Development of a global computable general equilibrium model coupled with detailed energy end-use technology
Shinichiro Fujimori,
Toshihiko Masui and
Yuzuru Matsuoka
Applied Energy, 2014, vol. 128, issue C, 296-306
Abstract:
A global computable general equilibrium (CGE) model integrating detailed energy end-use technologies is developed in this paper. The paper (1) presents how energy end-use technologies are treated within the model and (2) analyzes the characteristics of the model’s behavior. Energy service demand and end-use technologies are explicitly considered, and the share of technologies is determined by a discrete probabilistic function, namely a Logit function, to meet the energy service demand. Coupling with detailed technology information enables the CGE model to have more realistic representation in the energy consumption. The proposed model in this paper is compared with the aggregated traditional model under the same assumptions in scenarios with and without mitigation roughly consistent with the two degree climate mitigation target. Although the results of aggregated energy supply and greenhouse gas emissions are similar, there are three main differences between the aggregated and the detailed technologies models. First, GDP losses in mitigation scenarios are lower in the detailed technology model (2.8% in 2050) as compared with the aggregated model (3.2%). Second, price elasticity and autonomous energy efficiency improvement are heterogeneous across regions and sectors in the detailed technology model, whereas the traditional aggregated model generally utilizes a single value for each of these variables. Third, the magnitude of emissions reduction and factors (energy intensity and carbon factor reduction) related to climate mitigation also varies among sectors in the detailed technology model. The household sector in the detailed technology model has a relatively higher reduction for both energy intensity and the carbon factor.
Keywords: Computable general equilibrium model; Energy end-use technologies; Integrated assessment model; Hybrid model (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (51)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:128:y:2014:i:c:p:296-306
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DOI: 10.1016/j.apenergy.2014.04.074
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