Abstract
In July 2016, the European Commission presented its proposal for a regulation to reduce greenhouse gases emissions in sectors not covered by the emissions trading system with regard to post-2020 binding targets. The proposal extends the burden-sharing framework designed in 2008. This new burden-sharing, called by the European Commission as the Effort Sharing Regulation, is based on a GDP per capita rule and aims to reflect the economic capacity of each European Member State on the basis of its relative wealth. However, several papers have pointed out that this way of allocating emissions can result in great cost-inefficiencies, as the allocations do not take Member State abatement costs into account. The proposal acknowledges this issue and proposes a range of flexibility instruments (i.e., more than 15 flexibility options) that intend to enhance cost-effectiveness. This paper evaluates the proposal and analyzes the economic impacts of each flexibility option with respect to fairness and cost-effectiveness using a computable general equilibrium model. The performed analysis demonstrates that flexibility mechanisms that allow “inter-Member state flexibility” constitute the most efficient options. Specifically, they reduce compliance costs and, simultaneously, increase fairness between low-income Member States and high-income Member States.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The model is calibrated on the GTAP 9 data base, and therefore the economic variables are measured in US$\(_{2011}\) . I compute figures in €\(_{2017}\) by using the exchange rate between € and US$ for the year 2011, and the European GDP deflator between 2011 and 2017 provided by Eurostat.
The average \(\hbox {CO}_2\) price is weighted with the emissions of the scenario.
The term “hot air” was first used when the Kyoto Protocol was negotiated. It refers to an emissions target that far exceeds the likely level of emissions (like the one defined for Russia in the Kyoto Protocol). If an emissions trading system between countries is established, the emissions surplus (corresponding to the difference between GHG commitment and the effective emissions level, called “hot air”) can be sold without any reduction in emissions (Victor et al. 2001).
I estimate a linear regression between the GTT and these two variables. The following estimation is found: \(\hbox {GTT}= 0.0071 \cdot \hbox {Trade Openness} + 0.00005 \cdot \hbox {ESR tax} -0.0096\) with \(R^2\) = 0.67.
The detailed simulation results of all scenarios presented in this paper are given in the Appendix.
See Table 22 in the Appendix.
References
Aguiar A, Narayanan B, McDougall R (2016) An overview of the GTAP 9 data base. J Glob Econ Anal 1(1):181–208
Amann M, Bertok I, Borken-Kleefeld J, Cofala J, Heyes C, Höglund-Isaksson L, Klimont Z, Nguyen B, Posch M, Rafaj P, Sandler R, Schöpp W, Wagner F, Winiwarter W (2011) Cost-effective control of air quality and greenhouse gases in Europe: modeling and policy applications. Environ Model Softw 26(12):1489–1501
Armington P (1969) A theory of demand for products distinguished by place of production. IMF Staff Pap 16(1):159–78
Babiker M, Reilly J, Viguier L (2004) Is international emissions trading always beneficial? Energy J 25(2):33–56
Babonneau F, Bernard A, Haurie A, Vielle M (2018) Welfare implications of EU effort sharing decision and possible impact of a hard Brexit. Energy Econ 74:470–489
Bernard A, Vielle M (2008) GEMINI-E3, a general equilibrium model of international national interactions between economy, energy and the environment. CMS 5(3):173–206
Bernard A, Vielle M (2009) Assessment of European Union transition scenarios with a special focus on the issue of carbon leakage. Energy Econ 31:S274–S284
Bernard AL, Vielle M (2003) Measuring the welfare cost of climate change policies: a comparative assessment based on the computable general equilibrium model GEMINI-E3. Environ Model Assess 8(3):199–217
Boeters S (2014) Optimally differentiated carbon prices for unilateral climate policy. Energy Econ 45:304–312
Böhringer C (2014) Two decades of European climate policy: a critical appraisal. Rev Environ Econ Policy 8(1):1–17
Böhringer C, Rutherford TF (2002) Carbon abatement and international spillovers. Environ Res Econ 22(3):391–417
Christoph B, Rutherford Thomas F, Tol Richard SJ (2009) The EU 20/20/2020 targets: an overview of the EMF22 assessment. Energy Econ 31(Supplement 2):S268–S273
