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Estimation Of Revealed Probabilities And Utility Functions For Product Safety Decisions

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  • W. Kip Viscusi
  • William N. Evans

Abstract

Using survey data on consumer product purchases, this paper introduces an approach to estimate jointly individual utility functions and risk perceptions implied by their decisions. The behavioral risk beliefs reflected in consumers' risky decisions differ from the stated probabilities given to them in the survey. These results are not consistent with a Bayesian learning model in which the information respondents utilize is restricted to what the survey presents. The results are, however, potentially consistent with models in which prior risk information is influential or models in which people do not act in a fully rational manner. © 1998 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

Suggested Citation

  • W. Kip Viscusi & William N. Evans, 1998. "Estimation Of Revealed Probabilities And Utility Functions For Product Safety Decisions," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 28-33, February.
  • Handle: RePEc:tpr:restat:v:80:y:1998:i:1:p:28-33
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    Citations

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    Cited by:

    1. Steffen Andersen & John Fountain & Glenn Harrison & E. Rutström, 2014. "Estimating subjective probabilities," Journal of Risk and Uncertainty, Springer, vol. 48(3), pages 207-229, June.
    2. Jakus, Paul M & Shaw, W Douglass, 2003. "Perceived Hazard and Product Choice: An Application to Recreational Site Choice," Journal of Risk and Uncertainty, Springer, vol. 26(1), pages 77-92, January.
    3. Andrea M. Leiter & Gerald J. Pruckner, 2006. "Proportionality of Willingness to Pay to Small Risk Changes – The Impact of Attitudinal Factors in Scope Tests," Working Papers 2006.90, Fondazione Eni Enrico Mattei.
    4. Thomas Lundhede & Jette Bredahl Jacobsen & Nick Hanley & Niels Strange & Bo Jellesmark Thorsen, 2015. "Incorporating Outcome Uncertainty and Prior Outcome Beliefs in Stated Preferences," Land Economics, University of Wisconsin Press, vol. 91(2), pages 296-316.
    5. Glenn C. Blomquist, 2004. "Self-Protection and Averting Behavior, Values of Statistical Lives, and Benefit Cost Analysis of Environmental Policy," Review of Economics of the Household, Springer, vol. 2(1), pages 89-110, March.
    6. Hyytinen, Ari & Pajarinen, Mika, 2005. "Why Are All New Entrepreneurs Better Than Average? Evidence from Subjective Failure Rate Expectations," Discussion Papers 987, The Research Institute of the Finnish Economy.
    7. Atsushi Maruyama & Masao Kikuchi, 2004. "Risk-learning process in forming willingness-to-pay for egg safety," Agribusiness, John Wiley & Sons, Ltd., vol. 20(2), pages 167-179.
    8. Konstantinos Drakos & Catherine Mueller, 2014. "On the Determinants of Terrorism Risk Concern in Europe," Defence and Peace Economics, Taylor & Francis Journals, vol. 25(3), pages 291-310, June.
    9. Cropper, Maureen L. & Haile, Mitiku & Lampietti, Julian & Poulos, Christine & Whittington, Dale, 2004. "The demand for a malaria vaccine: evidence from Ethiopia," Journal of Development Economics, Elsevier, vol. 75(1), pages 303-318, October.
    10. Nikolai Svetlov, 2001. "Econometric application of linear programming: a model of Russian large-scale farm (the case of the Moscow Region)," Econometrics 0112002, University Library of Munich, Germany.
    11. 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.
    12. William H. Starbuck, 2009. "Perspective ---Cognitive Reactions to Rare Events: Perceptions, Uncertainty, and Learning," Organization Science, INFORMS, vol. 20(5), pages 925-937, October.

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