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Modeling Detailed Energy-Efficiency Technologies and Technology Policies within a CGE Framework

John A. "Skip" Laitner and Donald A. Hanson

Year: 2006
Volume: Hybrid Modeling
Number: Special Issue #2
DOI: 10.5547/ISSN0195-6574-EJ-VolSI2006-NoSI2-8
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Abstract:
Policy makers and analysts are raising questions about the adequacy of policy and technology representation in conventional energy and economic models. Most conventional models rely on a highly stylized and limited characterization of technology. In these models, any desired changes in energy demand are driven largely by pure price mechanisms such as energy taxes or carbon charges. In this paper, however, we explore the mapping of discrete technology characterizations and examine how cost-effective technologies and programs might prompt desirable increases in energy efficiency. Using the commercial health care sector as an example, we show how changes in energy efficiency and technology investments might be more properly represented in policy models.



Technology Policy and World Greenhouse Gas Emissions in the AMIGA Modeling System

Donald A. Hanson and John A. "Skip" Laitner

Year: 2006
Volume: Multi-Greenhouse Gas Mitigation and Climate Policy
Number: Special Issue #3
DOI: 10.5547/ISSN0195-6574-EJ-VolSI2006-NoSI3-18
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Abstract:
In this paper we examine the interaction between technology policy and its impact on the full basket of worldwide greenhouse emissions over the 21st century. The heart of the analysis is the Argonne National Laboratory�s AMIGA Modeling System, a technology rich, general equilibrium model that (depending on data availability) characterizes as many as 200 sectors of the regional economies. We suggest in this paper that technologies and technology policies exist which could reduce carbon emissions enough to achieve stabilization targets at relatively modest costs given the size of the world economy. This can be accomplished largely through harnessing market forces and creating incentives with the use of efficient prices on greenhouse gas emissions, combined with complementary programs and policies to reduce market failures and to promote new technology improvements and investments.



Demand Subsidies Versus R&D: Comparing the Uncertain Impacts of Policy on a Pre-commercial Low-carbon Energy Technology

Gregory F. Nemet and Erin Baker

Year: 2009
Volume: Volume 30
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol30-No4-2
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Abstract:
We combine an expert elicitation and a bottom-up manufacturing cost model to compare the effects of R&D and demand subsidies. We model their effects on the future costs of a low-carbon energy technology that is not currently commercially available, purely organic photovoltaics (PV). We find that: (1) successful R&D enables PV to achieve a cost target of 4c/kWh, (2) the cost of PV does not reach the target when only subsidies, and not R&D, are implemented, and (3) production-related effects on technological advance�learning-by-doing and economies of scale�are not as critical to the long-term potential for cost reduction in organic PV than is the investment in and success of R&D. These results are insensitive to two levels of policy intensity, the level of a carbon price, the availability of storage technology, and uncertainty in the main parameters used in the model. However, a case can still be made for subsidies: comparisons of stochastic dominance show that subsidies provide a hedge against failure in the R&D program.



Learning by Doing with Constrained Growth Rates:An Application to Energy Technology Policy

Karsten Neuhoff

Year: 2008
Volume: Volume 29
Number: Special Issue #2
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-NoSI2-9
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Abstract:
Learning by doing methodology attributes cost reductions of a technology to cumulative investment and experience. This paper argues that in addition market growth rates must also be considered. Historically growth rates have been limited in most sectors, thus allowing for feedback in the learning process. When market growth is below the optimal rate, the marginal value of additional investment could be a multiple of the direct learning benefit. Analytic and numeric models quantify this impact emphasizing the need for tailored technology policy in addition to carbon pricing. Implications for the modeling of endogenous technological change are discussed.





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