Abstract: We
estimate Arizona residents’ Willingness to Pay (WTP) to invest in a
solar energy research and development fund using data obtained from a
Dichotomous-Choice Contingent Valuation mail survey. We examine
differences in WTP estimates using different categorizations for
respondent uncertainty. We also employ both commonly used Maximum
Likelihood and less frequently applied Bayesian estimation techniques.
We find that respondent uncertainty has an economically significant
impact on WTP estimates, while WTP estimates are robust to different
estimation techniques. Our robust specification with strict uncertainty
coding indicates the average Arizona household is WTP approximately $17
per month to invest in research and development in solar energy.
Highlights
►
We estimate Willingness to Pay using Bayesian and Maximum Likelihood.
► Willingness to Pay estimates are robust to estimation techniques.
► Arizona residents are willing to pay $17 to invest in R&D in solar energy.
► Willingness to Pay estimates are robust to estimation techniques.
► Arizona residents are willing to pay $17 to invest in R&D in solar energy.
- Fig. 3. WTP draws for Bayesian models 10–12.
- by Julie M. Mueller, The W.A. Franke College of Business, Northern Arizona University, PO Box 15066, Flagstaff, AZ 86011,United States; Tel.: +1 928 523 6612; fax: +1 928 523 7331
- Energy Policy via Elsevier Science Direct www.ScienceDirect.com
- Volume 53; February, 2013; Pages 462–476
- Keywords: Contingent valuation; Bayesian estimation; Solar energy
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