Testing Inequalities Linear in Nuisance Parameters
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866917060782587904 |
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| author | Cox, Gregory Fletcher Shi, Xiaoxia Shimizu, Yuya |
| author_facet | Cox, Gregory Fletcher Shi, Xiaoxia Shimizu, Yuya |
| contents | This paper proposes a new test for inequalities that are linear in possibly partially identified nuisance parameters. This type of hypothesis arises in a broad set of problems, including subvector inference for linear unconditional moment (in)equality models, specification testing of such models, and inference for parameters bounded by linear programs. The new test uses a two-step test statistic and a chi-squared critical value with data-dependent degrees of freedom that can be calculated by an elementary formula. Its simple structure and tuning-parameter-free implementation make it attractive for practical use. We establish uniform asymptotic validity of the test, demonstrate its finite-sample size and power in simulations, and illustrate its use in an empirical application that analyzes women's labor supply in response to a welfare policy reform. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_27633 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Testing Inequalities Linear in Nuisance Parameters Cox, Gregory Fletcher Shi, Xiaoxia Shimizu, Yuya Methodology Econometrics Applications This paper proposes a new test for inequalities that are linear in possibly partially identified nuisance parameters. This type of hypothesis arises in a broad set of problems, including subvector inference for linear unconditional moment (in)equality models, specification testing of such models, and inference for parameters bounded by linear programs. The new test uses a two-step test statistic and a chi-squared critical value with data-dependent degrees of freedom that can be calculated by an elementary formula. Its simple structure and tuning-parameter-free implementation make it attractive for practical use. We establish uniform asymptotic validity of the test, demonstrate its finite-sample size and power in simulations, and illustrate its use in an empirical application that analyzes women's labor supply in response to a welfare policy reform. |
| title | Testing Inequalities Linear in Nuisance Parameters |
| topic | Methodology Econometrics Applications |
| url | https://arxiv.org/abs/2510.27633 |