The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss
AbstractThe United States Energy Information Administration publishes annual forecasts of nationally aggregated energy consumption, production, prices, intensity and GDP. These government issued forecasts often serve as reference cases in the calibration of simulation and econometric models, which climate and energy policy are based on. This study tests for rationality of published EIA forecasts under symmetric and asymmetric loss. We find strong empirical evidence of asymmetric loss for oil, coal and gas prices as well as natural gas consumption, GDP and energy intensity.
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Bibliographic InfoPaper provided by Department of Agricultural & Resource Economics, UC Berkeley in its series Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series with number qt2ts415ts.
Date of creation: 16 Dec 2005
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Forecasting; Asymmetric Loss; Energy Intensity; Energy Information Administration; Life Sciences;
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- Christopher Yang & Stephen Schneider, 1998. "Global Carbon Dioxide Emissions Scenarios: Sensitivity to Social and Technological Factors in Three Regions," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 2(4), pages 373-404, December.
- Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996.
"Efficient Tests for an Autoregressive Unit Root,"
Econometric Society, vol. 64(4), pages 813-36, July.
- Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
- Tom Doan, . "GLSDETREND: RATS procedure to perform local to unity GLS detrending," Statistical Software Components RTS00077, Boston College Department of Economics.
- Tom Doan, . "ERSTEST: RATS procedure to perform Elliott-Rothenberg-Stock unit root tests," Statistical Software Components RTS00066, Boston College Department of Economics.
- 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.
- Andy S. Kydes, 1999. "Energy Intensity and Carbon Emission Responses to Technological Change: The U.S. Outlook," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 93-121.
- 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.
- Sands, Ronald D., 2004. "Dynamics of carbon abatement in the Second Generation Model," Energy Economics, Elsevier, vol. 26(4), pages 721-738, July.
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