Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Nov;27(11):1699-1716.
doi: 10.1002/hec.3795. Epub 2018 Jul 3.

Ambiguity preferences for health

Affiliations

Ambiguity preferences for health

Arthur E Attema et al. Health Econ. 2018 Nov.

Abstract

In most medical decisions, probabilities are ambiguous and not objectively known. Empirical evidence suggests that people's preferences are affected by ambiguity. Health economic analyses generally ignore ambiguity preferences and assume that they are the same as preferences under risk. We show how health preferences can be measured under ambiguity, and we compare them with health preferences under risk. We assume a general ambiguity model that includes many of the ambiguity models that have been proposed in the literature. For health gains, ambiguity preferences and risk preferences were indeed the same. For health losses, they differed with subjects being more pessimistic in decision under ambiguity. Utility and loss aversion were the same for risk and ambiguity. Our results imply that reducing the clinical ambiguity of health losses has more impact than reducing the ambiguity of health gains, that utilities elicited with known probabilities may not carry over to an ambiguous setting, and that ambiguity aversion may impact value of information analyses if losses are involved. These findings are highly relevant for medical decision making, because most medical interventions involve losses.

Keywords: ambiguity; health.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Presentation of the choices under ambiguity [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 2
Figure 2
Original and repeated elicitation of the third indifference value for gains [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 3
Figure 3
Tests of ambiguity aversion [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 4
Figure 4
The utility for gains and losses based on the median data [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 5
Figure 5
Individual shapes of utility [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 6
Figure 6
The relation between median gains and median losses with the same absolute utility [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 7
Figure 7
Probability and event weighting functions for gains and losses based on the median data [Colour figure can be viewed at http://wileyonlinelibrary.com]

References

    1. Abdellaoui, M. , Bleichrodt, H. , L'Haridon, O. , & van Dolder, D. (2016). Measuring loss aversion under ambiguity: A method to make prospect theory completely observable. Journal of Risk and Uncertainty, 52(1), 1–20.
    1. Anwar, S. , & Zheng, M. (2012). Competitive insurance market in the presence of ambiguity. Insurance: Mathematics and Economics, 50(1), 79–84.
    1. Asano, T. , & Shibata, A. (2011). Risk and uncertainty in health investment. The European Journal of Health Economics, 12(1), 79–85. - PubMed
    1. Attema, A. E. , Bleichrodt, H. , L'Haridon, O. , Peretti‐Watel, P. , & Seror, V. (2018). Discounting health and money: New evidence using a more robust method. Journal of Risk and Uncertainty, 56(2), 117–140. - PMC - PubMed
    1. Attema, A. E. , Brouwer, W. B. F. , & L'Haridon, O. (2013). Prospect theory in the health domain: A quantitative assessment. Journal of Health Economics, 32(6), 1057–1065. - PubMed

LinkOut - more resources