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Mitigation Strategies and Costs of Climate Protection: The Effects of ETC in the Hybrid Model MIND

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  • Ottmar Edenhofer, Kai Lessmann, Nico Bauer

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.

Suggested Citation

  • Ottmar Edenhofer, Kai Lessmann, Nico Bauer, 2006. "Mitigation Strategies and Costs of Climate Protection: The Effects of ETC in the Hybrid Model MIND," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 207-222.
  • Handle: RePEc:aen:journl:2006se-a10
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    1. Grimaud, André & Lafforgue, Gilles & Magné, Bertrand, 2011. "Climate change mitigation options and directed technical change: A decentralized equilibrium analysis," Resource and Energy Economics, Elsevier, vol. 33(4), pages 938-962.
    2. 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.
    3. André Grimaud & Gilles Lafforgue, 2008. "Climate change mitigation policies : Are R&D subsidies preferable to a carbon tax ?," Revue d'économie politique, Dalloz, vol. 118(6), pages 915-940.
    4. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    5. Graham Palmer, 2018. "A Biophysical Perspective of IPCC Integrated Energy Modelling," Energies, MDPI, vol. 11(4), pages 1-17, April.
    6. Held, Hermann & Kriegler, Elmar & Lessmann, Kai & Edenhofer, Ottmar, 2009. "Efficient climate policies under technology and climate uncertainty," Energy Economics, Elsevier, vol. 31(Supplemen), pages 50-61.
    7. Grimaud, André & Lafforgue, Gilles & Magné, Bertrand, 2007. "Innovation Markets in the Policy Appraisal of Climate Change Mitigation," IDEI Working Papers 481, Institut d'Économie Industrielle (IDEI), Toulouse.
    8. Wei, Yi-Ming & Mi, Zhi-Fu & Huang, Zhimin, 2015. "Climate policy modeling: An online SCI-E and SSCI based literature review," Omega, Elsevier, vol. 57(PA), pages 70-84.
    9. Martin Junginger & Wilfried van Sark & André Faaij (ed.), 2010. "Technological Learning in the Energy Sector," Books, Edward Elgar Publishing, number 13741.
    10. Marco Rogna, 2020. "Microeconomic models of a production economy with environmental externalities," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(3), pages 2625-2650, March.
    11. Ortiz, Ramon Arigoni & Golub, Alexander & Lugovoy, Oleg & Markandya, Anil & Wang, James, 2011. "DICER: A tool for analyzing climate policies," Energy Economics, Elsevier, vol. 33(S1), pages 41-49.
    12. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    13. 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.
    14. Mathias Berthod, 2020. "Commitment and efficiency-inducing tax and subsidy scheme in the development of a clean technology," Working Papers hal-02489971, HAL.
    15. Grimaud, André & Lafforgue, Gilles, 2008. "Second Best Analysis in a General Equilibrium Climate Change Model," IDEI Working Papers 535, Institut d'Économie Industrielle (IDEI), Toulouse.
    16. GRIMAUD André & LAFFORGUE Gilles & MAGNE Bertrand, 2007. "Economic growth and Climate change in a decentralized Economy: A Theoretical and Empirical Approach," LERNA Working Papers 07.04.225, LERNA, University of Toulouse.
    17. Grimaud, André & Lafforgue, Gilles & Magné, Bertrand, 2008. "Decentralized Equilibrium Analysis in a Growth Model with Directed Technical Change and Climate Change Mitigation," IDEI Working Papers 537, Institut d'Économie Industrielle (IDEI), Toulouse.
    18. 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.
    19. Marie-Catherine Riekhof & Johannes Bröcker, 2017. "Does The Adverse Announcement Effect Of Climate Policy Matter? — A Dynamic General Equilibrium Analysis," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-34, May.
    20. Mathias Berthod, 2020. "Commitment and efficiency-inducing tax and subsidy scheme in the development of a clean technology," CEE-M Working Papers hal-02489971, CEE-M, Universtiy of Montpellier, CNRS, INRA, Montpellier SupAgro.

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    JEL classification:

    • F0 - International Economics - - General

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