Is the distribution of resolvable uncertainty Type I extreme value? A Test for Random Coefficient Models using Choice Probabilities
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866912280221843456 |
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| author | Meango, Romuald |
| author_facet | Meango, Romuald |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2503_13901 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Is the distribution of resolvable uncertainty Type I extreme value? A Test for Random Coefficient Models using Choice Probabilities Meango, Romuald General Economics Economics 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. |
| title | Is the distribution of resolvable uncertainty Type I extreme value? A Test for Random Coefficient Models using Choice Probabilities |
| topic | General Economics Economics |
| url | https://arxiv.org/abs/2503.13901 |