On the Estimated Variances of Regression Coefficients in Misspecified Error Components Models
研究了在错误设定误差成分结构时，回归系数估计方差的不一致性，发现当错误省略某些误差成分时，估计方差总是偏小，并给出了两向模型中时间成分被错误省略时的阶数结果。
In a regression model with an arbitrary number of error components, the covariance matrix of the disturbances has three equivalent representations as linear combinations of matrices. Furthermore, this property is invariant with respect to powers, matrix addition, and matrix multiplication. This result is applied to the derivation and interpretation of the inconsistency of the estimated coefficient variances when the error components structure is improperly restricted. This inconsistency is defined as the difference between the asymptotic variance obtained when the restricted model is correctly specified, and the asymptotic variance obtained when the restricted model is incorrectly specified; when some error components are improperly omitted, and the remaining variance components are consistently estimated, it is always negative. In the case where the time component is improperly omitted from the two-way model, we show that the difference between the true and estimated coefficient variances is of order greater than N –1 in probability.