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How Overconfident are Current Projections of Anthropogenic Carbon Dioxide Emissions?

Author

Listed:
  • Klaus Keller

    (Penn State University Park)

  • Louise I. Miltich

    (Penn State University Park)

  • Alexander Robinson

    (Penn State University Park)

  • Richard S.J. Tol

    (Economic and Social Research Institute)

Abstract

Analyzing the risks of anthropogenic climate change requires sound probabilistic projections of CO2 emissions. Previous projections have broken important new ground, but many rely on out-of-range projections, are limited to the 21st century, or provide only implicit probabilistic information. Here we take a step towards resolving these problems by assimilating globally aggregated observations of population size, economic output, and CO2 emissions over the last three centuries into a simple economic model. We use this model to derive probabilistic projections of business-as-usual CO2 emissions to the year 2150. We demonstrate how the common practice to limit the calibration timescale to decades can result in biased and overconfident projections. The range of several CO2 emission scenarios (e.g., from the Special Report on Emission Scenarios) misses potentially important tails of our projected probability density function. Studies that have interpreted the range of CO2 emission scenarios as an approximation for the full forcing uncertainty may well be biased towards overconfident climate change projections.

Suggested Citation

  • Klaus Keller & Louise I. Miltich & Alexander Robinson & Richard S.J. Tol, 2007. "How Overconfident are Current Projections of Anthropogenic Carbon Dioxide Emissions?," Working Papers 2007.39, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2007.39
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Dritan Osmani, "undated". "A note on optimal transfer schemes, stable coalition for environmental protection and joint maximization assumption," Working Papers FNU-176, Research unit Sustainability and Global Change, Hamburg University.

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    More about this item

    Keywords

    Carbon Dioxide; Emissions; Scenarios; Data Assimilation; Markov Chain Monte Carlo;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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