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Literature Review of Energy-Economics Models, Regarding Technological Change and Uncertainty

Author

Listed:
  • Pablo Salas

    (Cambridge Centre for Climate Change Mitigation Research, Department of Land Economy, University of Cambridge)

Abstract

The power sector contributes with more than one third of the anthropogenic green house gas (GHG) emissions, and therefore it is a relevant target for climate change mitigation measures. However, its technological evolution is co-dependent with many other complex phenomena, such as climate policies, energy investment, natural resources availability, social and political change, among others. In order to create the appropriate policies that help us to adopt low carbon energy technologies, it is necessary to understand how these uncertain phenomena interact, and what are the implications in terms of carbon emissions. This paper is an overview of some of the energy-economic models available to study the evolution of the power sector, with particular emphasis in the uncertain drivers of technological change, and the consequent impacts on GHG emissions.

Suggested Citation

  • Pablo Salas, 2013. "Literature Review of Energy-Economics Models, Regarding Technological Change and Uncertainty," 4CMR Working Paper Series 003, University of Cambridge, Department of Land Economy, Cambridge Centre for Climate Change Mitigation Research.
    • Handle: RePEc:ccc:wpaper:003
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    File URL: http://be.4cmr.group.cam.ac.uk/working-papers/pdf/4cmr_WP_03.pdf
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    References listed on IDEAS

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    Keywords

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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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