IDEAS home Printed from https://ideas.repec.org/p/ags/aiea13/149894.html
   My bibliography  Save this paper

The incorporation of subjective risks into choice experiments to test scenario adjustment

Author

Listed:
  • Cerroni, Simone
  • Notaro, Sandra
  • Raffaelli, Roberta
  • Shaw, Douglass W.

Abstract

In choice experiment (CE) applications, subjects are typically assumed to fully accept information given in the status quo (SQ) alternative, however, subjects might adjust such information on the basis of their subjective beliefs. This phenomenon is known as scenario adjustment. By using a CE field survey, we investigate whether subjects adjust risks portrayed in the SQ using their subjective estimates via a two-stage approach. In the first stage, subjective risks are elicited using the exchangeability method. In the second stage, two treatment groups are designed. In the first group, each subject is presented with a SQ which incorporates her/his own subjective risk estimate, and, hence, no adjustment is required. In the second group, each subject faces a SQ where the presented risk is not consistent with her/his own estimate, and, hence, a mental adjustment to the scenario might take place. Our modeling results suggest that subjects who are provided with a SQ in which the risk is lower than their own subjective estimates have a higher maximum willingness to pay (WTP) for a risk reduction than subjects provided with a SQ where the risk is consistent with their perceptions. Hence, in this case the scenario adjustment takes place. In contrast, subjects who are presented with a SQ where the risk is higher than their subjective estimates, overreact to the risk information, and have a higher WTP for the risk reduction than subjects who face a SQ where the presented risk is consistent with their perceived risks. Hence, in this case they appear to go along with the information in the SQ and abandon their subjective estimate

Suggested Citation

  • Cerroni, Simone & Notaro, Sandra & Raffaelli, Roberta & Shaw, Douglass W., 2013. "The incorporation of subjective risks into choice experiments to test scenario adjustment," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149894, Italian Association of Agricultural and Applied Economics (AIEAA).
  • Handle: RePEc:ags:aiea13:149894
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/149894
    Download Restriction: no

    References listed on IDEAS

    as
    1. Raymond J. G. M. Florax & Chiara M. Travisi & Peter Nijkamp, 2005. "A meta-analysis of the willingness to pay for reductions in pesticide risk exposure," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, pages 441-467.
    2. Hensher, David A. & Greene, William H. & Li, Zheng, 2011. "Embedding risk attitude and decision weights in non-linear logit to accommodate time variability in the value of expected travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 954-972, August.
    3. Riccardo Scarpa & Sandra Notaro & Jordan Louviere & Roberta Raffaelli, 2010. "Exploring Scale Effects of Best/Worst Rank Ordered Choice Data to Estimate Benefits of Tourism in Alpine Grazing Commons," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(3), pages 809-824.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, December.
    5. Steffen Andersen & Glenn Harrison & Morten Lau & E. Rutström, 2009. "Elicitation using multiple price list formats," Experimental Economics, Springer;Economic Science Association, vol. 12(3), pages 365-366, September.
    6. Viscusi, W Kip, 1985. "Are Individuals Bayesian Decision Makers?," American Economic Review, American Economic Association, vol. 75(2), pages 381-385, May.
    7. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    8. Viscusi, W Kip, 1990. "Do Smokers Underestimate Risks?," Journal of Political Economy, University of Chicago Press, vol. 98(6), pages 1253-1269, December.
    9. Cerroni, Simone & Notaro, Sandra & Shaw, W. Douglass, 2012. "Eliciting and estimating valid subjective probabilities: An experimental investigation of the exchangeability method," Journal of Economic Behavior & Organization, Elsevier, vol. 84(1), pages 201-215.
    10. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2008. "Eliciting Risk and Time Preferences," Econometrica, Econometric Society, vol. 76(3), pages 583-618, May.
    11. Mohammed Abdellaoui & Aurelien Baillon & Laetitia Placido & Peter P. Wakker, 2011. "The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation," American Economic Review, American Economic Association, vol. 101(2), pages 695-723, April.
    12. Travisi, Chiara Maria & Nijkamp, Peter, 2008. "Valuing environmental and health risk in agriculture: A choice experiment approach to pesticides in Italy," Ecological Economics, Elsevier, vol. 67(4), pages 598-607, November.
    13. David A. Hensher & Zheng Li, 2012. "Valuing Travel Time Variability within a Rank-Dependent Utility Framework and an Investigation of Unobserved Taste Heterogeneity," Journal of Transport Economics and Policy, University of Bath, vol. 46(2), pages 293-312, May.
    14. Cerroni, Simone & Shaw, W. Douglass, 2012. "Does climate change information affect stated risks of pine beetle impacts on forests? An application of the exchangeability method," Forest Policy and Economics, Elsevier, vol. 22(C), pages 72-84.
    15. 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.
    16. Stephane Hess & John Rose, 2009. "Should Reference Alternatives in Pivot Design SC Surveys be Treated Differently?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 297-317, March.
    17. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    18. Viscusi, W Kip, 1997. "Alarmist Decisions with Divergent Risk Information," Economic Journal, Royal Economic Society, vol. 107(445), pages 1657-1670, November.
    19. Cameron, Trudy Ann, 2005. "Individual option prices for climate change mitigation," Journal of Public Economics, Elsevier, vol. 89(2-3), pages 283-301, February.
    20. Carl S. Spetzler & Carl-Axel S. Staël Von Holstein, 1975. "Exceptional Paper--Probability Encoding in Decision Analysis," Management Science, INFORMS, vol. 22(3), pages 340-358, November.
    21. Peter Wakker & Daniel Deneffe, 1996. "Eliciting von Neumann-Morgenstern Utilities When Probabilities Are Distorted or Unknown," Management Science, INFORMS, vol. 42(8), pages 1131-1150, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Torres, Cati & Faccioli, Michela & Riera Font, Antoni, 2017. "Waiting or acting now? The effect on willingness-to-pay of delivering inherent uncertainty information in choice experiments," Ecological Economics, Elsevier, vol. 131(C), pages 231-240.

    More about this item

    Keywords

    subjective risks; risk information; scenario adjustment; choice experiment; best-worst pivot design; Consumer/Household Economics; Demand and Price Analysis; C83; C93; D81; Q18;

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aiea13:149894. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aieaaea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.