摘要翻译：
对于具有大量独立群的聚类数据，我们给出了一个完备的渐近分布理论，推广了经典的大数定律、一致定律、中心极限理论和聚类协方差矩阵估计。我们的理论允许具有异构和无界簇大小的簇观测。我们的条件完全符合I.N.I.D.的经典结果。观察，即我们的条件专门用于独立抽样下的经典条件。我们利用这一理论发展了一个基于线性最小二乘、2SLS、非线性MLE和非线性GMM的完全渐近分布估计理论。
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英文标题：
《Asymptotic Theory for Clustered Samples》
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作者：
Bruce E. Hansen and Seojeong Lee
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最新提交年份：
2019
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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 provide a complete asymptotic distribution theory for clustered data with a large number of independent groups, generalizing the classic laws of large numbers, uniform laws, central limit theory, and clustered covariance matrix estimation. Our theory allows for clustered observations with heterogeneous and unbounded cluster sizes. Our conditions cleanly nest the classical results for i.n.i.d. observations, in the sense that our conditions specialize to the classical conditions under independent sampling. We use this theory to develop a full asymptotic distribution theory for estimation based on linear least-squares, 2SLS, nonlinear MLE, and nonlinear GMM.
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PDF链接：
https://arxiv.org/pdf/1902.01497