Directed Tests of No Cross‐Sectional Correlation in Large‐N Panel Data Models
基于信息矩阵等式提出定向检验方法，通过加权残差协方差或相关性检验无横截面相关，适用于大N面板数据，无需球形或分布假设。
Summary The paper proposes tests for no cross‐correlation based on the information matrix equality. The tests rely on suitably weighted residual cross‐covariances or cross‐correlations, and are in this sense a generalization of Pesaran's (2004, CESifo working paper 1229) test for no cross‐sectional dependence. They follow chi‐squared distributions under joint N , T asymptotics without restrictive sphericity or distributional assumptions. When using the outcome of the directed tests to decide whether to use panel‐robust standard errors or not for testing slope parameters, the latter tests are apparently not affected; they can be severely affected, though, if using generic cross‐correlation tests as pretests. Copyright © 2015 John Wiley & Sons, Ltd.