Capturing key energy and emission trends in CGE models: Assessment of Status and Remaining Challenges

IF 2.2 Q2 ECONOMICS Journal of Global Economic Analysis Pub Date : 2020-06-25 DOI:10.21642/JGEA.050106AF
Taran Fæhn, G. Bachner, Robert H. Beach, Jean Château, S. Fujimori, M. Ghosh, M. Hamdi-Chérif, E. Lanzi, S. Paltsev, Toon Vandyck, Bruno S. L. Cunha, Rafael Garaffa, K. Steininger
{"title":"Capturing key energy and emission trends in CGE models: Assessment of Status and Remaining Challenges","authors":"Taran Fæhn, G. Bachner, Robert H. Beach, Jean Château, S. Fujimori, M. Ghosh, M. Hamdi-Chérif, E. Lanzi, S. Paltsev, Toon Vandyck, Bruno S. L. Cunha, Rafael Garaffa, K. Steininger","doi":"10.21642/JGEA.050106AF","DOIUrl":null,"url":null,"abstract":"Limiting global warming in line with the goals in the Paris Agreement will require substantial technological and behavioural transformations. This challenge drives many of the current modelling trends. This article undertakes a review of 17 state-of-the-art recursive-dynamic computable general equilibrium (CGE) models and assesses the key methodologies and applied modules they use for representing sectoral energy and emission characteristics and dynamics. The purpose is to provide technical insight into recent advances in the modelling of current and future energy and abatement technologies and how they can be used to make baseline projections and scenarios 20-80 years ahead. Numerical illustrations are provided. In order to represent likely energy system transitions in the decades to come, modern CGE tools have learned from bottom-up studies. Three different approaches to baseline quantification can be distinguished: (a) exploiting bottom-up model characteristics to endogenize responses of technological investment and utilization, (b) relying on external information sources to feed the exogenous parameters and variables of the model, and (c) linking the model with more technology-rich, partial models to obtain bottom-up- and pathway-consistent parameters.","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Global Economic Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21642/JGEA.050106AF","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 15

Abstract

Limiting global warming in line with the goals in the Paris Agreement will require substantial technological and behavioural transformations. This challenge drives many of the current modelling trends. This article undertakes a review of 17 state-of-the-art recursive-dynamic computable general equilibrium (CGE) models and assesses the key methodologies and applied modules they use for representing sectoral energy and emission characteristics and dynamics. The purpose is to provide technical insight into recent advances in the modelling of current and future energy and abatement technologies and how they can be used to make baseline projections and scenarios 20-80 years ahead. Numerical illustrations are provided. In order to represent likely energy system transitions in the decades to come, modern CGE tools have learned from bottom-up studies. Three different approaches to baseline quantification can be distinguished: (a) exploiting bottom-up model characteristics to endogenize responses of technological investment and utilization, (b) relying on external information sources to feed the exogenous parameters and variables of the model, and (c) linking the model with more technology-rich, partial models to obtain bottom-up- and pathway-consistent parameters.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
在CGE模型中捕捉关键的能源和排放趋势:现状和剩余挑战评估
根据《巴黎协定》的目标限制全球变暖需要进行实质性的技术和行为变革。这一挑战推动了当前许多建模趋势。本文对17个最先进的递归动态可计算一般均衡(CGE)模型进行了综述,并评估了它们用于表示部门能源和排放特征和动态的关键方法和应用模块。其目的是提供技术见解,了解当前和未来能源和减排技术建模的最新进展,以及如何使用这些技术来做出20-80年前的基线预测和情景。提供了数字插图。为了代表未来几十年可能发生的能源系统转型,现代CGE工具从自下而上的研究中学习。可以区分三种不同的基线量化方法:(a)利用自下而上的模型特征来内生技术投资和利用的反应,(b)依靠外部信息源来提供模型的外生参数和变量,以及(c)将模型与更丰富的技术联系起来,部分模型,以获得自下而上和路径一致的参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
5.60
自引率
12.00%
发文量
0
期刊最新文献
Estimation of the value-added/intermediate input substitution elasticities consistent with the GTAP data A Ricardian Trade Structure in CGE: Modeling Eaton-Kortum Based Trade with GTAP GTAP-Power Data Base: Version 11 Calibrating Constant Elasticityof Substitution Technologies toBottom-up Cost Estimates A Latin Hypercube Sampling Utility: with an application to an Integrated Assessment Model
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1