4.5 Article

Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries

Journal

JOURNAL OF BUSINESS & ECONOMIC STATISTICS
Volume 31, Issue 1, Pages 78-93

Publisher

AMER STATISTICAL ASSOC
DOI: 10.1080/07350015.2012.740436

Keywords

Asymmetry; Nonlinearity; Out-of-sample forecast

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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.

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