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Modeling Certainty-Adjusted Willingness to Pay for Ecosystem Service Improvement from Agriculture

Author

Listed:
  • Ma, Shan
  • Lupi, Frank
  • Swinton, Scott M.
  • Chen, Huilan

Abstract

The public demand for ecosystem services measured by willingness to pay (WTP) in contingent valuation studies provides important information for designing Payment-for-Ecosystem-Service (PES) programs. However, the hypothetical markets for contingent valuation and respondents’ unfamiliarity with certain ecosystem services may increase their preference uncertainty, which may increase variance and even cause bias in WTP estimates. Taking advantage of a unique stated preference data set that includes a follow-up question rating the respondent’s certainty level, this study evaluates alternative methods of modeling certainty-adjusted WTP for cleaner lakes and abated global warming. Results suggest that the incorporation of self-reported uncertainty into binary choice models significantly reduces the median WTP and appears to improve our understanding of the demand for ecosystem services.

Suggested Citation

  • Ma, Shan & Lupi, Frank & Swinton, Scott M. & Chen, Huilan, 2011. "Modeling Certainty-Adjusted Willingness to Pay for Ecosystem Service Improvement from Agriculture," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103734, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea11:103734
    DOI: 10.22004/ag.econ.103734
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    References listed on IDEAS

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    1. G. Cornelis van Kooten & Emina Krcmar & Erwin H. Bulte, 2001. "Preference Uncertainty in Non-Market Valuation: A Fuzzy Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 487-500.
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    Cited by:

    1. Catherine M. H. Keske & Adam Mayer, 2014. "Visitor Willingness to Pay U.S. Forest Service Recreation Fees in New West Rural Mountain Economies," Economic Development Quarterly, , vol. 28(1), pages 87-100, February.

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    Keywords

    Environmental Economics and Policy; Research Methods/ Statistical Methods; Risk and Uncertainty;
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