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Real-Time Analysis of Oil Price Risks Using Forecast Scenarios

  • Baumeister, Christiane
  • Kilian, Lutz

Recently, there has been increased interest in real-time forecasts of the real price of crude oil. Standard oil price forecasts based on reduced-form regressions or based on oil futures prices do not allow consumers of forecasts to explore how much the forecast would change relative to the baseline forecast under alternative scenarios about future oil demand and oil supply conditions. Such scenario analysis is of central importance for end-users of oil price forecasts interested in evaluating the risks underlying these forecasts. We show how policy-relevant forecast scenarios can be constructed from recently proposed structural vector autoregressive models of the global oil market and how changes in the probability weights attached to these scenarios affect the upside and downside risks embodied in the baseline real-time oil price forecast. Such risk analysis helps forecast users understand what assumptions are driving the forecast. An application to real-time data for December 2010 illustrates the use of these tools in conjunction with reduced-form vector autoregressive forecasts of the real price of oil, the superior real-time forecast accuracy of which has recently been established.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 8698.

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Date of creation: Dec 2011
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Handle: RePEc:cpr:ceprdp:8698
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  1. Domenico Giannone & Lucrezia Reichlin, 2006. "Does information help recovering structural shocks from past observations?," Journal of the European Economic Association, MIT Press, vol. 4(2-3), pages 455-465, 04-05.
  2. Lutz Kilian, 2008. "Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy?," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 216-240, May.
  3. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-69, June.
  4. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  5. Kilian, Lutz & Murphy, Daniel P, 2009. "Why Agnostic Sign Restrictions Are Not Enough: Understanding the Dynamics of Oil Market VAR Models," CEPR Discussion Papers 7471, C.E.P.R. Discussion Papers.
  6. Christiane Baumeister & Gert Peersman, 2011. "The Role of Time-Varying Price Elasticities in Accounting for Volatility Changes in the Crude Oil Market," Working Papers 11-28, Bank of Canada.
  7. Lutz Kilian & Simone Manganelli, 2007. "Quantifying the Risk of Deflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2-3), pages 561-590, 03.
  8. Martin Bodenstein & Luca Guerrieri, 2011. "Oil efficiency, demand, and prices: a tale of ups and downs," International Finance Discussion Papers 1031, Board of Governors of the Federal Reserve System (U.S.).
  9. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
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