Forecasting Contemporaneously Aggregated Vector ARMA Processes
研究多变量ARMA过程生成的多元时间序列，在均方误差准则下，比较直接预测聚合序列与先预测各分量再聚合的优劣，发现已知过程时后者更优，但估计过程时结论不成立，并用经济数据验证。
Given a multiple time series that is generated by a multivariate ARMA process and assuming the objective is to forecast a weighted sum of the individual variables, then under a mean squared error measure of forecasting precision, it is preferable to forecast the disaggregated multiple time series and aggregate the forecasts, rather than forecast the aggregated series directly, if the involved processes are known. This result fails to hold if the processes used for forecasting are estimated from a given set of time series data. The implications of these results for empirical research are investigated using different sets of economic data.