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Willingness to pay for emissions reduction: Application of choice modeling under uncertainty and different management options

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  • Williams, Galina
  • Rolfe, John

Abstract

This paper presents the results of a choice modeling survey of households in Queensland, Australia to assess values for reductions in national greenhouse emissions by 2020. The study is novel in two main ways. First, labeled alternatives were used to assess whether the types of management options for reducing net emissions (green power, energy efficient technologies or carbon capture) are significant in understanding preferences for reducing emissions. Second, the importance of the level and type of uncertainty involved in reductions is tested. The types of uncertainty include (1) the uncertainty of achieving emissions reduction and (2) the uncertainty of international participation as the percentage of total global emissions covered by international agreements. The results of this survey identified how choice responses vary when the level of uncertainty associated with emissions reduction options is included within choice alternatives.

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  • Williams, Galina & Rolfe, John, 2017. "Willingness to pay for emissions reduction: Application of choice modeling under uncertainty and different management options," Energy Economics, Elsevier, vol. 62(C), pages 302-311.
    • Handle: RePEc:eee:eneeco:v:62:y:2017:i:c:p:302-311
    DOI: 10.1016/j.eneco.2017.01.004
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    Cited by:

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    2. Alberini, Anna & Ščasný, Milan & Bigano, Andrea, 2018. "Policy- v. individual heterogeneity in the benefits of climate change mitigation: Evidence from a stated-preference survey," Energy Policy, Elsevier, vol. 121(C), pages 565-575.
    3. Paul A. Hindsley & O. Ashton Morgan, 2020. "The Role of Cultural Worldviews in Willingness to Pay for Environmental Policy," Working Papers 20-03, Department of Economics, Appalachian State University.
    4. Tensay Hadush Meles & Razack Lokina & Erica Louis Mtenga & Julieth Julius Tibanywana, 2023. "Stated Preferences with Survey Consequentiality and Outcome Uncertainty: A Split Sample Discrete Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 86(4), pages 717-754, December.
    5. Hangjian Wu & Emmanouil Mentzakis & Marije Schaafsma, 2022. "Exploring Different Assumptions about Outcome-Related Risk Perceptions in Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 531-572, March.
    6. Bujosa, Angel & Torres, Cati & Riera, Antoni, 2018. "Framing Decisions in Uncertain Scenarios: An Analysis of Tourist Preferences in the Face of Global Warming," Ecological Economics, Elsevier, vol. 148(C), pages 36-42.
    7. Imran Ali & Mohammad Naushad, 2023. "Determinants of Green Energy Technology Purchase Intention: An Analytical Study," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 375-382, July.
    8. Ossokina, Ioulia V. & Kerperien, Stephan & Arentze, Theo A., 2021. "Does information encourage or discourage tenants to accept energy retrofitting of homes?," Energy Economics, Elsevier, vol. 103(C).
    9. 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).
    10. Galina Williams, 2023. "Temporal Stability of Attitudes towards Climate Change and Willingness to Pay for the Emissions Reduction Options in Queensland, Australia," Energies, MDPI, vol. 16(9), pages 1-22, May.

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    More about this item

    Keywords

    Choice modeling; Greenhouse gas emissions reduction; Uncertainty; Willingness to pay;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles

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