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Real-Time Forecasts of the Real Price of Oil

  • Baumeister, Christiane
  • Kilian, Lutz

We construct a monthly real-time data set consisting of vintages for 1991.1-2010.12 that is suitable for generating forecasts of the real price of oil from a variety of models. We document that revisions of the data typically represent news, and we introduce backcasting and nowcasting techniques to fill gaps in the real-time data. We show that real-time forecasts of the real price of oil can be more accurate than the no-change forecast at horizons up to one year. In some cases real-time MSPE reductions may be as high as 25 percent one month ahead and 24 percent three months ahead. This result is in striking contrast to related results in the literature for asset prices. In particular, recursive vector autoregressive (VAR) forecasts based on global oil market variables tend to have lower MSPE at short horizons than forecasts based on oil futures prices, forecasts based on AR and ARMA models, and the no-change forecast. In addition, these VAR models have consistently higher directional accuracy. We demonstrate how with additional identifying assumptions such VAR models may be used not only to understand historical fluctuations in the real price of oil, but to construct conditional forecasts that reflect hypothetical scenarios about future demand and supply conditions in the market for crude oil. These tools are designed to allow forecasters to interpret their oil price forecast in light of economic models and to evaluate its sensitivity to alternative assumptions.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 8414.

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Date of creation: Jun 2011
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Handle: RePEc:cpr:ceprdp:8414
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  1. Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the Price of Oil," Working Papers 11-15, Bank of Canada.
  2. Kilian, Lutz & Vega, Clara, 2008. "Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices," CEPR Discussion Papers 7015, C.E.P.R. Discussion Papers.
  3. Kilian, Lutz & Murphy, Daniel P, 2010. "The Role of Inventories and Speculative Trading in the Global Market for Crude Oil," CEPR Discussion Papers 7753, C.E.P.R. Discussion Papers.
  4. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers 0004, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  5. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000. "The use and abuse of "real-time" data in economic forecasting," Working Papers 0004, Federal Reserve Bank of Dallas.
  6. Kilian, Lutz, 2005. "Exogenous Oil Supply Shocks: How Big Are They and How Much do they Matter for the US Economy?," CEPR Discussion Papers 5131, C.E.P.R. Discussion Papers.
  7. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  8. Todd E. Clark & Michael W. McCracken, 2007. "Tests of equal predictive ability with real-time data," Research Working Paper RWP 07-06, Federal Reserve Bank of Kansas City.
  9. Kilian, Lutz, 2006. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," CEPR Discussion Papers 5994, C.E.P.R. Discussion Papers.
  10. Alquist, Ron & Kilian, Lutz, 2007. "What Do We Learn from the Price of Crude Oil Futures?," CEPR Discussion Papers 6548, C.E.P.R. Discussion Papers.
  11. Domenico Giannone & Michèle Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," Working Papers ECARES ECARES 2012-002, ULB -- Universite Libre de Bruxelles.
  12. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
  13. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  14. Domenico Giannone & Lucrezia Reichlin, 2006. "Does information help recovering structural shocks from past observations?," ULB Institutional Repository 2013/166169, ULB -- Universite Libre de Bruxelles.
  15. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, 08.
  16. C. Baumeister & G. Peersman & -, 2010. "Sources of the Volatility Puzzle in the Crude Oil Market," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/634, Ghent University, Faculty of Economics and Business Administration.
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