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Oil and US GDP: A Real-Time out-of Sample Examination

Listed author(s):
  • Francesco Ravazzolo
  • Philip Rothman

We study the real-time predictive content of crude oil prices for US real GDP growth through a pseudo out-of-sample (OOS) forecasting exercise. Comparing our benchmark model ?withoutoil? against alternatives ?with oil,? we strongly reject the null hypothesis of no OOS population-level predictability from oil prices to GDP at the longer forecast horizon we consider. 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. This examination of the global OOS relative performance of the models we consider is robust to use of ex-post revised data. But when we focus on the forecasting models? local relative performance, we observe strong differences across use of real-time and ex-post revised data.

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Paper provided by Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School in its series Working Papers with number 0004.

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Length: 23 pages
Date of creation: Nov 2011
Handle: RePEc:bny:wpaper:0004
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