Delving into Choice Internals: A Joint Discrete Choice/Attribute Rating Model
Multi-attribute modeling has rapidly progressed from being a novelty to becoming a widely used tool of economic research. When both choice and attribute ratings data are available, a model that makes joint use of both offers informative inference opportunities. In the present study we develop a joint model which utilizes both choice and ratings data, allows for scale usage heterogeneity, is robust to violations of utility continuity and completeness. The model is used to obtain WTP estimates for genetically-modified content and country-of-origin attributes in an survey-based study of Canola oil labeling. The median survey respondent's WTP for non-GM Canola oil was found to be CA$0.92/liter. The median WTP for non-specification of GM content was found to be approximately 80% of the WTP for the explicitly non-GM-labeled product. The median WTP to purchase Canada-made Canola oil versus a U.S. product was estimated to be CA$0.86/liter.
|Date of creation:||2008|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (414) 918-3190
Fax: (414) 276-3349
Web page: http://www.aaea.org
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.:
- David Hensher & John Rose & William Greene, 2005. "The implications on willingness to pay of respondents ignoring specific attributes," Transportation, Springer, vol. 32(3), pages 203-222, 05.
- Swait, Joffre & Adamowicz, Wiktor L., 1999.
"Choice Environment, Market Complexity and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice,"
Staff Paper Series
24093, University of Alberta, Department of Resource Economics and Environmental Sociology.
- Swait, Joffre & Adamowicz, Wiktor, 2001. "Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 86(2), pages 141-167, November.
- Rossi P. E & Gilula Z. & Allenby G. M, 2001. "Overcoming Scale Usage Heterogeneity: A Bayesian Hierarchical Approach," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 20-31, March.
- Edward Morey & Jennifer Thacher & William Breffle, 2006. "Using Angler Characteristics and Attitudinal Data to Identify Environmental Preference Classes: A Latent-Class Model," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 34(1), pages 91-115, 05.
- Hauser, John R., 1985. "Agendas and consumer choice," Working papers 1641-85., Massachusetts Institute of Technology (MIT), Sloan School of Management.
When requesting a correction, please mention this item's handle: RePEc:ags:aaea08:6252. 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: (AgEcon Search)
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.