Böhringer C, Keller A, Bortolamedi M, Seyffarth AR (2016) Good things do not always come in threes: on the excess cost of overlapping regulation in EU climate policy. Energy Policy 94:502–508
Brink C, Vollebergh HRJ, van der Werf E (2016) Carbon pricing in the EU: evaluation of different EU ETS reform options. Energy Policy 97:603–617
Capros P, Tasios N, De Vita A, Mantzos L, Paroussos L (2012) Model-based analysis of decarbonising the EU economy in the time horizon to 2050. Energy Strateg Rev 1(2):76–84
Capros P, Mantzos L, Parousos L, Tasios N, Klaassen G, Van Ierland T (2011) Analysis of the EU policy package on climate change and renewables. Energy Policy 39(3):1476–1485
Capros P, Paroussos L, Fragkos P, Tsani S, Boitier B, Wagner F, Busch S, Resch G, Blesl M, Bollen J (2014) European decarbonisation pathways under alternative technological and policy choices: a multi-model analysis. Energy Strateg Rev 2(3):231–245
De Cara S, Jayet P-A (2011) Marginal abatement costs of greenhouse gas emissions from European agriculture, cost effectiveness, and the EU non-ETS burden sharing agreement. Ecol Econ 70(9):1680–1690
Chiodi A, Gargiulo M, Deane JP, Lavigne D, Rout UK, Gallachóir BPÓ (2013) Modelling the impacts of challenging 2020 non-ETS GHG emissions reduction targets on Ireland’s energy system. Energy Policy 62:1438–1452
Delreux T, Ohler F (2019) Climate policy in European Union politics in Oxford research encyclopedia of politics. https://doi.org/10.1093/acrefore/9780190228637.013.1097
Ellison D, Lundblad M, Petersson H (2014) Reforming the EU approach to LULUCF and the climate policy framework. Environ Sci Policy 40:1–15
Elofsson K, Gren I-M (2018) Cost-efficient climate policies for interdependent carbon pools. Environ Model Softw 101:86–101
European Commission (2013) EU reference scenario 2013, publications office of the European Union. https://doi.org/10.2833/17897. ISBN 978-92-79-33728-4
European Commission (2015) The 2015 ageing report: economic and budgetary projections for the 28 EU Member States (2013–2060). Directorate-General for Economic and Financial Affairs. https://doi.org/10.2765/877631. ISSN 1725-3217
European Commission (2016a) EU reference scenario 2016. https://doi.org/10.2833/001137. ISBN 978-92-79-52374-8
European Commission (2016b) Commission staff working document impact assessment accompanying the document proposal for a regulation of the European parliament and of the council on binding annual greenhouse gas emission reductions by member states from 2021 to 2030 for a resilient energy union and to meet commitments under the Paris agreement and amending regulation no 525/2013 of the European parliament and the council on a mechanism for monitoring and reporting greenhouse gas emissions and other information relevant to climate change, SWD(2016) 247 final
European Commission (2016c) Commission staff working document - impact assessment - accompanying the document proposal for a regulation of the European parliament and of the council on the inclusion of greenhouse gas emissions and removals from land use, land use change and forestry into the 2030 climate and energy framework and amending regulation no 525/2013 of the European parliament and the council on a mechanism for monitoring and reporting greenhouse gas emissions and other information relevant to climate change, SWD(2016) 249 final
Favero A, Sohngen B, Huang Y, Jin Y (2018) Global cost estimates of forest climate mitigation with albedo: a new integrative policy approach. Environ Res Lett 13(12):125002
Grassi G, Pilli R (2017) Projecting the EU forest carbon net emissions in line with the “continuation of forest management”: the JRC method, EUR 28623, vol 106814. Publications Office of the European Union, Luxembourg. https://doi.org/10.2760/844243. ISBN 978-92-79-69098-3I, ISSN 1831-9424
Harrison WJ, Horridge JM, Pearson KR (2000) Decomposing simulation results with respect to exogenous shocks. Comput Econ 15(3):227–249
Hepburn C, Grubb M, Neuhoff K, Matthes F, Tse M (2006) Auctioning of EU ETS phase II allowances: how and why? Clim Policy 6(1):137–160
Höglund-Isaksson L, Winiwarter W, Purohit P, Rafaj P, Schöpp W, Klimont Z (2012) EU low carbon roadmap 2050. Energy Strateg Rev 1(2):97–108
Michetti M, Rosa R (2012) Afforestation and timber management compliance strategies in climate policy. A computable general equilibrium analysis. Ecol Econ 77:139–148
