Minimum Sliced Distance Estimation in a Class of Nonregular Econometric Models
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916512926793728 |
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| author | Fan, Yanqin Park, Hyeonseok |
| author_facet | Fan, Yanqin Park, Hyeonseok |
| contents | This paper proposes minimum sliced distance estimation in structural econometric models with possibly parameter-dependent supports. In contrast to likelihood-based estimation, we show that under mild regularity conditions, the minimum sliced distance estimator is asymptotically normally distributed leading to simple inference regardless of the presence/absence of parameter dependent supports. We illustrate the performance of our estimator on an auction model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_05621 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Minimum Sliced Distance Estimation in a Class of Nonregular Econometric Models Fan, Yanqin Park, Hyeonseok Econometrics This paper proposes minimum sliced distance estimation in structural econometric models with possibly parameter-dependent supports. In contrast to likelihood-based estimation, we show that under mild regularity conditions, the minimum sliced distance estimator is asymptotically normally distributed leading to simple inference regardless of the presence/absence of parameter dependent supports. We illustrate the performance of our estimator on an auction model. |
| title | Minimum Sliced Distance Estimation in a Class of Nonregular Econometric Models |
| topic | Econometrics |
| url | https://arxiv.org/abs/2412.05621 |