In this paper, we propose a new heteroskedasticity and autocorrelation consistent covariance matrix estimator based on the prewhitened kernel estimator and a localized leave-one-out frequency domain cross-validation (FDCV). We adapt the cross-validated log likelihood (CVLL) function to simultaneously select the order of the prewhitening vector autoregression (VAR) and the bandwidth. The prewhitening VAR is estimated by the Burg method without eigen adjustment as we find the eigen adjustment rule of Andrews and Monahan (1992) can be triggered unnecessarily and harmfully when regressors have nonzero mean. Through Monte Carlo simulations and three empirical examples, we illustrate the flaws of eigen adjustment and the reliability of our method.

翻译：本文基于预白化核估计器及局部留一频域交叉验证(FDCV)，提出了一种新的异方差与自相关一致协方差矩阵估计量。我们采用交叉验证对数似然(CVLL)函数来同时选择预白化向量自回归(VAR)的阶数与带宽。预白化VAR通过Burg方法进行估计且不进行特征调整，因为我们发现当回归变量具有非零均值时，Andrews和Monahan（1992）的特征调整规则可能被不必要且有害地触发。通过蒙特卡洛模拟与三个实证案例，我们阐明了特征调整的缺陷以及本方法的可靠性。