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Oil and US GDP: A real-time out-of-sample examination

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  • Francesco Ravazzolo

    ()
    (Norges Bank (Central Bank of Norway))

  • Philip Rothman

    ()
    (East Carolina University)

Abstract

We study the real-time Granger-causal relationship between crude oil prices and US GDP growth through a simulated out-of-sample (OOS) forecasting exercise; we also provide strong evidence of in-sample predictability from oil prices to GDP. Comparing our benchmark model "without oil" against alternatives "with oil," we strongly reject the null hypothesis of no OOS predictability from oil prices to GDP via our point forecast comparisons from the mid-1980s through the Great Recession. Further analysis shows that these results may be due to our oil price measures serving as proxies for a recently developed measure of global real economic activity omitted from the alternatives to the benchmark forecasting models in which we only use lags of GDP growth. By way of density forecast OOS comparisons, we find evidence of such oil price predictability for GDP for our full 1970-2009 OOS period. Examination of the density forecasts reveals a massive increase in forecast uncertainty following the 1973 post-Yom Kippur War crude oil price increases.

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Bibliographic Info

Paper provided by Norges Bank in its series Working Paper with number 2010/18.

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Length: 25 pages
Date of creation: 15 Sep 2010
Date of revision:
Handle: RePEc:bno:worpap:2010_18

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Citations

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Cited by:
  1. Claudio Morana, 2012. "The Oil price-Macroeconomy Relationship since the Mid- 1980s: A global perspective," Working Papers 2012.28, Fondazione Eni Enrico Mattei.
  2. Kilian, Lutz & Vigfusson, Robert J., 2014. "The role of oil price shocks in causing U.S. recessions," CFS Working Paper Series 460, Center for Financial Studies (CFS).
  3. Lutz Kilian & Robert J. Vigfusson, 2013. "Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 78-93, January.
  4. Granziera, Eleonora & Hubrich, Kirstin & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
  5. Gaye Gencer & Sercan Demiralay, 2013. "The Impact of Oil Prices on Sectoral Returns: An Empirical Analysis from Borsa Istanbul," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 245, Ekonomik Yaklasim Association.
  6. Christiane Baumeister & Lutz Kilian, 2011. "Real-Time Forecasts of the Real Price of Oil," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 326-336, September.
  7. Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the price of oil," International Finance Discussion Papers 1022, Board of Governors of the Federal Reserve System (U.S.).
  8. Fan, Qinbin & Jahan-Parvar, Mohammad R., 2012. "U.S. industry-level returns and oil prices," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 112-128.
  9. Hamilton, James D., 2011. "Nonlinearities And The Macroeconomic Effects Of Oil Prices," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 364-378, November.
  10. James D. Hamilton, 2012. "Oil Prices, Exhaustible Resources, and Economic Growth," NBER Working Papers 17759, National Bureau of Economic Research, Inc.

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