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What Central Bankers Need To Know About Forecasting Oil Prices

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  • Christiane Baumeister
  • Lutz Kilian

Abstract

Central banks routinely use short‐horizon forecasts of the quarterly price of oil in assessing the global and domestic economic outlook. We address a number of econometric issues specific to the construction of quarterly oil price forecasts in the United States and abroad. We show that quarterly forecasts of the real price of oil from suitably designed vector autoregressive models estimated on monthly data generate the most accurate real‐time forecasts overall among a wide range of methods, including quarterly averages of forecasts based on monthly oil futures prices, no‐change forecasts, and forecasts based on regression models estimated on quarterly data.

Suggested Citation

  • Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.
    • Handle: RePEc:wly:iecrev:v:55:y:2014:i:3:p:869-889
    DOI: 10.1111/iere.12074
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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