SPECIFICATION OF VARIANCE MATRICES FOR PANEL DATA MODELS
定义了面板数据或空间计量模型中误差方差矩阵的结构，使得仅用T和N阶矩阵就能计算其行列式和逆矩阵，同时允许异方差、个体自相关和时间空间相关，适用于大T N情形。
Many regression models have two dimensions, say time ( t = 1,…, T ) and households ( i = 1,…, N ), as in panel data, error components, or spatial econometrics. In estimating such models we need to specify the structure of the error variance matrix Ω , which is of dimension T N × T N . If T N is large, then direct computation of the determinant and inverse of Ω is not practical. In this note we define structures of Ω that allow the computation of its determinant and inverse, only using matrices of orders T and N , and at the same time allowing for heteroskedasticity, for household- or station-specific autocorrelation, and for time-specific spatial correlation.