We propose an experimental design and data‑analytic method for eliciting and distinguishing the strict‑preference, indifference, and indecisiveness components of individual preferences in general choice environments. The design combines a forced‑choice treatment with a free‑choice treatment. In both treatments, subjects may select multiple alternatives from a menu. In the free‑choice treatment, subjects may also avoid or delay choice at a small expected cost. To analyze such data, we extend a standard non‑parametric goodness‑of‑fit criterion to accommodate multi‑valued choices. We apply it to evaluate the consistency of subjects’ 50 decisions with utility maximization and two models of incomplete‑preference maximization. Around 55% of subjects are well explained by one of these models, with 33% and 22% best explained by utility and incomplete-preference maximization, respectively. Revealed preferences typically feature non-trivial indifferences, and those that are incomplete often exhibit the predicted theoretical distinctions between indifference and indecisiveness, which are documented empirically for the first time.
Georgios Gerasimou (Fri,) studied this question.