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摘要翻译：
多项式选择模型的辨识通常是通过使用具有完全支持的特殊协变量来建立的。本文展示了当所有协变量有界时，这些辨识结果如何推广到一大类多项式选择模型。给出了模型有限维参数的一个新的$\sqrt{n}$-一致渐近正态估计。
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英文标题：
《Identification and estimation of multinomial choice models with latent
special covariates》
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作者：
Nail Kashaev
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最新提交年份：
2021
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分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
Identification of multinomial choice models is often established by using special covariates that have full support. This paper shows how these identification results can be extended to a large class of multinomial choice models when all covariates are bounded. I also provide a new $\sqrt{n}$-consistent asymptotically normal estimator of the finite-dimensional parameters of the model.
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PDF链接：
https://arxiv.org/pdf/1811.05555
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