Alternative Models of Preference Heterogeneity for Elicited Choice Probabilities - Nathan Kettlewell; Matthew J. Walker; Hong Il Yoo (Institute of Labor Economics (IZA), 2024)
Discrete choice experiments (DCEs) often present concise choice scenarios that may appear incomplete to respondents. To allow respondents to express uncertainty arising from this incompleteness, DCEs may ask them to state probabilities with which they expect to make specific choices. The workhorse method for analyzing the elicited probabilities involves semi-parametric estimation of population average preferences. Despite flexible distributional assumptions, this method presents challenges in estimating unobserved preference heterogeneity, a key element in non-market valuation studies. We introduce a fractional response model based on a mixture of beta distributions. The model enables researchers to uncover preference heterogeneity under comparable parametric assumptions as adopted in conventional choice analysis, and can accommodate multiplicative forms of heterogeneity that make the semi-parametric method inconsistent. Using a DCE on alternative fuel vehicles, we illustrate the complementary roles of the parametric and semi-parametric approaches. We also undertake a separate analysis in which respondents are randomized to either a DCE employing a conventional choice elicitation format or a parallel DCE employing the probability elicitation format.
Keywords: C35; D12; D84; Q42; R41; 330; discrete choice experiment; probability elicitation; mixed logit; beta regression; willingness to pay