlemans, Leon A.G. & Chan, Kai-Ying & Volschenk, Jako, 2016. "Willingness to pay for green electricity: A review of the contingent valuation literature and its sources of error," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 875-885.
    2. Dalia Streimikiene & Tomas Balezentis & Ilona Alisauskaite-Seskiene & Gintare Stankuniene & Zaneta Simanaviciene, 2019. "A Review of Willingness to Pay Studies for Climate Change Mitigation in the Energy Sector," Energies, MDPI, vol. 12(8), pages 1-38, April.
    3. Gianluca Grilli, 2017. "Renewable energy and willingness to pay: Evidences from a meta-analysis," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2017(1-2), pages 253-271.
    4. Bakkensen, Laura & Schuler, Paul, 2020. "A preference for power: Willingness to pay for energy reliability versus fuel type in Vietnam," Energy Policy, Elsevier, vol. 144(C).
    5. Soon, Jan-Jan & Ahmad, Siti-Aznor, 2015. "Willingly or grudgingly? A meta-analysis on the willingness-to-pay for renewable energy use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 877-887.
    6. Balezentis, Tomas & Streimikiene, Dalia & Mikalauskas, Ignas & Shen, Zhiyang, 2021. "Towards carbon free economy and electricity: The puzzle of energy costs, sustainability and security based on willingness to pay," Energy, Elsevier, vol. 214(C).
    7. Martínez-Cruz, Adán L. & Núñez, Héctor M., 2021. "Tension in Mexico's energy transition: Are urban residential consumers in Aguascalientes willing to pay for renewable energy and green jobs?," Energy Policy, Elsevier, vol. 150(C).
    8. Sundt, Swantje & Rehdanz, Katrin, 2015. "Consumers' willingness to pay for green electricity: A meta-analysis of the literature," Energy Economics, Elsevier, vol. 51(C), pages 1-8.
    9. Cerdá, Emilio & López-Otero, Xiral & Quiroga, Sonia & Soliño, Mario, 2024. "Willingness to pay for renewables: Insights from a meta-analysis of choice experiments," Energy Economics, Elsevier, vol. 130(C).
    10. Ayodele, T.R. & Ogunjuyigbe, A.S.O. & Ajayi, O.D. & Yusuff, A.A. & Mosetlhe, T.C., 2021. "Willingness to pay for green electricity derived from renewable energy sources in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    11. Herbes, Carsten & Friege, Christian & Baldo, Davide & Mueller, Kai-Markus, 2015. "Willingness to pay lip service? Applying a neuroscience-based method to WTP for green electricity," Energy Policy, Elsevier, vol. 87(C), pages 562-572.
    12. Bae, Jeong Hwan & Rishi, Meenakshi & Li, Dmitriy, 2021. "Consumer preferences for a green certificate program in South Korea," Energy, Elsevier, vol. 230(C).
    13. Will, Christian & Lehmann, Nico & Baumgartner, Nora & Feurer, Sven & Jochem, Patrick & Fichtner, Wolf, 2022. "Consumer understanding and evaluation of carbon-neutral electric vehicle charging services," Applied Energy, Elsevier, vol. 313(C).
    14. Lehmann, Nico & Sloot, Daniel & Schüle, Christopher & Ardone, Armin & Fichtner, Wolf, 2023. "The motivational drivers behind consumer preferences for regional electricity – Results of a choice experiment in Southern Germany," Energy Economics, Elsevier, vol. 120(C).
    15. Yu, Ying & Yamaguchi, Kensuke & Thuy, Truong Dang & Kittner, Noah, 2022. "Will the public in emerging economies support renewable energy? Evidence from Ho Chi Minh City, Vietnam," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    16. Alló, Maria & Loureiro, Maria L., 2014. "The role of social norms on preferences towards climate change policies: A meta-analysis," Energy Policy, Elsevier, vol. 73(C), pages 563-574.
    17. Kim, Hyunggeun & Park, Sangkyu & Lee, Jongsu, 2021. "Is renewable energy acceptable with power grid expansion? A quantitative study of South Korea's renewable energy acceptance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    18. Cardella, Eric & Ewing, Brad & Williams, Ryan Blake, 2018. "Green is Good – The Impact of Information Nudges on the Adoption of Voluntary Green Power Plans," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266583, Southern Agricultural Economics Association.
    19. Chan, Kai-Ying & Oerlemans, Leon A.G. & Volschenk, Jako, 2015. "On the construct validity of measures of willingness to pay for green electricity: Evidence from a South African case," Applied Energy, Elsevier, vol. 160(C), pages 321-328.
    20. Anna Kowalska-Pyzalska, 2019. "Do Consumers Want to Pay for Green Electricity? A Case Study from Poland," Sustainability, MDPI, vol. 11(5), pages 1-20, March.

    More about this item

    Keywords

    Renewable energy; Willingness to pay; Meta-analysis;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:131:y:2024:i:c:s0140988324000987. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.