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Improving Long-Range Energy Modeling: A Plea for Historical Retrospectives

Author

Listed:
  • Jonathan Koomey
  • Paul Craig
  • Ashok Gadgil
  • David Lorenzetti

Abstract

One of the most striking things about forecasters is their lack of historical perspective. They rarely do retrospectives, even though looking back at past work can both illuminate the reasons for its success or failure, and improve the methodologies of current and future forecasts. One of the best and most famous retrospectives is that by Hans Landsberg, which investigates work conducted by Landsberg, Sam Schurr, and others. In this article, written mainly for model users, we highlight Landsberg s retrospective as a uniquely valuable contribution to improving forecasting methodologies. We also encourage model users to support such retrospectives more frequently. Finally, we give the current generation of analysts the kind of guidance we believe Landsberg and Sam Schurr would have offered about how to do retrospectives well.

Suggested Citation

  • Jonathan Koomey & Paul Craig & Ashok Gadgil & David Lorenzetti, 2003. "Improving Long-Range Energy Modeling: A Plea for Historical Retrospectives," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 75-92.
    • Handle: RePEc:aen:journl:2003v24-04-a04
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    Cited by:

    1. Glotin, David & Bourgeois, Cyril & Giraudet, Louis-Gaëtan & Quirion, Philippe, 2019. "Prediction is difficult, even when it's about the past: A hindcast experiment using Res-IRF, an integrated energy-economy model," Energy Economics, Elsevier, vol. 84(S1).
    2. Danny Cullenward & Lee Schipper & Anant Sudarshan & Richard Howarth, 2011. "Psychohistory revisited: fundamental issues in forecasting climate futures," Climatic Change, Springer, vol. 104(3), pages 457-472, February.
    3. Sohn, Ira, 2007. "Long-term energy projections: What lessons have we learned?," Energy Policy, Elsevier, vol. 35(9), pages 4574-4584, September.
    4. Kuchler, Magdalena & Höök, Mikael, 2020. "Fractured visions: Anticipating (un)conventional natural gas in Poland," Resources Policy, Elsevier, vol. 68(C).
    5. 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.
    6. 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.
    7. Sukanya Ghosh & P.P. Sengupta & Biman Maity, 2012. "Evidence On The Future Prospects Of Indian Thermal Power Sector In The Perspective Of Depleting Coal Reserve," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 6(1), pages 77-89.
    8. Koomey, Jonathan & Hultman, Nathan E., 2007. "A reactor-level analysis of busbar costs for US nuclear plants, 1970-2005," Energy Policy, Elsevier, vol. 35(11), pages 5630-5642, November.
    9. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    10. Charlie Wilson & Céline Guivarch & Elmar Kriegler & Bas Ruijven & Detlef P. Vuuren & Volker Krey & Valeria Jana Schwanitz & Erica L. Thompson, 2021. "Evaluating process-based integrated assessment models of climate change mitigation," Climatic Change, Springer, vol. 166(1), pages 1-22, May.
    11. 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.
    12. Irene Scher & Jonathan Koomey, 2011. "Is accurate forecasting of economic systems possible?," Climatic Change, Springer, vol. 104(3), pages 473-479, February.
    13. Baomin Dong & Xuefeng Li & Boqiang Lin, 2010. "Forecasting Long-Run Coal Price in China: A Shifting Trend Time-Series Approach," Review of Development Economics, Wiley Blackwell, vol. 14(s1), pages 499-519, August.

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    JEL classification:

    • F0 - International Economics - - General

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