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Modelling unobserved heterogeneity in contingent valuation of health risks

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  • Jorge Arana
  • Carmelo Leon

Abstract

Human preferences for alternative levels of health risks can be heterogeneous. In this paper a flexible distribution approach to model health values elicited with the dichotomous choice contingent valuation method is considered. Rigid parametric structures cannot model sample heterogeneity while imposing strong assumptions on the error distribution. A mixture of normal distributions is considered which can approximate arbitrary well any empirical distributions as the number of mixtures increases. The model is applied to data on willingness to pay for reducing the individual risk of an episode of respiratory illness. The mixture distribution model is compared with the rigid probit model using a Bayes factor test. The results show that the mixture modelling approach improves performance while allowing for the consideration of alternative groups of individuals with different preferences for health risks.

Suggested Citation

  • Jorge Arana & Carmelo Leon, 2006. "Modelling unobserved heterogeneity in contingent valuation of health risks," Applied Economics, Taylor & Francis Journals, vol. 38(19), pages 2315-2325.
    • Handle: RePEc:taf:applec:v:38:y:2006:i:19:p:2315-2325
    DOI: 10.1080/00036840500427460
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    References listed on IDEAS

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    1. Isabel Proenca, "undated". "On the performance of the H-H Test," Statistic und Oekonometrie 9310, Humboldt Universitaet Berlin.
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    Cited by:

    1. Pere Riera & Raúl Brey & Guillermo Gándara, 2008. "Bid design for non-parametric contingent valuation with a single bounded dichotomous choice format," Hacienda Pública Española / Review of Public Economics, IEF, vol. 186(3), pages 43-60, October.
    2. Stefani, Gianluca & Scarpa, Riccardo & Lombardi, Ginevra V., 2014. "An addendum to: a meta-analysis of hypothethical bias in stated preference valuation," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 3(2), pages 1-10, August.
    3. Gelo, Dambala & Turpie, Jane, 2021. "Bayesian analysis of demand for urban green space: A contingent valuation of developing a new urban park," Land Use Policy, Elsevier, vol. 109(C).
    4. Araña, Jorge E. & León, Carmelo J. & Hanemann, Michael W., 2008. "Emotions and decision rules in discrete choice experiments for valuing health care programmes for the elderly," Journal of Health Economics, Elsevier, vol. 27(3), pages 753-769, May.

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