Abstract
In order to reduce future dependence on foreign oil and emissions of CO2, how much would US households be willing to pay annually to support increased energy research and development (R&D) activities designed to replace fossil fuels? Does it matter whether the R&D includes nuclear energy options? We explore these questions using data from a unique set of national telephone and Internet surveys. Using a national advisory referendum format, the contingent valuation method is applied to estimate annual household willingness-to-pay (WTP) for US household support of a national Energy Research and Development Fund (ERDF) for investments in energy sources not reliant on fossil fuels. While accounting for the level of (un)certainty in voting responses, the WTP modeling includes a comparison of both classic maximum likelihood estimation (MLE) and Bayesian analysis. Evidence indicates that MLE and Bayesian analysis achieve similar statistical inference, while the Bayesian analysis provides a narrower confidence interval around estimated WTP.
| Original language | English |
|---|---|
| Pages (from-to) | 731-742 |
| Number of pages | 12 |
| Journal | Ecological Economics |
| Volume | 68 |
| Issue number | 3 |
| Early online date | 14 Jul 2008 |
| DOIs | |
| Publication status | Published - 15 Jan 2009 |
Bibliographical note
Acknowledgments:This research was undertaken with funding provided by the Sandia National Laboratories. Special thanks to John Taylor. This paper has benefited from discussions with participants at Midwest Economics Association meeting in 2007. The authors thank Kishore Gawande, John Stoll, Carol Tallarico and three anonymous reviewers for their detailed and valuable comments. The authors are solely responsible for all errors and omissions.
Keywords
- Uncertainty
- Bayesian
- Research and development (R&D)
- Renewable energy
- Contingent valuation
- Nuclear energy
ASJC Scopus subject areas
- General Environmental Science
- Economics and Econometrics
