A MERGE Model with Endogenous Technological Change and the Cost of Carbon Stabilization
Socrates Kypreos
No 12083, Knowledge, Technology, Human Capital Working Papers from Fondazione Eni Enrico Mattei (FEEM)
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.
Keywords: Research; and; Development/Tech; Change/Emerging; Technologies (search for similar items in EconPapers)
Pages: 29
Date: 2005
References: View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://ageconsearch.umn.edu/record/12083/files/wp050123.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ags:feemkt:12083
DOI: 10.22004/ag.econ.12083
Access Statistics for this paper
More papers in Knowledge, Technology, Human Capital Working Papers from Fondazione Eni Enrico Mattei (FEEM) Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().