北京交通大学卯光宇老师作了一场题为“Testing for Error Cross-Sectional Independence in a Two-Way Error Components Panel Data Model(双向误差分量面板数据模型的测试误差为截独立性)”的讲座，在职研究生讲座的主要内容是：

　　北京交通大学共有22个学科参评，系统科学一级学科排名全国第一，交通运输工程名列前茅，信息与通信工程、安全科学与工程、光学工程、统计学、应用经济学、土木工程、电气工程、建筑学等学科位于前列，计算机科学与技术、力学、机械工程、动力工程、城乡规划学、软件工程等学科具有优势。

　　本文提出了一种在一个双向误差分量面板数据模型的误差截独立性新的考验。模型被假定为基于大维数据集，因此两者的横截面尺寸和模型的时间序列尺寸被假定当相关渐近理论的开发，以趋向于无穷大。根据下原始数据情况统计文献现有的统计，我们制订了模型的残差内用一个比喻检验统计量。它表明，所得到的统计需要偏置校正，以使有效的推理。然而，偏置的首项依赖于未知参数。要实现可行的修正，我们建议估计首项的方法。从理论上证明了可行偏压校正统计可以被用来测试错误剖独立性。此外，一些仿真实验也进行评估新开发的测试的有限样本的性能。据发现，试验井下的零假设不考虑横截面尺寸和本文所考虑的时间序列维之间的相对幅度进行，并具有对几种典型的替代电源。

　　原文：This paper proposes a new test for the error cross-sectional independence in a two-way error components panel data model. The model is postulated to be based on large dimensional data sets, and hence both the cross-sectional dimension and the time-series dimension of the model are assumed to tend to in nity when related asymptotic theories are developed. Based on an existing statistic in the statistical literature under the raw data circumstance, we formulate an analogy test statistic using the within residuals of the model. It is shown that the resulting statistic needs bias correction to make valid inference. However, the leading term of the bias relies on unknown parameters. To implement feasible correction, we propose a method to estimate the leading term. It is theoretically proved that the feasible bias-corrected statistic can be employed to test the error cross-sectional independence. Additionally, several simulation experiments are also conducted to evaluate the nite-sample performance of the newly developed test. It is found that the test performs well under the null hypothesis irrespective of the relative magnitude between the cross-sectional dimension and the time-series dimension considered in this paper, and has power against several typical alternatives.