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Global warming: Forecasts by scientists versus scientific forecasts

Author

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  • Green, Kesten C.
  • Armstrong, J. Scott

Abstract

In 2007, the Intergovernmental Panel on Climate Change’s Working Group One, a panel of experts established by the World Meteorological Organization and the United Nations Environment Programme, issued its Fourth Assessment Report. The Report included predictions of dramatic increases in average world temperatures over the next 92 years and serious harm resulting from the predicted temperature increases. Using forecasting principles as our guide we asked: Are these forecasts a good basis for developing public policy? Our answer is “no.” To provide forecasts of climate change that are useful for policy-making, one would need to forecast (1) global temperature, (2) the effects of any temperature changes, (3) the effects of alternative policies, and (4) whether the best policy would be successfully implemented. Proper forecasts of all four are necessary for rational policy making. The IPCC Report was regarded as providing the most credible long-term forecasts of global average temperatures by 31 of the 51 scientists and others involved in forecasting climate change who responded to our survey. We found no references to the primary sources of information on forecasting methods despite the fact these are easily available in books, articles, and websites. We audited the forecasting processes described in Chapter 8 of the IPCC’s WG1 Report to assess the extent to which they complied with forecasting principles. We found enough information to make judgments on 89 out of a total of 140 forecasting principles. The forecasting procedures that were described violated 72 principles. Many of the violations were, by themselves, critical. The forecasts in the Report were not the outcome of scientific procedures. In effect, they were the opinions of scientists transformed by mathematics and obscured by complex writing. Research on forecasting has shown that experts’ predictions are not useful. We have been unable to identify any scientific forecasts of global warming. Claims that the Earth will get warmer have no more credence than saying that it will get colder.

Suggested Citation

  • Green, Kesten C. & Armstrong, J. Scott, 2007. "Global warming: Forecasts by scientists versus scientific forecasts," MPRA Paper 4361, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:4361
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    References listed on IDEAS

    as
    1. JS Armstrong, 2004. "Forecasting for Environmental Decision Making," General Economics and Teaching 0412023, EconWPA.
    2. Schnaars, Steven P. & Bavuso, R. Joseph, 1986. "Extrapolation models on very short-term forecasts," Journal of Business Research, Elsevier, vol. 14(1), pages 27-36, February.
    3. Armstrong, J. Scott, 2006. "Findings from evidence-based forecasting: Methods for reducing forecast error," International Journal of Forecasting, Elsevier, vol. 22(3), pages 583-598.
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    Citations

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    Cited by:

    1. J. Scott Armstrong & Kesten C. Green & Willie Soon, 2008. "Polar Bear Population Forecasts: A Public-Policy Forecasting Audit," Interfaces, INFORMS, vol. 38(5), pages 382-405, October.
    2. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    3. Fildes, Robert & Kourentzes, Nikolaos, 2011. "Validation and forecasting accuracy in models of climate change," International Journal of Forecasting, Elsevier, vol. 27(4), pages 968-995, October.
    4. Green, Kesten C & Armstrong, J Scott & Soon, Willie, 2008. "Benchmark forecasts for climate change," MPRA Paper 12163, University Library of Munich, Germany.

    More about this item

    Keywords

    accuracy; audit; climate change; evaluation; expert judgment; mathematical models; public policy;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation

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