FINITE-SAMPLE PROPERTIES OF FORECASTS FROM THE STATIONARY FIRST-ORDER AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION
研究了在一般误差分布下，平稳一阶自回归模型的多期最小二乘预测的有限样本性质，发现预测无偏性至O(T−1)阶，均方预测误差至O(T−3/2)阶对非正态性稳健。
We study the properties of the multi-period-ahead least-squares forecast for the stationary AR(1) model under a general error distribution. We find that the forecast is unbiased up to O(T−1), where T is the in-sample size, regardless of the error distribution and that the mean squared forecast error, up to O(T−3/2), is robust against nonnormality.The author is grateful to the co-editor Paolo Paruolo and two anonymous referees for helpful comments. The author is solely responsible for any remaining errors.