Real-Time Forecasts of the Real Price of Oil

We construct a monthly real-time dataset 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 1 year. In some cases, real-time mean squared prediction error (MSPE) reductions may be as high as 25% 1 month ahead and 24% 3 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 autoregressive (AR) and autoregressive moving average (ARMA) models, and the no-change forecast. In addition, these VAR models have consistently higher directional accuracy.

[1]  Clara Vega,et al.  Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices , 2008, Review of Economics and Statistics.

[2]  Domenico Giannone,et al.  Does Information Help Recovering Structural Shocks from Past Observations? , 2006, SSRN Electronic Journal.

[3]  Jonathan H. Wright,et al.  Federal Reserve Board , 2000 .

[4]  Lutz Kilian,et al.  Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003-2008? , 2009 .

[5]  L. Kilian,et al.  Why Agnostic Sign Restrictions are not Enough: Understanding the Dynamics of Oil Market VAR Models , 2009 .

[6]  D. H. Mellor,et al.  Real time , 1981 .

[7]  G. Peersman,et al.  Sources of the Volatility Puzzle in the Crude Oil Market , 2009 .

[8]  L. Kilian,et al.  What Do We Learn from the Price of Crude Oil Futures? , 2007 .

[9]  L. Kilian.  Not All Oil Price Shocks are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market , 2006 .

[10]  R Long,et al.  Use and abuse. , 1978, Nursing times.

[11]  Knut Anton Mork,et al.  Oil and the Macroeconomy When Prices Go Up and Down: An Extension of Hamilton's Results , 1989, Journal of Political Economy.

[12]  Daniel F. Waggoner,et al.  Conditional Forecasts in Dynamic Multivariate Models , 1998, Review of Economics and Statistics.

[13]  M. Hashem Pesaran,et al.  Testing Dependence Among Serially Correlated Multicategory Variables , 2006, SSRN Electronic Journal.

[14]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

[15]  Dean D. Croushore,et al.  Frontiers of Real-Time Data Analysis , 2008 .

[16]  Lutz Kilian,et al.  Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy? , 2005, The Review of Economics and Statistics.

[17]  A. Timmermann,et al.  Predictability of Stock Returns: Robustness and Economic Significance , 1995 .

[18]  Todd E. Clark,et al.  Tests of equal predictive ability with Real-Time data. Discussion paper , 2007 .

[19]  Jeremy Piger,et al.  The Use and Abuse of Real-Time Data in Economic Forecasting , 2003, Review of Economics and Statistics.

[20]  Rational Economic Data Revisions , 1987 .

[21]  C. Dunis,et al.  Exchange Rate Forecasting , 1990 .

[22]  Michael P. Clements,et al.  Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions , 2010 .

[23]  L. Kilian,et al.  Real-Time Analysis of Oil Price Risks Using Forecast Scenarios , 2011 .

[24]  Jonathan H. Wright,et al.  Exchange Rate Forecasting: The Errors We've Really Made , 2001 .

[25]  Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices , 2008 .

[26]  Lutz Kilian,et al.  Forecasting the Price of Oil , 2010 .

[27]  F. Ravazzolo,et al.  Oil and US GDP: A Real-Time Out-of-Sample Examination , 2010 .

[28]  Lutz Kilian,et al.  The Role of Inventories and Speculative Trading in the Global Market for Crude Oil , 2010 .

[29]  Dean Croushore,et al.  Forecasting with Real-Time Macroeconomic Data , 2006 .