Higher-order approximations for frequency domain time series regression
给出了高效频域回归估计量的二阶展开和均方误差近似，展示了带宽选择如何影响二阶效率，并提供了数据驱动的带宽选择规则，通过蒙特卡洛模拟比较了两种常用谱回归估计量的二阶渐近差异。
Second-order expansions and mean squared error approximations are given for efficient frequency domain regression estimators. While bandwidth choices do not figure in first order asymptotics for these estimators, they do influence second-order terms and it is shown how suitable choices will enhance second-order efficiency. Data-based bandwidth selection rules are given for practical implementation of these procedures. Two commonly used and asymptotically equivalent spectral regression estimators are studied and shown to differ in their second-order asymptotic behavior. Some Monte Carlo evidence is reported.