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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2604.13399 |
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| _version_ | 1866914473905750016 |
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| author | Liu, Nan Liu, Yanbo Sasaki, Yuya Wan, Yuanyuan |
| author_facet | Liu, Nan Liu, Yanbo Sasaki, Yuya Wan, Yuanyuan |
| contents | The maximum score method (Manski, 1975, 1985) is a powerful approach for binary choice models, yet it is known to face both practical and theoretical challenges. In particular, the estimator converges at a slower-than-root-$n$ rate to a nonstandard limiting distribution. We investigate conditions under which strictly concave surrogate score functions can be employed to achieve identification through a smooth criterion function. This criterion enables root-$n$ convergence to a normal limiting distribution. While the conditions to guarantee these desired properties are nontrivial, we characterize them in terms of primitive conditions. Extensive simulation studies support, the root-$n$ convergence rate, the asymptotic normality, and the validity of the standard inference methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_13399 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Root-$n$ Asymptotically Normal Maximum Score Estimation Liu, Nan Liu, Yanbo Sasaki, Yuya Wan, Yuanyuan Econometrics The maximum score method (Manski, 1975, 1985) is a powerful approach for binary choice models, yet it is known to face both practical and theoretical challenges. In particular, the estimator converges at a slower-than-root-$n$ rate to a nonstandard limiting distribution. We investigate conditions under which strictly concave surrogate score functions can be employed to achieve identification through a smooth criterion function. This criterion enables root-$n$ convergence to a normal limiting distribution. While the conditions to guarantee these desired properties are nontrivial, we characterize them in terms of primitive conditions. Extensive simulation studies support, the root-$n$ convergence rate, the asymptotic normality, and the validity of the standard inference methods. |
| title | Root-$n$ Asymptotically Normal Maximum Score Estimation |
| topic | Econometrics |
| url | https://arxiv.org/abs/2604.13399 |