本页提供题录、可核实摘要与阅读线索。AI 解读未完成全文核验，可能有误；具体假设、证明和结论请核对原文。仅依据书目生成的内容属于阅读导航，不是对论文结论的确认。
摘要保留来源文本，未经模型改写。材料不足时保留待解读状态；引用采用 OpenAlex 单条关联记录，不合计版本，缺失不视为零，也不代表论文质量。
正在核对对应版本的资源…
This article considers testing the hypothesis that errors in a panel data model are weakly cross-sectionally dependent, using the exponent of cross-sectional dependence α, introduced recently in Bailey, Kapetanios, and Pesaran (2012). It is shown that the implicit null of the cross-sectional dependence (CD) test depends on the relative expansion rates of N and T. When T = O(N ε), for some 0 < ε ≤1, then the implicit null of the CD test is given by 0 ≤ α < (2 − ε)/4, which gives 0 ≤ α <1/4, when N and T tend to infinity at the same rate such that T/N → κ, with κ being a finite positive constant. It is argued that in the case of large N panels, the null of weak dependence is more appropriate than the null of independence which could be quite restrictive for large panels. Using Monte Carlo experiments, it is shown that the CD test has the correct size for values of α in the range [0, 1/4], for all combinations of N and T, and irrespective of whether the panel contains lagged values of the dependent variables, so long as there are no major asymmetries in the error distribution.