Vis enkel innførsel

dc.contributor.authorFæhn, Taran
dc.contributor.authorBachner, Gabriel
dc.contributor.authorBeach, Robert
dc.contributor.authorChateau, Jean
dc.contributor.authorFujimori, Shinichiro
dc.contributor.authorGhosh, Madanmohan
dc.contributor.authorHamdi-Cherif, Meriem
dc.contributor.authorLanzi, Elisa
dc.contributor.authorPaltsev, Sergey
dc.contributor.authorVandyck, Toon
dc.contributor.authorCunha, Bruno
dc.contributor.authorGaraffa, Rafael
dc.contributor.authorSteininger, Karl
dc.date.accessioned2020-07-14T12:17:55Z
dc.date.available2020-07-14T12:17:55Z
dc.date.issued2020-07
dc.identifier.issn1892-753X
dc.identifier.urihttps://hdl.handle.net/11250/2663967
dc.descriptionThe present article is forthcoming in Journal of Global Economic Analysis vol. 5 (2020) No.1, 196-272. It is a product of fruitful discussions in the OECD/GTAP workshop "Shaping long-term baselines with CGE models” in the OECD, Paris, 24-25 January 2018, in particular, the break-out session on energy and the environment.en_US
dc.description.abstractLimiting 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 pathwayconsistent parameters.en_US
dc.language.isoengen_US
dc.publisherStatistisk sentralbyråen_US
dc.relation.ispartofseriesDiscussion Paper;No. 936
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.subjectComputable general equilibrium modelsen_US
dc.subjectLong-term economic projectionsen_US
dc.subjectEnergyen_US
dc.subjectTechnological changeen_US
dc.subjectEmissionsen_US
dc.subjectGreenhouse gasesen_US
dc.titleCapturing Key Energy and Emission Trends in CGE models: Assessment of Status and Remaining Challengesen_US
dc.typeWorking paperen_US
dc.source.pagenumber76en_US
dc.relation.projectNorges Forskningsråd: 268200en_US


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal