Estimating individual valuation distributions with multiple bounded discrete choice data

This article presents a new modelling strategy that estimates individual valuation distributions with Multiple Bounded Discrete Choice (MBDC) data. An individual's valuation of a commodity or service is assumed to have a distribution rather than being a single number. Likelihood responses to the MBDC questions are numerically coded and treated with a new panel technique. The proposed estimation strategy is empirically compared with previous data analysis methods.