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Evaluating long term forecasts

Author

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  • Lady, George M.

Abstract

The U.S. Department of Energy's Energy Information Administration (EIA), and its predecessor organizations, has published projections of U.S. energy production, consumption, distribution and prices annually for over 30Â years. A natural issue to raise in evaluating the projections is an assessment of their accuracy compared to eventual outcomes. A related issue is the determination of the sources of "error" in the projections that are due to differences between the actual versus realized values of the associated assumptions. One way to do this would be to run the computer-based model from which the projections are derived at the time the projected values are realized, using actual rather than assumed values for model assumptions; and, compare these results to the original projections. For long term forecasts, this approach would require that the model's software and hardware configuration be archived and available for many years, possibly decades, into the future. Such archival creates many practical problems; and, in general, it is not being done. This paper reports on an alternative approach for evaluating the projections. In the alternative approach, the model is run many times for cases in which important assumptions are changed individually and in combinations. A database is assembled from the solutions and a regression analysis is conducted for each important projected variable with the associated assumptions chosen as exogenous variables. When actual data are eventually available, the regression results are then used to estimate the sources of the differences in the projections of the endogenous variables compared to their eventual outcomes. The results presented here are for residential and commercial sector natural gas and electricity consumption.

Suggested Citation

  • Lady, George M., 2010. "Evaluating long term forecasts," Energy Economics, Elsevier, vol. 32(2), pages 450-457, March.
    • Handle: RePEc:eee:eneeco:v:32:y:2010:i:2:p:450-457
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    References listed on IDEAS

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    1. James M. Griffin, 1977. "Long-Run Production Modeling with Pseudo Data: Electric Power Generation," Bell Journal of Economics, The RAND Corporation, vol. 8(1), pages 112-127, Spring.
    2. Winebrake, James J. & Sakva, Denys, 2006. "An evaluation of errors in US energy forecasts: 1982-2003," Energy Policy, Elsevier, vol. 34(18), pages 3475-3483, December.
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    Cited by:

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    3. Liao, Hua & Cai, Jia-Wei & Yang, Dong-Wei & Wei, Yi-Ming, 2016. "Why did the historical energy forecasting succeed or fail? A case study on IEA's projection," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 90-96.
    4. Hal T. Nelson & David von Hippel & Tom Peterson & Roman Garagulagian, 2016. "The Great Recession or progressive energy policies? Explaining the decline in US greenhouse gas emissions forecasts," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 59(3), pages 480-500, March.
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    6. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts," National Institute of Economic and Social Research (NIESR) Discussion Papers 541, National Institute of Economic and Social Research.
    7. 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.
    8. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2023. "Asymmetry and interdependence when evaluating U.S. Energy Information Administration forecasts," Energy Economics, Elsevier, vol. 121(C).

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