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Mitigation Strategies and Costs of Climate Protection: The effects of ETC in the hybrid Model MIND

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  • Kai Lessmann

    (Potsdam Institute for Climate Impact Research (PIK))

  • Ottmar Edenhofer

    (Potsdam Institute for Climate Impact Research)

  • Nico Bauer

    (Paul ScherrerInstitute (PSI))

Abstract

MIND is a hybrid model incorporating several energy related sectors in an endogenous growth model of the world economy. This model structure allows a better understanding of the linkages between the energy sectors and the macro-economic environment. We perform a sensitivity analysis and parameter studies to improve the understanding of the economic mechanisms underlying opportunity costs and the optimal mix of mitigation options. Parameters representing technological change that permeates the entire economy have a strong impact on both the opportunity costs of climate protection and on the optimal mitigation strategies, e.g. parameters in the macro-economic environment and in the extraction sector. Sector-specific energy technology parameters change the portfolio of mitigation options but have only modest effects on opportunity costs, e.g. learning rate of the renewable energy technologies. We conclude that feedback loops between the macro-economy and the energy sectors are crucial for the determination of opportunity costs and mitigation strategies.

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Bibliographic Info

Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2005.150.

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Date of creation: Dec 2005
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Handle: RePEc:fem:femwpa:2005.150

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Keywords: Endogenous technological change; Climate change mitigation costs; Integrated assessment; Growth model; Energy sector; Integrated assessment;

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Cited by:
  1. repec:hal:ciredw:hal-00866431 is not listed on IDEAS
  2. Grimaud, André & Lafforgue, Gilles & Magné, Bertrand, 2008. "Climate Change Mitigation Options and Directed Technical Change: A Decentralized Equilibrium Analysis," IDEI Working Papers 510, Institut d'Économie Industrielle (IDEI), Toulouse, revised Nov 2009.
  3. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
  4. Alexander Golub & Oleg Lugovoy & Anil Markandya & Ramon Arigoni Ortiz & James Wang, 2013. "Regional IAM: analysis of risk-adjusted costs and benefits of climate policies," Working Papers 2013-06, BC3.
  5. Guivarch, Céline & Hallegatte, Stéphane & Crassous, Renaud, 2009. "The resilience of the Indian economy to rising oil prices as a validation test for a global energy-environment-economy CGE model," Energy Policy, Elsevier, vol. 37(11), pages 4259-4266, November.
  6. Elizabeth Stanton, 2011. "Negishi welfare weights in integrated assessment models: the mathematics of global inequality," Climatic Change, Springer, vol. 107(3), pages 417-432, August.

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