Is the distribution of resolvable uncertainty type I extreme value? A test for random coefficient models using choice probabilities

Preprint

Stated choice probabilities are increasingly used in conjunction with the random-coefficient model (RCM) to describe individual preferences. They allow survey respondents to express uncertainty about the future or the incompleteness of a hypothetical scenario: the resolvable uncertainty. Parametric assumptions such as a Type I extreme value (EV1) distribution are almost always imposed on this uncertainty to identify and estimate the associated RCM. This paper proposes the first test for these parametric assumptions, based on a nonparametric identification result for the population distribution of the interquantile range of the resolvable uncertainty. In all four empirical applications considered, the test finds strong evidence against the EV1 assumption.

Authors: Meango, R

• Publication status: Published
• Preprint server: arXiv
• Publication date: 2025-03-18
• DOI: 10.48550/arXiv.2503.13901
• Server owner: Cornell University
• Language: English
• Keywords: random utility model; choice probability; stated preferences; resolvable uncertainty; willingness-to-pay