When are Direct Multi-step and Iterative Forecasts Identical?

被引:5
作者
McElroy, Tucker [1 ]
机构
[1] US Bur Census, Ctr Stat Res & Methodol, Washington, DC 20233 USA
关键词
ARIMA models; econometric models; long-term forecasting; seasonality; spectral analysis; time series; TIME-SERIES MODELS; AUTOREGRESSIVE PROCESSES; AR METHODS; SELECTION; PREDICTION; ORDER;
D O I
10.1002/for.2321
中图分类号
F [经济];
学科分类号
02 ;
摘要
Although both direct multi-step-ahead forecasting and iterated one-step-ahead forecasting are two popular methods for predicting future values of a time series, it is not clear that the direct method is superior in practice, even though from a theoretical perspective it has lower mean squared error (MSE). A given model can be fitted according to either a multi-step or a one-step forecast error criterion, and we show here that discrepancies in performance between direct and iterative forecasting arise chiefly from the method of fitting, and is dictated by the nuances of the model's misspecification. We derive new formulas for quantifying iterative forecast MSE, and present a new approach for assessing asymptotic forecast MSE. Finally, the direct and iterative methods are compared on a retail series, which illustrates the strengths and weaknesses of each approach. Copyright (C) 2015 John Wiley & Sons, Ltd.
引用
收藏
页码:315 / 336
页数:22
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