Abstract
One core assumption of standard economic theory is that an individual’s preferences are stable, irrespective of the method used to elicit them. This assumption may be violated if preference reversals are observed when comparing different methods to elicit people’s preferences. People may then prefer A over B using one method while preferring B over A using another. Such preference reversals pose a significant problem for theoretical and applied research. We used a sample of medical and economics students to investigate preference reversals in the health and financial domain when choosing patients/clients. We explored whether preference reversals are associated with domain-relevant training and tested whether using guided ‘choice list’ elicitation reduces reversals. Our findings suggest that preference reversals were more likely to occur for medical students, within the health domain, and for open-ended valuation questions. Familiarity with a domain reduced the likelihood of preference reversals in that domain. Although preference reversals occur less frequently within specialist domains, they remain a significant theoretical and practical problem. The use of clearer valuation procedures offers a promising approach to reduce preference reversals.
| Original language | English |
|---|---|
| Pages (from-to) | 679-697 |
| Number of pages | 19 |
| Journal | European Journal of Health Economics |
| Volume | 22 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 20 Mar 2021 |
Bibliographical note
Funding Information:Sebastian Neumann-Böhme receives funding from an MRC Early Career Fellowship in the Economics of Health, Grant/Award Number: G1002334.
Funding Information:
We would like to thank Professor Aki Tsuchiya, Laurenske Visser, Margot Cloostermans, Job van Exel, the participants of the presentations at the iHEA 2019 in Basel, the EUHEA PhD 2019 in Porto, Lola HESG 2019, DGGOE 2019 in Augsburg and the HERU research seminar at the University of Aberdeen for their feedback.
Publisher Copyright:
© 2021, The Author(s).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research programs
- EMC NIHES-05-63-02 Quality
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