Inferring Willingness-to-Pay for Health Attributes of Air Quality Using Information on ranking of Alternatives and Cognitive Ability of Respondents
We investigate the use of variable scale parameters to account for heterogeneity in responses to a stated preference survey of willingness to pay for air quality. The survey instrument collected full rankings of four alternatives in each of nine choice sets. Nine of 54 pairwise comparisons involved dominated alternatives; selection of a dominated alternative is interpreted as indicating cognitive difficulties. We allow the scale parameter in a conditional logit model to vary by the ranking considered (first, second or third choice) and by the degree of cognitive difficulty encountered. We investigate the effect of this on the magnitude and precision of estimated willingness-to-pay using empirically-based confidence intervals. The size of the scale parameter is significantly and positively related to the frequency with which respondents chose dominated choices, even after corrections designed to eliminate endogeneity bias. Ignoring heterogeneity in the cognitive ability of respondents biases willingness-to-pay estimates upwards. Consideration of second and third choices narrows the confidence intervals on WTP estimates. Introducing a variable scale parameter related to ranking by itself does not improve the precision of the estimate. Sample STATA code is provided.
|Date of creation:||Feb 2001|
|Date of revision:|
|Contact details of provider:|| Postal: 1280 Main Street West, Hamilton, Ontario, L8S 4M4|
Phone: (905) 525-9140 ext. 22765
Fax: (905) 521-8232
Web page: http://www.economics.mcmaster.ca/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hensher, David & Louviere, Jordan & Swait, Joffre, 1998. "Combining sources of preference data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 197-221, November.
When requesting a correction, please mention this item's handle: RePEc:mcm:deptwp:2001-02. 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: ()
If references are entirely missing, you can add them using this form.