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摘要翻译：
本文提出了一种新的线性面板数据模型的标准误差估计器。该估计器对未知形式的异方差、序列相关和横截面相关具有较强的鲁棒性。串行相关由Newey-West方法控制。为了控制截面相关性，我们建议使用阈值化方法，而不假设簇是已知的。我们建立了所提出的估计量的相合性。蒙特卡罗仿真结果表明，该方法是有效的。考虑了一个经验应用。
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英文标题：
《Standard Errors for Panel Data Models with Unknown Clusters》
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作者：
Jushan Bai, Sung Hoon Choi, and Yuan Liao
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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：
This paper develops a new standard-error estimator for linear panel data models. The proposed estimator is robust to heteroskedasticity, serial correlation, and cross-sectional correlation of unknown forms. The serial correlation is controlled by the Newey-West method. To control for cross-sectional correlations, we propose to use the thresholding method, without assuming the clusters to be known. We establish the consistency of the proposed estimator. Monte Carlo simulations show the method works well. An empirical application is considered.
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PDF链接：
https://arxiv.org/pdf/1910.07406
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