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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2202.11031 |
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| _version_ | 1866918252890816512 |
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| author | Li, Xingyu Song, Xiaojun Sun, Zhenting |
| author_facet | Li, Xingyu Song, Xiaojun Sun, Zhenting |
| contents | This paper proposes a simple unified inference approach on moment restrictions in the presence of nuisance parameters. The proposed test is constructed based on a new characterization that avoids the estimation of nuisance parameters and can be broadly applied across diverse settings. Under suitable conditions, the test is shown to be asymptotically size controlled and consistent for both independent and dependent samples. Monte Carlo simulations show that the test performs well in finite samples. Numerical results from the application to conditional moment restriction models with weak instruments demonstrate that the proposed method may improve upon existing approaches in the literature. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2202_11031 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Unified Inference on Moment Restrictions with Nuisance Parameters Li, Xingyu Song, Xiaojun Sun, Zhenting Methodology Econometrics This paper proposes a simple unified inference approach on moment restrictions in the presence of nuisance parameters. The proposed test is constructed based on a new characterization that avoids the estimation of nuisance parameters and can be broadly applied across diverse settings. Under suitable conditions, the test is shown to be asymptotically size controlled and consistent for both independent and dependent samples. Monte Carlo simulations show that the test performs well in finite samples. Numerical results from the application to conditional moment restriction models with weak instruments demonstrate that the proposed method may improve upon existing approaches in the literature. |
| title | Unified Inference on Moment Restrictions with Nuisance Parameters |
| topic | Methodology Econometrics |
| url | https://arxiv.org/abs/2202.11031 |