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Latent Thresholds Analysis of Choice Data under Value Uncertainty

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  • Mimako Kobayashi
  • Klaus Moeltner
  • Kimberly Rollins

Abstract

In many non-market valuation settings stakeholders will be uncertain as to their exact willingness-to-pay for a proposed environmental amenity. It then makes sense for the analyst to treat this value as a random variable with distribution only known to the respondent. In stated preference settings, researchers have used elicitation formats with multiple bids and uncertain-response options to learn about individual value distributions. Past efforts have focused on inference involving the expectation of individual densities. This requires stringent and likely unrealistic assumptions regarding the shape or moments of individual value distributions. We propose a Latent Thresholds Estimator that focuses instead on the range, i.e. minimum and maximum willingness-to-pay of individual respondents. The estimator efficiently exploits correlation patterns in individual responses and does not require any restrictive assumptions on underlying values. It also nests some of the existing approaches, which are not statistically supported for our empirical application. Copyright 2012, Oxford University Press.

Suggested Citation

  • Mimako Kobayashi & Klaus Moeltner & Kimberly Rollins, 2012. "Latent Thresholds Analysis of Choice Data under Value Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 189-208.
  • Handle: RePEc:oup:ajagec:v:94:y:2012:i:1:p:189-208
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    File URL: http://hdl.handle.net/10.1093/ajae/aar129
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    Citations

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    Cited by:

    1. Jed Cohen, Klaus Moeltner, Johannes Reichl and Michael Schmidthaler, 2016. "An Empirical Analysis of Local Opposition to New Transmission Lines Across the EU-27," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    2. Bethany Cooper & Michael Burton & Lin Crase, 2019. "Willingness to Pay to Avoid Water Restrictions in Australia Under a Changing Climate," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(3), pages 823-847, March.
    3. Pierre-Alexandre Mahieu & François-Charles Wolff & Jason Shogren & Pascal Gastineau, 2017. "Interval bidding in a distribution elicitation format," Applied Economics, Taylor & Francis Journals, vol. 49(51), pages 5200-5211, November.
    4. Riccardo Scarpa & Claudia Bazzani & Diego Begalli & Roberta Capitello, 2021. "Resolvable and Near‐epistemic Uncertainty in Stated Preference for Olive Oil: An Empirical Exploration," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(2), pages 335-369, June.
    5. Dekker, Thijs & Hess, Stephane & Brouwer, Roy & Hofkes, Marjan, 2016. "Decision uncertainty in multi-attribute stated preference studies," Resource and Energy Economics, Elsevier, vol. 43(C), pages 57-73.

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