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Long Run Projections for Climate Change Scenarios

Author

Listed:
  • Warwick J. McKibbin

    (Australian National University, Research School of Pacific and Asian Studies, Economics Division
    The Brookings Institution)

  • David Pearce

    (Centre for International Economics, Canberra)

  • Alison Stagman

    (Australian National University)

Abstract

The prediction of future temperature increases depends critically on the projections of future greenhouse gas emissions. Yet there is a vigorous debate about how these projections should be undertaken and how reasonable is the approach of the Special Report on Emissions Scenarios (SRES) published by the Intergovernmental Panel on Climate Change (IPCC) which forms the basis of nearly all recent analyses of the impacts of climate change. In particular there has been significant criticism by Ian Castles and David Henderson regarding the plausibility of some scenarios. This paper explores a range of methodological issues surrounding projecting greenhouse emissions over the next century. It points out that understanding future emissions, requires a framework that deals with the sources of economic growth and allows for endogenous structural change. It also explores the role of “convergence” assumptions and the debate regarding the use of purchasing power parity (PPP) measurement versus market exchange rate (MER) measurement of income differentials. Using the G-Cubed multi-country model we show that emission projections based on convergence assumptions defined in MER terms, are 40% higher by 2100 than emissions generated using a PPP comparison of income differentials between economies. This result illustrates the argument by Castles and Henderson that the use of MER convergence assumptions will likely overestimate emissions projections, taking many other issues as given. However it is not clear what this means for the SRES projections given that it might be argued that in some models in the SRES, there could be endogenous changes in technology that will offset this result. We do not have access to those models to explore this issue and can only show what this particular assumption implies in the G-Cubed model. It is also ambiguous exactly what was done in the SRES report regarding convergence assumptions in some scenarios. Either way these results do not imply that climate change is not an issue but that there is a great deal of uncertainty about future climate projections and it is very unhelpful to presume that all futures are equally likely. In order to deal with this we also propose as a better guide to policymakers a methodology that calculates probabilities for future projections rather than the approach of SRES which is based on storylines without any assessment of plausibility. It is unfortunate that some analyses of the impacts of future climate change are based on the extreme outliers from the SRES without any understanding of the probability of these outcomes. This alternative approach could be done using the economic approach proposed in the G-Cubed model as outlined in this paper, or it could be done with the existing range of SRES scenarios to better inform the debate on likely future greenhouse scenarios.

Suggested Citation

  • Warwick J. McKibbin & David Pearce & Alison Stagman, 2004. "Long Run Projections for Climate Change Scenarios," Economics and Environment Network Working Papers 0405, Australian National University, Economics and Environment Network.
  • Handle: RePEc:anu:eenwps:0405
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    Citations

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    Cited by:

    1. Warwick J. McKIBBIN, 2006. "Environmental Consequences of Rising Energy Use in China," Asian Economic Policy Review, Japan Center for Economic Research, vol. 1(1), pages 157-174, June.
    2. Bosetti, Valentina & Massetti, Emanuele & Tavoni, Massimo, 2007. "The WITCH Model. Structure, Baseline, Solutions," Climate Change Modelling and Policy Working Papers 12064, Fondazione Eni Enrico Mattei (FEEM).
    3. Bosello, Francesco & Roson, Roberto & Tol, Richard S.J., 2006. "Economy-wide estimates of the implications of climate change: Human health," Ecological Economics, Elsevier, vol. 58(3), pages 579-591, June.
    4. Warwick J. McKIBBIN, 2006. "Environmental Consequences of Rising Energy Use in China," Asian Economic Policy Review, Japan Center for Economic Research, vol. 1(1), pages 157-174.
    5. Warwick J. McKibbin & David Pearce & Alison Stegman, 2004. "Can the IPCC SRES Be Improved?," Energy & Environment, , vol. 15(3), pages 351-362, July.
    6. Méjean, Aurélie & Hope, Chris, 2010. "Modelling the costs of energy crops: A case study of US corn and Brazilian sugar cane," Energy Policy, Elsevier, vol. 38(1), pages 547-561, January.
    7. Richard S.J. Tol, 2004. "Exchange Rates And Climate Change: An Application Of Fund," Working Papers FNU-45, Research unit Sustainability and Global Change, Hamburg University, revised Jun 2004.
    8. Pant, Hom M. & Fisher, Brian S., 2007. "Alternative measures of output in global economic-environmental models: Purchasing power parity or market exchange rates? -- Comment," Energy Economics, Elsevier, vol. 29(3), pages 375-389, May.
    9. Peter B. Dixon & Maureen T. Rimmer, 2005. "Analysing Convergence with a Multi-Country Computable General Equilibrium Model: PPP versus Mer," Energy & Environment, , vol. 16(6), pages 901-921, November.
    10. McKibbin, Warwick J. & Pearce, David & Stegman, Alison, 2007. "Long term projections of carbon emissions," International Journal of Forecasting, Elsevier, vol. 23(4), pages 637-653.
    11. Warwick J. Mckibbin, 2005. "Climate Change Policy for India," Palgrave Macmillan Books, in: Raghbendra Jha (ed.), Economic Growth, Economic Performance and Welfare in South Asia, chapter 7, pages 121-150, Palgrave Macmillan.
    12. Duval, Romain & de la Maisonneuve, Christine, 2010. "Long-run growth scenarios for the world economy," Journal of Policy Modeling, Elsevier, vol. 32(1), pages 64-80, January.

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    More about this item

    Keywords

    Climate change; Kyoto Protocol; G-Cubed; model; projections; SRES; PPP versus MER;
    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
    • O20 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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