Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries
AbstractThere 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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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business & Economic Statistics.
Volume (Year): 31 (2013)
Issue (Month): 1 (January)
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Other versions of this item:
- Lutz Kilian & Robert J. Vigfusson, 2012. "Do oil prices help forecast U.S. real GDP? the role of nonlinearities and asymmetries," International Finance Discussion Papers 1050, Board of Governors of the Federal Reserve System (U.S.).
- Kilian, Lutz & Vigfusson, Robert J., 2012. "Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries," CEPR Discussion Papers 8980, C.E.P.R. Discussion Papers.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
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