Efficiency of Ordinary Least Squares for Linear Models with Autocorrelation
重新审视Kramer(1980)关于自相关误差线性模型中最小二乘估计的结果，发现其效率度量有缺陷，低估了修正自相关的好处。
Abstract This article provides a reconsideration of Kramer's (1980) results on least squares estimation in linear models with autocorrelated errors. Kramer's results are shown to be dependent on his measure of efficiency and to understate the advantages of correcting for autocorrelation.