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关注这篇论文的作者
Hannes Leeb

模型选择后估计量的有限样本分布:一致与非一致逼近

研究问题
研究模型选择后估计量的有限样本分布,以及常规渐近逼近无法对真实参数保持一致准确的问题。
方法与思路
作者推导无条件和条件有限样本分布,再构造对参数一致接近这些分布、且较易解释的近似。
材料陈述的贡献
摘要称获得参数一致的有限样本分布逼近,并补充了条件于选中错误模型时估计量的渐近分布。
阅读关注点
应核对模型选择规则、条件事件和参数范围,以及一致逼近采用的距离、误差界与适用模型类别。
阅读边界
出版社摘要未说明具体模型、选择规则和一致性度量,不能据此判断该结果适用于任意模型选择程序。

原文摘要

In Pötscher (1991, Econometric Theory 7, 163–185) the asymptotic distribution of a post-model-selection estimator, both unconditional and conditional on selecting a correct model (minimal or not), has been derived. Limitations of these results are (i) that they do not provide information on the distribution of the post-model-selection estimator conditional on selecting an incorrect model and (ii) that the quality of this asymptotic approximation to the finite-sample distribution is not uniform with respect to the underlying parameters. In the present paper we first obtain the unconditional and also the conditional finite-sample distribution of the post-model-selection estimator, which turn out to be complicated and difficult to interpret. Second, we obtain approximations to the finite-sample distributions that are as simple and easy to interpret as the asymptotic distributions obtained in Pötscher (1991) but at the same time are close to the finite-sample distributions uniformly with respect to the underlying parameters. As a by-product, we also obtain the asymptotic distribution conditional on selecting an incorrect model.We thank the co-editor Richard Smith and the two referees for helpful comments on a previous version of this paper. Hannes Leeb's research was supported by the Austrian Science Foundation (FWF), project P13868-MAT.

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