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The role of regret minimisation in lifestyle choices affecting the risk of coronary heart disease
► This paper introduces the discrete choice paradigm of Random Regret Minimisation (RRM) to the field of health economics. ► The combined use of RRM and Random Utility Maximisation (RUM) models provide useful behavioural insights on choice. ► Whilst the RUM is suitable for calculating welfare estima...
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Published in: | Journal of health economics 2013-01, Vol.32 (1), p.253-260 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | ► This paper introduces the discrete choice paradigm of Random Regret Minimisation (RRM) to the field of health economics. ► The combined use of RRM and Random Utility Maximisation (RUM) models provide useful behavioural insights on choice. ► Whilst the RUM is suitable for calculating welfare estimates, the RRM highlights how anticipated regret affects choices. ► We find that the choices of overweight or obese respondents and smokers are more likely to conform to the RUM approach. ► We also find that the choices of people in good health and with higher education are more likely to reflect the RRM approach.
This paper introduces the discrete choice model-paradigm of Random Regret Minimisation (RRM) to the field of health economics. The RRM is a regret-based model that explores a driver of choice different from the traditional utility-based Random Utility Maximisation (RUM). The RRM approach is based on the idea that, when choosing, individuals aim to minimise their regret–regret being defined as what one experiences when a non-chosen alternative in a choice set performs better than a chosen one in relation to one or more attributes. Analysing data from a discrete choice experiment on diet, physical activity and risk of a fatal heart attack in the next ten years administered to a sample of the Northern Ireland population, we find that the combined use of RUM and RRM models offer additional information, providing useful behavioural insights for better informed policy appraisal. |
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ISSN: | 0167-6296 1879-1646 |
DOI: | 10.1016/j.jhealeco.2012.10.007 |