Band Covariance Matrix Estimation Using Restricted Residuals: A Monte Carlo Analysis
通过蒙特卡洛模拟，比较了基于不同版本异方差一致带状协方差矩阵估计量的Wald检验统计量表现，发现使用受限残差而非普通OLS残差可大幅减少过度第一类错误。
Using Monte Carlo simulations, the authors examine the performance of Wald-type test statistics based on alternative versions of a heteroskedasticity consistent band covariance matrix estimator that is algorithmically constrained to be positive definite in finite samples. They find that the test statistic based on the originally proposed estimator tends to result in excessive type I errors. This problem can be alleviated to some extent by employing a quasi-maximum likelihood procedure. However, by simply using restricted, as opposed to the usual OLS residuals when constructing the band covariance matrix estimator, excessive type I errors can be substantially reduced, if not eliminated. Copyright 1995 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.