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

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Author Info
Socrates Kypreos (Paul Scherrer Institute)
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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Publisher 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;

Find related papers by JEL classification:
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General
Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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