Nabuurs G-J, Delacote P, Ellison D, Hanewinkel M, Hetemäki L, Lindner M (2017) By 2050 the mitigation effects of EU forests could nearly double through climate smart forestry. Forests 8(12)
Official Journal of the European Union (2009) Decision no 406/2009/EC of the European parliament and of the council of 23 April 2009 on the effort of member states to reduce their greenhouse gas emissions to meet the community’s greenhouse gas emission reduction commitments up to 2020. http://data.europa.eu/eli/dec/2009/406/oj
Sartor O, Bart I, Cochran I, Tuerk A (2015) Enhanced flexibility in the EU’s 2030 effort sharing agreement: issue and options. Tech Rep Clim Strateg
Tol RSJ (2009) Intra-union flexibility of non-ETS emission reduction obligations in the European Union. Energy Policy 37(5):1745–1752
United Nations Framework Convention on Climate Change (2018) Greenhouse gas inventory data
Venmans F (2012) A literature-based multi-criteria evaluation of the EU ETS. Renew Sustain Energy Rev 16(8):5493–5510
Victor DG, Nakićenović N, Victor N (2001) The Kyoto protocol emission allocations: windfall surpluses for Russia and Ukraine. Clim Change 49(3):263–277
Viguier L, Vielle M, Haurie A, Bernard A (2006) A two-level computable equilibrium model to assess the strategic allocation of emission allowances within the European Union. Comput Oper Res 33(2):369–385
Weitzel M, Saveyn B, Vandyck T (2019) Including bottom-up emission abatement technologies in a large-scale global economic model for policy assessments. Energy Econ 83:254–263
Acknowledgements
Three anonymous reviewers are gratefully thanked for their valuable comments and suggestions. I would also like to thank Bert Saveyn and the participants of the ENERDAY 2019 conference, the 22nd Annual Conference on Global Economic Analysis, the 16th IAEE European Conference and the economic seminar of the institut national de la statistique et des études économiques du Grand-Duché de Luxembourg for their helpful comments on a previous version of this paper.
This work was supported by the H2020 European Commission Project “PARIS REINFORCE” under grant Agreement No. 820846. The sole responsibility for the content of this paper lies with the author; the paper does not necessarily reflect the opinions of the European Commission.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
1.1 Nested CES production function
Domestic production technologies are described through nested CES functions which differ according to the sector. Figure 6 shows the nested CES production structure of the non-fossil energy sector. Production is done with four aggregates: Capital, labor, material and energy. In a second step (nest), material and energy are decomposed in individual goods using again CES functions.
Nested CES production structure of non-fossil energy sector
Coal, crude oil and natural gas sectors include a fix factor that represents the non-renewable resource associated with each fossil fuel energy. For these sectors I suppose that the domestic production is realized with this fix factor and the other standard inputs (i.e., capital, labor, material and energy) through again a nested CES function. Finally, Refined petroleum products are produced from the basic input, that is crude oil. The model considers this specificity with a CES function between crude oil and other standards inputs at the top level of the nested CES structure.
1.2 Nested CES household function
Figure 7 shows the nested CES structure of the household consumption. At the first level of the consumption function, households choose between three aggregates: housing, transport and other consumptions. Energy consumption is divided between transportation and housing purposes. In each nest, energy can be substituted by spending more on capital goods, cars in the first case and shelter in the second one, in other words, by purchasing more energy-efficient but also more expensive cars and housing units.
Nested CES structure of household consumption
1.3 Scenario detailed results
See Tables 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 and 22.
About this article
Cite this article
Vielle, M. Navigating various flexibility mechanisms under European burden-sharing. Environ Econ Policy Stud 22, 267–313 (2020). https://doi.org/10.1007/s10018-019-00257-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10018-019-00257-3