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摘要翻译：
针对线性广义矩量法(GMM)提出了一种新的有限样本修正方差估计，包括一步估计、两步估计和迭代估计。我们的公式在Windmeijer(2005)常用的有限样本校正的基础上，进一步校正了方差估计中的过辨识偏差，从而得到了双重校正。提出的双重校正的一个重要特征是，它自动提供对矩条件的错误规范的鲁棒性。相比之下，传统的方差估计和Windmeijer校正在错误的规范下是不一致的。也就是说，所提出的双重修正公式提供了一种方便的方法，以获得在正确规范下的改进推理，并同时具有对错误规范的鲁棒性。
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英文标题：
《A Doubly Corrected Robust Variance Estimator for Linear GMM》
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作者：
Jungbin Hwang, Byunghoon Kang, Seojeong Lee
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最新提交年份：
2020
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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：
We propose a new finite sample corrected variance estimator for the linear generalized method of moments (GMM) including the one-step, two-step, and iterated estimators. Our formula additionally corrects for the over-identification bias in variance estimation on top of the commonly used finite sample correction of Windmeijer (2005) which corrects for the bias from estimating the efficient weight matrix, so is doubly corrected. An important feature of the proposed double correction is that it automatically provides robustness to misspecification of the moment condition. In contrast, the conventional variance estimator and the Windmeijer correction are inconsistent under misspecification. That is, the proposed double correction formula provides a convenient way to obtain improved inference under correct specification and robustness against misspecification at the same time.
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PDF链接：
https://arxiv.org/pdf/1908.07821
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