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'Scenario Adjustment' in Stated Preference Research

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  • Cameron, Trudy Ann
  • Deshazo, J.R.
  • Johnson, Erica H.

Abstract

To assess demand for non-market goods, researchers must sometimes resort to direct elicitation of consumer tradeoffs with the use of surveys. Stated preference (SP) methods typically involve surveys of consumers wherein choice scenarios are posed to respondents and individuals are asked to indicate their preferred alternatives. As SP research has matured, much progress has been made to address a variety of well-known biases that can afflict demand estimates produced by these methods, but some concerns still remain. We use an existing survey designed to ascertain willingness to pay for private health-risk reduction programs to illustrate yet another potential source of bias. This bias is caused when not all respondents answer exactly the choice question they are asked and that the researcher intended for respondents to answer. SP researchers are familiar with the problem of outright scenario rejection, where respondents may choose the status quo alternative because they reject the viability of the proposed alternatives. In contrast, we address the more subtle problem of scenario adjustment, where respondents impute that the substantive alternative(s) in a choice set, in their own particular case, will be different than the survey instrument suggests. We demonstrate a strategy to control and potentially correct for scenario adjustment in the estimation of willingness to pay.

Suggested Citation

  • Cameron, Trudy Ann & Deshazo, J.R. & Johnson, Erica H., 2007. "'Scenario Adjustment' in Stated Preference Research," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 9739, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea07:9739
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    File URL: http://purl.umn.edu/9739
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    References listed on IDEAS

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    1. 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 715-719, November.
    2. Hadrich, Joleen C. & Wolf, Christopher A. & Roy Black, J. & Harsh, Stephen B., 2008. "Incorporating Environmentally Compliant Manure Nutrient Disposal Costs into Least-Cost Livestock Ration Formulation," Journal of Agricultural and Applied Economics, Cambridge University Press, pages 287-300.
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    Cited by:

    1. Marsh, Dan & Mkwara, Lena Asimenye & Scarpa, Riccardo, 2010. "Does respondent’s perceived knowledge of the status quo affect attribute attendance and WTP in choice experiments? Evidence from the Karapiro Catchment Freshwater streams," 2010 Conference, August 26-27, 2010, Nelson, New Zealand 96809, New Zealand Agricultural and Resource Economics Society.
    2. Daniel Burghart & Trudy Cameron & Geoffrey Gerdes, 2007. "Valuing publicly sponsored research projects: Risks, scenario adjustments, and inattention," Journal of Risk and Uncertainty, Springer, vol. 35(1), pages 77-105, August.
    3. Trudy Cameron & J. DeShazo & Peter Stiffler, 2010. "Demand for health risk reductions: A cross-national comparison between the U.S. and Canada," Journal of Risk and Uncertainty, Springer, vol. 41(3), pages 245-273, December.

    More about this item

    Keywords

    value of a statistical life; value of a statistical illness profile; health risk reductions; stated preference; scenario rejection; scenario adjustment; Demand and Price Analysis; Q51;

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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