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A MERGE Model with Endogenous Technological Change and the Cost of Carbon Stabilization

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  • Socrates Kypreos

    (Paul Scherrer Institute)

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    Abstract

    Two stylized backstop systems with endogenous technological learning formulations (ETL) are introduced in MERGE: one for the electric and the other for the non-electric markets. Then the model is applied to analyze the impacts of ETL on carbon-mitigation policy, contrasting the resulting impacts with the situation without learning. As the model considers endogenous technological change in the energy sector only some exogenous key parameters defining the production function are varied together with the assumed learning rates to check the robustness of our results. Based on model estimations and the sensitivity analyses we conclude that increased commitments for the development of new technologies to advance along their learning curves has a potential for substantial reductions in the cost of climate mitigation helping to reach safe concentrations of carbon in the atmosphere.

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    Bibliographic Info

    Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2005.123.

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    Date of creation: Oct 2005
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    Handle: RePEc:fem:femwpa:2005.123

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    Related research

    Keywords: Climate change stabilization policies; Non-linear optimization; Induced technological change; Energy and macroeconomy;

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