With or without U(K): A pre-Brexit network analysis of the EU ETS
Autoři:
Simone Borghesi aff001; Andrea Flori aff003
Působiště autorů:
FSR Climate, European University Institute, Florence, Italy
aff001; Department of Political and International Sciences, University of Siena, Siena, Italy
aff002; Department of Management, Economics and Industrial Engineering, Polytechnic University of Milan, Milan, Italy
aff003
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0221587
Souhrn
The European Emission Trading System (EU ETS) is commonly regarded as the key pillar of the European climate policy and as the main unifying tool to create a unique carbon price all over Europe. The UK has always played a crucial role in the EU ETS, being one of the most active national registry and a crucial hub for the exchange of allowances in the market. Brexit, therefore, could deeply modify the number and directions of such exchanges as well as the centrality of the other countries in this system. To investigate these issues, the present paper exploits network analysis tools to compare the structure of the EU ETS market in its first two phases with and without the UK, investigating a few different scenarios that might emerge from a possible reallocation of the transactions that have involved UK partners. We find that without the UK the EU ETS network would become in general much more homogeneous, though results may change focusing on the type of accounts involved in the transactions.
Klíčová slova:
Physical sciences – People and places – Computer and information sciences – Network analysis – Mathematics – Geographical locations – Europe – European Union – Germany – Algebra – Linear algebra – Eigenvectors – France – Denmark – Centrality
Zdroje
1. European Commission. EU ETS Handbook European Commission, DG Climate Action (CLIMA). 2015.
2. European Parliament and Council of the European Union. Directive (EU) 2018/410 of the European Parliament and of the Council of 14 March 2018 amending Directive 2003/87/EC to enhance cost-effective emission reductions and low-carbon investments, and Decision (EU) 2015/1814 Official Journal of the European Union, 19/3/2018.
3. Ellerman AD, Convery FJ, De Perthuis C. Pricing carbon: the European Union emissions trading scheme. Cambridge University Press. 2010.
4. World Bank, Ecofys. State and Trends of Carbon Pricing 2018. World Bank Publications. Washington, DC, 2018.
5. Carbon Pulse. EU, UK reach deal on transition period to the end of 2020. https://carbon-pulse.com/49217/. Published on March 19, 2018.
6. Hepburn C, Teytelboym A. Climate change policy after Brexit. Oxford Review of Economic Policy. 2017;33(suppl_1), S144–S154. doi: 10.1093/oxrep/grx004
7. European Union. The Impact of Brexit for the EU energy system. Directorate-General for Internal Policies Policy Department A: Economic and Scientific Policy, Bruxelles. 2017.
8. Pollitt MG, Chyong K. A Brexit and its Implications for British and EU Energy and Climate Policy. Centre on Regulation in Europe (CERRE): Brussels, Belgium. 2017.
9. Babonneau FLF, Haurie A, Vielle M. Welfare implications of EU effort sharing decision and possible impact of a hard Brexit. Energy Economics. 2018;74: 470–489. doi: 10.1016/j.eneco.2018.06.024
10. Tol RSJ. Policy Brief—Leaving an Emissions Trading Scheme: Implications for the United Kingdom and the European Union. Review of Environmental Economics and Policy. 2017;12(1), 183–189. doi: 10.1093/reep/rex025
11. Currarini S, Marchiori C, Tavoni A. Network economics and the environment: insights and perspectives. Environmental and Resource Economics. 2016;65(1), 159–189. doi: 10.1007/s10640-015-9953-6
12. İlkılıç R. Networks of common property resources. Economic Theory. 2011;47(1), 105–134. doi: 10.1007/s00199-010-0520-7
13. Conley T, Udry C. Social learning through networks: The adoption of new agricultural technologies in Ghana. American Journal of Agricultural Economics. 2001;83(3), 668–673. doi: 10.1111/0002-9092.00188
14. Günther M, Hellmann T. International environmental agreements for local and global pollution. Journal of Environmental Economics and Management. 2017;81, 38–58. doi: 10.1016/j.jeem.2016.09.001
15. Kyriakopoulou E, Xepapadeas A. Natural Resource Management: A Network Perspective. World Congress of Environmental and Resource Economists, Gothenburg, June 25-29. 2018.
16. Kharrazi A, Rovenskya E, Fath BD. Network structure impacts global commodity trade growth and resilience. PloS one. 2017;12.2: e0171184. doi: 10.1371/journal.pone.0171184 28207790
17. Dolfing AG, Leuven JRFW, Dermody BJ. The effects of network topology, climate variability and shocks on the evolution and resilience of a food trade network. PloS one. 2019;14.3: e0213378. doi: 10.1371/journal.pone.0213378 30913228
18. Karpf A, Mandel A, Battiston S. Price and network dynamics in the European carbon market. Journal of Economic Behavior & Organization. 2018;153: 103–122. doi: 10.1016/j.jebo.2018.06.019
19. Borghesi S, Flori A. EU ETS Facets in the Net: Structure and Evolution of the EU ETS Network. Energy Economics. 2018;75, 602–635. doi: 10.1016/j.eneco.2018.08.026
20. Newman MEJ. The structure and function of complex networks mixing in networks. SIAM review. 2003;45(2), 167–256. doi: 10.1137/S003614450342480
21. Jackson MO. Social and economic networks. Princeton University Press. 2010.
22. Newman MEJ. Networks. Oxford university press. 2018.
23. Caldarelli G. Scale-free networks: complex webs in nature and technology. Oxford University Press. 2007.
24. Betz RA, Schmidt TS. Transfer patterns in Phase I of the EU Emissions Trading System: a first reality check based on cluster analysis. Climate Policy. 2016;16(4), 474–495. doi: 10.1080/14693062.2015.1028319
25. Bagler G. Analysis of the airport network of India as a complex weighted network. Physica A: Statistical Mechanics and its Applications. 2008;387(12), 2972–2980. doi: 10.1016/j.physa.2008.01.077
26. Chopra SS, Dillon T, Bilec MM, Khanna V. A network-based framework for assessing infrastructure resilience: a case study of the London metro system. Journal of The Royal Society Interface. 2016;13(118), 20160113. doi: 10.1098/rsif.2016.0113
27. Cotilla-Sanchez E, Hines PDH, Barrows C, Blumsack S. Comparing the topological and electrical structure of the North American electric power infrastructure. IEEE Systems Journal. 2012;6(4), 616–626. doi: 10.1109/JSYST.2012.2183033
28. Europol. Further investigations into VAT fraud linked to the carbon emissions trading system. Europol. 2010.
29. Frunza MC, Guegan D, Lassoudiere A. Missing trader fraud on the emissions market Journal of financial crime. 2011;18(2), 183–194. doi: 10.1108/13590791111127750
30. Valente TW, Coronges K, Lakon C, Costenbader E. How correlated are network centrality measures?. Connections (Toronto, Ont.). 2008;28(1), 16.
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