Advanced Search
MyIDEAS: Login

Modelling unobserved heterogeneity in contingent valuation of health risks

Contents:

Author Info

  • 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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.tandfonline.com/doi/abs/10.1080/00036840500427460
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 38 (2006)
Issue (Month): 19 ()
Pages: 2315-2325

as in new window
Handle: RePEc:taf:applec:v:38:y:2006:i:19:p:2315-2325

Contact details of provider:
Web page: http://www.tandfonline.com/RAEC20

Order Information:
Web: http://www.tandfonline.com/pricing/journal/RAEC20

Related research

Keywords:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

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, IEF, vol. 186(3), pages 43-60, October.
  2. 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.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:taf:applec:v:38:y:2006:i:19:p:2315-2325. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.