Please use this identifier to cite or link to this item: http://hdl.handle.net/10532/2258
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dc.contributor.authorBourne, Michael Geoffreyes_ES
dc.contributor.authorPhilippidis, Georgees_ES
dc.contributor.authorQuiroga, S.es_ES
dc.contributor.authorFernández Haddad, Z.es_ES
dc.date.accessioned2013-06-24T11:17:38Z
dc.date.available2013-06-24T11:17:38Z
dc.date.issued2013es_ES
dc.identifier.citation16th Annual Conference on Global Economic Analysis: New Challenges for Global Trade in a Rapidly Changing World. 2013 Conference Papers: Shanghai, China, June 12-14, 2013: Shanghai, China, June 12-14, 2013en
dc.identifier.issn2160-2115 (online)es_ES
dc.identifier.urihttp://hdl.handle.net/10532/2258
dc.description.abstractEmploying a recursive dynamic computable general equilibrium (CGE) model of the Spanish economy, this study explicitly aims to characterise the potential impact of Kyoto and European Union environmental policy targets on the Spanish economy up to 2020, with a particular focus on the agricultural sector. The model code is modified to characterise the emissions trading scheme (ETS), emissions quotas and carbon taxes, whilst emissions reductions are applied to all six registered greenhouse gases (GHGs). As extensions to this work, the study attempts to integrate both the use of ‘Marginal Abatement Cost’ (MAC) curves for potential emissions reductions within the agricultural sector, and econometric estimates of the effects of global warming on land productivity in Spain. The study includes a no action baseline (with 2007 as the benchmark year), in which GHGs are not restricted in any sector of the economy. This is compared to an emissions stabilisation scenario, in which the European Union’s Emissions Trading Scheme (EU ETS) is implemented, and all of Spain’s commitments under Kyoto, and various pieces of EU climate change legislation, are met. Under this scenario, the policy-induced price rises of polluting inputs and processes determines the allocation of emissions reductions amongst the various industries in the economy. Given the agricultural focus of the study, the modelling of emissions response in this sector is further enhanced by the inclusion of MAC curves. These map out an endogenous technological response to price rises, and the extent to which the emissions coefficient (e.g. N2O per Kg of fertiliser applied, or CH4 per head of cattle) can be reduced, such that the same quantity of input emits a smaller amount of GHGs. A flexible functional form is used to calibrate the MAC curves to data from the IIASAs GAINS model , which includes potential emissions reductions, and associated costs, of all major technological advances in agriculture currently ...en
dc.language.isoenes_ES
dc.relation.urihttps://www.gtap.agecon.purdue.edu/resources/res_display.asp?RecordID=4154es_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/*
dc.subject.othereconomia agroalimentariaes_ES
dc.titleKyoto and Mañana: A CGE analysis of Spanish Greenhouse Gas targets to 2020en
dc.typeProceedings Paper*
dc.typeconferenceObject-
dc.bibliographicCitation.conferencedateJune 12-14, 2013es_ES
dc.bibliographicCitation.conferencename16th Annual Conference on Global Economic Analysis: New Challenges for Global Trade in a Rapidly Changing Worlden
dc.bibliographicCitation.conferenceplaceShanghai, Chinaes_ES
dc.subject.agrovocPolítica agrícolaes
dc.subject.agrovocCambio climáticoes
dc.subject.agrovocEspañaes
dc.description.statusPublishedes_ES
dc.type.refereedNon-Refereedes_ES
dc.type.specifiedArticlees_ES
dc.bibliographicCitation.title16th Annual Conference on Global Economic Analysis: New Challenges for Global Trade in a Rapidly Changing World. 2013 Conference Papers: Shanghai, China, June 12-14, 2013en
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