Optimal testing in a class of nonregular models
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866911191311319040 |
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| author | Shimizu, Yuya Otsu, Taisuke |
| author_facet | Shimizu, Yuya Otsu, Taisuke |
| contents | This paper studies optimal hypothesis testing for nonregular econometric models with parameter-dependent support. We consider both one-sided and two-sided hypothesis testing and develop asymptotically uniformly most powerful tests based on a limit experiment. Our two-sided test becomes asymptotically uniformly most powerful without imposing further restrictions such as unbiasedness, and can be inverted to construct a confidence set for the nonregular parameter. Simulation results illustrate desirable finite sample properties of the proposed tests. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_16413 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimal testing in a class of nonregular models Shimizu, Yuya Otsu, Taisuke Statistics Theory Econometrics Methodology This paper studies optimal hypothesis testing for nonregular econometric models with parameter-dependent support. We consider both one-sided and two-sided hypothesis testing and develop asymptotically uniformly most powerful tests based on a limit experiment. Our two-sided test becomes asymptotically uniformly most powerful without imposing further restrictions such as unbiasedness, and can be inverted to construct a confidence set for the nonregular parameter. Simulation results illustrate desirable finite sample properties of the proposed tests. |
| title | Optimal testing in a class of nonregular models |
| topic | Statistics Theory Econometrics Methodology |
| url | https://arxiv.org/abs/2403.16413 |