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A Comparison of Willingness to Pay Estimation Techniques From Referendum Questions

  • Kelly Giraud
  • John Loomis
  • Joseph Cooper

Referendum style willingness to pay questions have been used to estimatepassive use values. This referendum question format method may beproblematic for many reasons, including the statistical techniques used toestimate willingness to pay from discrete responses. This paper comparesa number of parametric, semi-nonparametric and nonparametric estimationtechniques using data collected from US households regarding Federalprotection of endangered fish species.The advantages and disadvantagesof the various statistical models used are explored. A hypothesis test forstatistical equality among estimation techniques is performed using ajackknife bootstrapping method. When the equality test is applied, themodeling techniques do show significant differences in some possiblecomparisons, but only those that are nonparamentric. This can lead toconflicting interpretations of what the data show. Resource managers andpolicy analysts need to use caution when interpreting results until anindustry standard can be developed for estimating willingness to pay fromclosed ended questions. Copyright Kluwer Academic Publishers 2001

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File URL: http://hdl.handle.net/10.1023/A:1013025120987
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Article provided by European Association of Environmental and Resource Economists in its journal Environmental and Resource Economics.

Volume (Year): 20 (2001)
Issue (Month): 4 (December)
Pages: 331-346

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Handle: RePEc:kap:enreec:v:20:y:2001:i:4:p:331-346
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  1. Timothy Park & John B. Loomis & Michael Creel, 1991. "Confidence Intervals for Evaluating Benefits Estimates from Dichotomous Choice Contingent Valuation Studies," Land Economics, University of Wisconsin Press, vol. 67(1), pages 64-73.
  2. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-19, November.
  3. John W. Duffield & David A. Patterson, 1991. "Inference and Optimal Design for a Welfare Measure in Dichotomous Choice Contingent Valuation," Land Economics, University of Wisconsin Press, vol. 67(2), pages 225-239.
  4. Gallant, A. Ronald, 1982. "Unbiased determination of production technologies," Journal of Econometrics, Elsevier, vol. 20(2), pages 285-323, November.
  5. Chen, Heng Z. & Randall, Alan, 1997. "Semi-nonparametric estimation of binary response models with an application to natural resource valuation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 323-340.
  6. Cummings, Ronald G & Harrison, Glenn W & Rutstrom, E Elisabet, 1995. "Homegrown Values and Hypothetical Surveys: Is the Dichotomous Choice Approach Incentive-Compatible?," American Economic Review, American Economic Association, vol. 85(1), pages 260-66, March.
  7. Carson, Richard T. & Hanemann, W. Michael, 2006. "Contingent Valuation," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 2, chapter 17, pages 821-936 Elsevier.
  8. Flores, Nicholas E., 1996. "Reconsidering the Use of Hicks Neutrality to Recover Total Value," Journal of Environmental Economics and Management, Elsevier, vol. 31(1), pages 49-64, July.
  9. Haab, Timothy C. & McConnell, Kenneth E., 1997. "Referendum Models and Negative Willingness to Pay: Alternative Solutions," Journal of Environmental Economics and Management, Elsevier, vol. 32(2), pages 251-270, February.
  10. Peter A. Diamond & Jerry A. Hausman, 1994. "Contingent Valuation: Is Some Number Better than No Number?," Journal of Economic Perspectives, American Economic Association, vol. 8(4), pages 45-64, Fall.
  11. Bengt Kristrom, 1990. "A Non-Parametric Approach to the Estimation of Welfare Measures in Discrete Response Valuation Studies," Land Economics, University of Wisconsin Press, vol. 66(2), pages 135-139.
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