IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v34y2006i18p3475-3483.html
   My bibliography  Save this article

An evaluation of errors in US energy forecasts: 1982-2003

Author

Listed:
  • Winebrake, James J.
  • Sakva, Denys

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:enepol:v:34:y:2006:i:18:p:3475-3483
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(05)00203-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Linderoth, Hans, 2002. "Forecast errors in IEA-countries' energy consumption," Energy Policy, Elsevier, vol. 30(1), pages 53-61, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mazen Labban, 2012. "Preempting Possibility: Critical Assessment of the IEA's World Energy Outlook 2010," Development and Change, International Institute of Social Studies, vol. 43(1), pages 375-393, January.
    2. 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.
    3. Strachan, Neil & Pye, Steve & Kannan, Ramachandran, 2009. "The iterative contribution and relevance of modelling to UK energy policy," Energy Policy, Elsevier, vol. 37(3), pages 850-860, March.
    4. O' Mahony, Tadhg & Zhou, P. & Sweeney, John, 2013. "Integrated scenarios of energy-related CO2 emissions in Ireland: A multi-sectoral analysis to 2020," Ecological Economics, Elsevier, vol. 93(C), pages 385-397.
    5. al Irsyad, Muhammad Indra & Halog, Anthony & Nepal, Rabindra, 2019. "Renewable energy projections for climate change mitigation: An analysis of uncertainty and errors," Renewable Energy, Elsevier, vol. 130(C), pages 536-546.
    6. Liu, Xiaoyu & Cui, Qingbin, 2018. "Value of performance baseline in voluntary carbon trading under uncertainty," Energy, Elsevier, vol. 145(C), pages 468-476.
    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).
    9. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2022. "Accuracy indicators for evaluating retrospective performance of energy system models," Applied Energy, Elsevier, vol. 325(C).
    10. Millard-Ball, Adam, 2013. "The trouble with voluntary emissions trading: Uncertainty and adverse selection in sectoral crediting programs☆☆Special thanks to Suzi Kerr, Lawrence Goulder, Michael Wara, Arthur van Benthem, Lee Sch," Journal of Environmental Economics and Management, Elsevier, vol. 65(1), pages 40-55.
    11. J. Andrew Kelly & Herman R.J. Vollebergh, 2012. "Adaptive Policy Mechanisms for Transboundary Air Pollution Regulation: Reasons and Recommendations," Working Papers 2012.32, Fondazione Eni Enrico Mattei.
    12. Scheer, Dirk, 2017. "Communicating energy system modelling to the wider public: An analysis of German media coverage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1389-1398.
    13. 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.
    14. Lady, George M., 2010. "Evaluating long term forecasts," Energy Economics, Elsevier, vol. 32(2), pages 450-457, March.
    15. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2023. "Hindcasting to inform the development of bottom-up electricity system models: The cases of endogenous demand and technology learning," Applied Energy, Elsevier, vol. 340(C).
    16. Moret, Stefano & Codina Gironès, Víctor & Bierlaire, Michel & Maréchal, François, 2017. "Characterization of input uncertainties in strategic energy planning models," Applied Energy, Elsevier, vol. 202(C), pages 597-617.
    17. Huntington, Hillard G., 2011. "Backcasting U.S. oil demand over a turbulent decade," Energy Policy, Elsevier, vol. 39(9), pages 5674-5680, September.
    18. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2022. "Accuracy indicators for evaluating retrospective performance of energy system models," Applied Energy, Elsevier, vol. 325(C).
    3. 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.
    4. al Irsyad, Muhammad Indra & Halog, Anthony & Nepal, Rabindra, 2019. "Renewable energy projections for climate change mitigation: An analysis of uncertainty and errors," Renewable Energy, Elsevier, vol. 130(C), pages 536-546.
    5. Moret, Stefano & Codina Gironès, Víctor & Bierlaire, Michel & Maréchal, François, 2017. "Characterization of input uncertainties in strategic energy planning models," Applied Energy, Elsevier, vol. 202(C), pages 597-617.
    6. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    7. Auffhammer, Maximilian, 2005. "The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2ts415ts, Department of Agricultural & Resource Economics, UC Berkeley.
    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. Schmitt, Rafael Jan Pablo & Rosa, Lorenzo, 2024. "Dams for hydropower and irrigation: Trends, challenges, and alternatives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    10. Kenneth Gillingham & Marten Ovaere & Stephanie Weber, 2021. "Carbon Policy and the Emissions Implications of Electric Vehicles," CESifo Working Paper Series 8974, CESifo.
    11. Jie Ma & Amos Oppong & Kingsley Nketia Acheampong & Lucille Aba Abruquah, 2018. "Forecasting Renewable Energy Consumption under Zero Assumptions," Sustainability, MDPI, vol. 10(3), pages 1-17, February.
    12. Michel, David, 2009. "Foxes, hedgehogs, and greenhouse governance: Knowledge, uncertainty, and international policy-making in a warming World," Applied Energy, Elsevier, vol. 86(2), pages 258-264, February.
    13. Aydin, Gokhan, 2014. "Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 382-389.
    14. Frank Jotzo, 2006. "Quantifying uncertainties for emission targets," Economics and Environment Network Working Papers 0603, Australian National University, Economics and Environment Network.
    15. Reza Hafezi & Amir Naser Akhavan & Mazdak Zamani & Saeed Pakseresht & Shahaboddin Shamshirband, 2019. "Developing a Data Mining Based Model to Extract Predictor Factors in Energy Systems: Application of Global Natural Gas Demand," Energies, MDPI, vol. 12(21), pages 1-22, October.
    16. Fodstad, Marte & Crespo del Granado, Pedro & Hellemo, Lars & Knudsen, Brage Rugstad & Pisciella, Paolo & Silvast, Antti & Bordin, Chiara & Schmidt, Sarah & Straus, Julian, 2022. "Next frontiers in energy system modelling: A review on challenges and the state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    17. Shoaib Ahmed Khatri & Nayyar Hussain Mirjat & Khanji Harijan & Mohammad Aslam Uqaili & Syed Feroz Shah & Pervez Hameed Shaikh & Laveet Kumar, 2022. "An Overview of the Current Energy Situation of Pakistan and the Way Forward towards Green Energy Implementation," Energies, MDPI, vol. 16(1), pages 1-27, December.
    18. Huntington, Hillard G., 2011. "Backcasting U.S. oil demand over a turbulent decade," Energy Policy, Elsevier, vol. 39(9), pages 5674-5680, September.
    19. Bismark Ameyaw & Li Yao, 2018. "Sectoral Energy Demand Forecasting under an Assumption-Free Data-Driven Technique," Sustainability, MDPI, vol. 10(7), pages 1-20, July.
    20. Ludovic Gaudard & Jeannette Gabbi & Andreas Bauder & Franco Romerio, 2016. "Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1325-1343, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:34:y:2006:i:18:p:3475-3483. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.