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The influence of the ratio bias phenomenon on the elicitation of health states utilities

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  • Jose-Luis Pinto-Prades
  • Jorge-Eduardo Martinez-Perez
  • Jose-Maria Abellan-Perpinan

Abstract

This paper tests whether logically equivalent risk formats can lead to different health state utilities elicited by means of the traditional standard gamble (SG) method and a modified version of the method that we call ``double lottery.'' We compare utilities for health states elicited when probabilities are framed in terms of frequencies with respect to 100 people in the population (i.e., X out of 100 who follow a medical treatment will die) with SG utilities elicited for frequencies with respect to 1,000 people in the population (i.e., Y out of 1,000 who follow a medical treatment will die). We found that people accepted a lower risk of death when success and failure probabilities were framed as frequencies type ``Y deaths out of 1,000'' rather than as frequencies type ``X deaths out of 100'' and hence the utilities for health outcomes were higher when the denominator was 1000 than when it was 100. This framing effect, known as Ratio Bias, may have important consequences in resource allocation decisions.

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Bibliographic Info

Article provided by Society for Judgment and Decision Making in its journal Judgment and Decision Making.

Volume (Year): 1 (2006)
Issue (Month): (November)
Pages: 118-133

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Handle: RePEc:jdm:journl:v:1:y:2006:i::p:118-133

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Related research

Keywords: framing effect; risk format; standard gamble; health state; dual-process theories.;

References

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  1. Dan Ariely & George Loewenstein & Drazen Prelec, 2003. ""Coherent Arbitrariness": Stable Demand Curves Without Stable Preferences," The Quarterly Journal of Economics, MIT Press, vol. 118(1), pages 73-105, February.
  2. José-Luis Pinto-Prades & José-María Abellán-Perpiñán, 2004. "Mesuring the Health of Populations: The Veil of Ignorance Approach," Working Papers 116, Barcelona Graduate School of Economics.
  3. Bleichrodt, Han, 2001. " Probability Weighting in Choice under Risk: An Empirical Test," Journal of Risk and Uncertainty, Springer, vol. 23(2), pages 185-98, September.
  4. Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
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Cited by:
  1. Carissa Bonner & Ben R. Newell, 2008. "How to make a risk seem riskier: The ratio bias versus construal level theory," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3, pages 411-416, June.
  2. Gabriella Passerini & Laura Macchi & Maria Bagassi, 2012. "A methodological approach to ratio bias," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(5), pages 602-617, September.
  3. Lefèbvre, Mathieu & Vieider, Ferdinand M. & Villeval, Marie Claire, 2009. "The Ratio Bias Phenomenon: Fact or Artifact?," IZA Discussion Papers 4546, Institute for the Study of Labor (IZA).
  4. Kaivanto, Kim & Kroll, Eike B., 2012. "Negative recency, randomization device choice, and reduction of compound lotteries," Economics Letters, Elsevier, vol. 115(2), pages 263-267.

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