Eliciting and distinguishing between weak and incomplete preferences: Theory, experiment and computation
提出一种实验设计和数据分析方法，用于在一般选择环境中引出并区分个体的严格偏好、无差异和犹豫不决成分，并首次实证记录了无差异与犹豫不决之间的理论区别。
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.