Scenario Adjustment in Stated Preference Research
AbstractStated preference (SP) survey methods have been used increasingly to assess willingness to pay for a wide variety of non-market goods and services, including reductions in risks to life and health. Poorly designed SP studies are subject to a number of well-known biases, but many of these biases can be minimized when they are anticipated ex ante and accommodated in the studyâ€™s design or during data analysis. We identify another source of potential bias, which we call â€œscenario adjustment,â€ where respondents assume that the substantive alternative(s) in an SP choice set, in their own particular case, will be different than the survey instrument describes. We use an existing survey, developed to ascertain willingness to pay for private health-risk reduction programs, to demonstrate a strategy to control and correct for scenario adjustment in the estimation of willingness to pay. This strategy involves data from carefully worded follow-up questions and ex post econometric controls for each respondentâ€™s subjective departures from the intended choice scenario. Our research has important implications for the design of future SP surveys.
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Bibliographic InfoPaper provided by University of Oregon Economics Department in its series University of Oregon Economics Department Working Papers with number 2010-9.
Date of creation: 22 Nov 2009
Date of revision:
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scenario adjustment; scenario rejection; stated preference; value of a statistical life (VSL); value of a statistical illness profile;
Other versions of this item:
- 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).
- 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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- 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.
- 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.
- 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.
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