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Embedding a Field Experiment in Contingent Valuation to Measure Context-Dependent Risk Preferences: Does Prospect Theory Explain Individual Responses for Wildfire Risk?

Author

Listed:
  • Kimberly Rollins

    () (Department of Resource Economics, University of Nevada, Reno)

  • Mimako Kobayashi

    () (Department of Resource Economics, University of Nevada, Reno)

Abstract

This paper contributes towards the development of an empirical approach applicable to contingent valuation to accommodate non-expected utility risk preferences. Combining elicitation approaches used in field experiments with contingent valuation, we embed an experimental design that systematically varies probabilities and losses across a survey sample in a willingness to pay elicitation format. We apply the proposed elicitation and estimation approaches to estimate the risk preferences of a representative homeowner who faces probabilistic wildfire risks and an investment option that reduces losses due to wildfire. Based on prospect theory, we estimate parameters of probability weighting, risk preferences and use individual characteristics as covariates for these parameters and as utility shifters. We find that risk preferences are consistent with prospect theory. We find that probability weighting may offer an explanation for respondents’ observed under investment in measures to reduce losses due to wildfire.

Suggested Citation

  • Kimberly Rollins & Mimako Kobayashi, 2010. "Embedding a Field Experiment in Contingent Valuation to Measure Context-Dependent Risk Preferences: Does Prospect Theory Explain Individual Responses for Wildfire Risk?," Working Papers 10-003, University of Nevada, Reno, Department of Economics;University of Nevada, Reno , Department of Resource Economics.
  • Handle: RePEc:unr:wpaper:10-003
    as

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    File URL: http://www.coba.unr.edu/econ/wp/papers/UNRECONWP10003.pdf
    File Function: First version, 2010
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    References listed on IDEAS

    as
    1. John Hey & Andrea Morone & Ulrich Schmidt, 2009. "Noise and bias in eliciting preferences," Journal of Risk and Uncertainty, Springer, vol. 39(3), pages 213-235, December.
    2. Wilcox, Nathaniel T., 2011. "'Stochastically more risk averse:' A contextual theory of stochastic discrete choice under risk," Journal of Econometrics, Elsevier, vol. 162(1), pages 89-104, May.
    3. Shaw, W. Douglass & Woodward, Richard T., 2008. "Why environmental and resource economists should care about non-expected utility models," Resource and Energy Economics, Elsevier, vol. 30(1), pages 66-89, January.
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    5. Shafran, Aric P., 2008. "Risk externalities and the problem of wildfire risk," Journal of Urban Economics, Elsevier, vol. 64(2), pages 488-495, September.
    6. Mariam Lankoande & Jonathan Yoder, 2006. "An Econometric Model of Wildfire Suppression Productivity," Working Papers 2006-10, School of Economic Sciences, Washington State University.
    7. Nathalie Etchart-Vincent, 2004. "Is Probability Weighting Sensitive to the Magnitude of Consequences? An Experimental Investigation on Losses," Journal of Risk and Uncertainty, Springer, vol. 28(3), pages 217-235, May.
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    12. Mary Riddel & W. Shaw, 2006. "A theoretically-consistent empirical model of non-expected utility: An application to nuclear-waste transport," Journal of Risk and Uncertainty, Springer, vol. 32(2), pages 131-150, March.
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    15. Kobayashi, Mimako & Zirogiannis, Nikolaos & Rollins, Kimberly S. & Evans, M.D.R., 2010. "Estimating Private Incentives for Wildfire Risk Mitigation: Determinants of Demands for Different Fire-Safe Actions," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61867, Agricultural and Applied Economics Association.
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    More about this item

    Keywords

    Prospect theory; Contingent valuation; Field experiment; Wildfire risk;

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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