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The rationality of EIA forecasts under symmetric and asymmetric loss

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  • Auffhammer, Maximilian

Abstract

The 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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  • 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.
    • Handle: RePEc:eee:resene:v:29:y:2007:i:2:p:102-121
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    3. Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2016. "Commodity Price Forecasts, Futures Prices and Pricing Models," NBER Working Papers 22991, National Bureau of Economic Research, Inc.
    4. Bastianin, Andrea & Manera, Matteo & Markandya, Anil & Scarpa, Elisa, 2011. "Oil Price Forecast Evaluation with Flexible Loss Functions," Energy: Resources and Markets 120042, Fondazione Eni Enrico Mattei (FEEM).
    5. Rülke, Jan-Christoph & Pierdzioch, Christian, 2014. "Government Forecasts of Budget Balances Under Asymmetric Loss: International Evidence," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100317, Verein für Socialpolitik / German Economic Association.
    6. Mamatzakis, E. & Koutsomanoli-Filippaki, A., 2014. "Testing the rationality of DOE's energy price forecasts under asymmetric loss preferences," Energy Policy, Elsevier, vol. 68(C), pages 567-575.
    7. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts," MPRA Paper 114325, University Library of Munich, Germany.
    8. Fischer, Carolyn & Herrnstadt, Evan & Morgenstern, Richard, 2009. "Understanding errors in EIA projections of energy demand," Resource and Energy Economics, Elsevier, vol. 31(3), pages 198-209, August.
    9. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    10. 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.
    11. Christoph Jeßberger, 2011. "Multilateral Environmental Agreements up to 2050: Are They Sustainable Enough?," ifo Working Paper Series 98, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    12. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2023. "Asymmetry and interdependence when evaluating U.S. Energy Information Administration forecasts," Energy Economics, Elsevier, vol. 121(C).
    13. Christian Pierdzioch & Jan C Rülke & Georg Stadtmann, 2012. "Forecasting the Dollar/British Pound Exchange Rate: Asymmetric Loss and Forecast Rationality," Economics Bulletin, AccessEcon, vol. 32(3), pages 213-213.
    14. Haoran Zhao & Sen Guo & Huiru Zhao, 2017. "Energy-Related CO 2 Emissions Forecasting Using an Improved LSSVM Model Optimized by Whale Optimization Algorithm," Energies, MDPI, vol. 10(7), pages 1-15, June.
    15. Kialashaki, Arash & Reisel, John R., 2014. "Development and validation of artificial neural network models of the energy demand in the industrial sector of the United States," Energy, Elsevier, vol. 76(C), pages 749-760.
    16. Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2019. "Commodity Price Forecasts, Futures Prices, and Pricing Models," Management Science, INFORMS, vol. 65(9), pages 4141-4155, September.
    17. Wang, Fangzhi & Liao, Hua, 2022. "Unexpected economic growth and oil price shocks," Energy Economics, Elsevier, vol. 116(C).
    18. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "On the loss function of the Bank of Canada: A note," Economics Letters, Elsevier, vol. 115(2), pages 155-159.
    19. Gholam Hossein Hasantash & Hamidreza Mostafaei & Shaghayegh Kordnoori, 2012. "Modelling the Errors of EIA's Oil Prices and Production Forecasts by the Grey Markov Model," International Journal of Economics and Financial Issues, Econjournals, vol. 2(3), pages 312-319.
    20. James G. Baldwin & Ian Sue Wing, 2013. "The Spatiotemporal Evolution Of U.S. Carbon Dioxide Emissions: Stylized Facts And Implications For Climate Policy," Journal of Regional Science, Wiley Blackwell, vol. 53(4), pages 672-689, October.
    21. Wachtmeister, Henrik & Henke, Petter & Höök, Mikael, 2018. "Oil projections in retrospect: Revisions, accuracy and current uncertainty," Applied Energy, Elsevier, vol. 220(C), pages 138-153.

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