We show that the abstract and conclusion of Hansen's {\it Econometrica} paper, \cite{Hansen22}, entitled a modern Gauss-Markov theorem (MGMT), obscures a material fact, which in turn can confuse students. The MGMT places ordinary least squares (OLS) back on a high pedestal by bringing in the Cramer-Rao efficiency bound. We explain why linearity and unbiasedness are linked, making most nonlinear estimators biased. Hence, MGMT extends the reach of the century-old GMT by a near-empty set. It misleads students because it misdirects attention back to the unbiased OLS from beneficial shrinkage and other tools, which reduce the mean squared error (MSE) by injecting bias.
翻译:我们发现,汉森的论文“现代高斯-马尔科夫理论(MGMT)”的抽象和结论掩盖了一个物质事实,而这反过来又会混淆学生。 MGMT将普通的最小方块(OLS)放在高位上,把Cramer-Rao效率捆绑起来。我们解释为什么线性和公正性是联系在一起的,使大多数非线性估量者有偏见。 因此,MGMMT通过近乎空洞的装置扩大了世纪之久的GMT的范围。 它误导学生,因为它误导了学生,因为它错误地将注意力从有益的收缩和其他工具上引回对无偏向无偏向的OSS,而这些工具通过注射偏见减少了平均平方错误(MSE ) 。