Title
A joint latent-class model: combining Likert-scale preference statements with choice data to harvest preference heterogeneity
Document Type
Article
Publication Date
9-2011
Abstract
In addition to choice questions (revealed and stated choices), preference surveys typically include other questions that provide information about preferences. Preference-statement data include questions on the importance of different attributes of a good or the extent of agreement with a particular statement. The intent of this paper is to model and jointly estimate preference heterogeneity using stated-preference choice data and preference-statement data. The starting point for this analysis is the belief that the individual has preferences, and both his/her choices and preference statements are manifestations of those preferences. Our modeling contribution is linking the choice data and preference-statement data in a latent-class framework. Estimation is straightforward using the E-M algorithm, even though our model has hundreds of preference parameters. Our estimates demonstrate that: (1) within a preference class, the importance anglers associate with different Green Bay site characteristics is in accordance with their responses to the preference statements; (2) estimated across-class utility parameters for fishing Green Bay are affected by the preference-statement data; (3) estimated across-class preference-statement response probabilities are affected by the inclusion of the choice data; and (4) both data sets influence the number of classes and the probability of belonging to a class as a function of the individual’s type.
Publication Title
Environmental and Resource Economics
Recommended Citation
Breffle, W. S.,
Morey, E. R.,
&
Thacher, J. A.
(2011).
A joint latent-class model: combining Likert-scale preference statements with choice data to harvest preference heterogeneity.
Environmental and Resource Economics,
50(1), 83-110.
http://doi.org/10.1007/s10640-011-9463-0
Retrieved from: https://digitalcommons.mtu.edu/business-fp/124
Publisher's Statement
© 2011 Springer Science+Business Media B.V. Publisher’s version of record: http://dx.doi.org/10.1007/s10640-011-9463-0