Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries
油价能否帮助预测美国实际 GDP？非线性与非对称性的作用AI 解读 ↓
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油价能否帮助预测美国实际 GDP？非线性与非对称性的作用
- 研究问题
- 油价与美国实际 GDP 的非线性、非对称预测关系能否改善样本外预测，在更长预测期和二〇〇八年衰退中表现如何？
- 方法与思路
- 作者比较不同油价变换和经济上合理的非线性模型，扩展预测期限，并考察基于三年净油价变化的时变阈值模型。
- 材料陈述的贡献
- 摘要称，常用油价变换中的非对称性无助于样本外预测；对称非线性模型给出更稳健且往往更准确的 GDP 预测。
- 阅读关注点
- 核对样本外评估窗口、基准模型、预测期限与误差指标，并查看阈值设定及二〇〇八年衰退预测的具体证据。
- 阅读边界
- 仅依据所给 OpenAlex 摘要；未提供预测误差数值、显著性检验或衰退预测结果，预测关系也不能直接解释为油价的因果效应。
原文摘要
There is a long tradition of using oil prices to forecast U.S. real GDP. It has been suggested that the predictive relationship between the price of oil and one-quarter-ahead U.S. real GDP is nonlinear in that (a) oil price increases matter only to the extent that they exceed the maximum oil price in recent years, and that (b) oil price decreases do not matter at all. We examine, first, whether the evidence of in-sample predictability in support of this view extends to out-of-sample forecasts. Second, we discuss how to extend this forecasting approach to higher horizons. Third, we compare the resulting class of nonlinear models to alternative economically plausible nonlinear specifications and examine which aspect of the model is most useful for forecasting. We show that the asymmetry embodied in commonly used nonlinear transformations of the price of oil is not helpful for out-of-sample forecasting; more robust and often more accurate real GDP forecasts are obtained from symmetric nonlinear models based on the 3-year net oil price change. Finally, we quantify the extent to which the 2008 recession could have been forecast using the latter class of time-varying threshold models.