Targeted growth rates for long-horizon crude oil price forecasts
提出一种通过目标滞后选择来改进长期预测精度的增长率变换方法，应用于原油实际价格模型，可将五年期预测精度提升至此前仅短期能达到的水平。
This paper proposes growth rate transformations with targeted lag selection in order to improve the long-horizon forecast accuracy. The method targets lower frequencies of the data that correspond to particular forecast horizons, and is applied to models of the real price of crude oil. Targeted growth rates can improve the forecast precision significantly at horizons of up to five years. For the real price of crude oil, the method can achieve a degree of accuracy up to five years ahead that previously has been achieved only at shorter horizons.