Serial Correlation and the Combination of Forecasts
证明基于回归的预测组合方法会产生序列相关的组合预测误差，刻画了该序列相关形式，并开发了一种利用序列相关性的最优组合预测器，数值例子显示其能降低均方预测误差。
It is shown that regression-based methods of forecast combination lead to serially correlated combined prediction errors. The form of the serial correlation is characterized, and specification, estimation, and prediction are treated. A fully optimal combined predictor, which exploits the serial correlation, is developed and compared with existing regression-based methods in a numerical example, leading to decreases in mean squared prediction error.