Small-Sample Properties of Predictions from the Regression Model with Autoregressive Errors
用蒙特卡洛方法研究了自回归误差回归模型中预测方差估计量的小样本性质，比较了两种估计量在不同样本量和预测期数下的表现，发现包含参数估计项的估计量在小样本中更优。
Abstract Monte Carlo methods are used to examine the small-sample properties of various estimators of asymptotic prediction variance (APV) from the regression model with autoregressive errors. Two practical estimators of APV, one of which includes terms reflecting parameter estimation and one of which excludes these terms, are compared to the mean squared error of prediction for regression models with different autocorrelation of the errors, different sample sizes, and different period-ahead predictions. The inclusion of terms reflecting the estimation of parameters is found to be worthwhile, particularly in small samples.