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Understanding errors in EIA projections of energy demand

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  • Fischer, Carolyn
  • Herrnstadt, Evan
  • Morgenstern, Richard

Abstract

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 mid-term projections of energy demand. Based on 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 after controlling for projection errors in gross domestic product, oil prices, and heating/cooling degree days. For 14 individual fuels/consuming sectors routinely reported by the EIA, we observe a great deal of directional consistency in the errors over time, ranging up to 7 percent per year. Electric utility renewables, electric utility natural gas, transportation distillate, and residential electricity show significant biases on average. Projections for certain other sectors have significant unexplained errors for selected time horizons. Such independent evaluation can be useful for validating analytic efforts and for prioritizing future model revisions.

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Bibliographic Info

Article provided by Elsevier in its journal Resource and Energy Economics.

Volume (Year): 31 (2009)
Issue (Month): 3 (August)
Pages: 198-209

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Handle: RePEc:eee:resene:v:31:y:2009:i:3:p:198-209

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Web page: http://www.elsevier.com/locate/inca/505569

Related research

Keywords: EIA Energy forecasting Bias;

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References

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  1. Tom Stark and Dean Croushore, 2001. "Forecasting with a Real-Time Data Set for Macroeconomists," Computing in Economics and Finance 2001 258, Society for Computational Economics.
  2. Auffhammer, Maximilian, 2007. "The rationality of EIA forecasts under symmetric and asymmetric loss," Resource and Energy Economics, Elsevier, vol. 29(2), pages 102-121, 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. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  5. 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.
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Cited by:
  1. Huntington, Hillard G., 2011. "Backcasting U.S. oil demand over a turbulent decade," Energy Policy, Elsevier, vol. 39(9), pages 5674-5680, September.
  2. Wilkerson, Jordan T. & Cullenward, Danny & Davidian, Danielle & Weyant, John P., 2013. "End use technology choice in the National Energy Modeling System (NEMS): An analysis of the residential and commercial building sectors," Energy Economics, Elsevier, vol. 40(C), pages 773-784.

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