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Understanding Errors in EIA Projections of Energy Demand

  • Fischer, Carolyn

    ()

    (Resources for the Future)

  • Herrnstadt, Evan
  • Morgenstern, Richard D.

This paper investigates the potential for systematic errors in the Energy Information Administration’s (EIA) widely used Annual Energy Outlook, focusing on the near- to midterm projections of energy demand as measured in physical quantities. Overall, based on an analysis of the EIA’s 22-year projection record, we find a fairly modest but persistent tendency to underestimate total energy demand by an average of 2 percent per year over the one- to five-year projection horizon after controlling for projection errors in gross domestic product, oil prices, and heating/cooling degree days. For the 14 individual fuels/consuming sectors routinely reported by the EIA, we observe a great deal of directional consistency in the error patterns over time, ranging up to 7 percent per year. Electric utility renewables, electric utility natural gas, transportation distillate, and residential electricity all show significant biases, on average, across the full five year projection horizon examined. Projections for certain other fuels/consuming sectors have significant unexplained errors for selected time horizons. Independent evaluation of this type can be useful for validating ongoing analytic efforts and for prioritizing future model revisions.

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Paper provided by Resources For the Future in its series Discussion Papers with number dp-08-54.

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Date of creation: 08 Nov 2008
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Handle: RePEc:rff:dpaper:dp-08-54
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  1. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  2. O'Neill, Brian C. & Desai, Mausami, 2005. "Accuracy of past projections of US energy consumption," Energy Policy, Elsevier, vol. 33(8), pages 979-993, May.
  3. Shlyakhter, Alexander I. & Kammen, Daniel M. & Broido, Claire L. & Wilson, Richard, 1994. "Quantifying the credibility of energy projections from trends in past data : The US energy sector," Energy Policy, Elsevier, vol. 22(2), pages 119-130, February.
  4. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  5. Randall Lutter, 2000. "Developing Countries' Greenhouse Emmissions: Uncertainty and Implications for Participation in the Kyoto Protocol," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 93-120.
  6. Auffhammer, Maximilian, 2005. "The rationality of EIA forecasts under symmetric and asymmetric loss," CUDARE Working Paper Series 1009, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
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