Nexus of COVID‑19 and carbon prices in the EU emission trading system: evidence from multifractal and the wavelet coherence approaches
Nexus of COVID‑19 and carbon prices in the EU emission trading system: evidence from multifractal and the wavelet coherence approaches
In this paper, we analyzed the role of carbon pricing as a vital tool for achieving the sustainable energy transition and discussed policy implications for reaching this goal in the era of the COVID-19 pandemic. To investigate the connection and cross-correlation between COVID-19 cases and carbon price returns in EU ETS, we applied two novel approaches: the multifractal detrending moving average cross-correlation (MF-X-DMA) and the Wavelet Coherence techniques. The coverage of data is from 2 March 2020 to 19 March 2021. The results of the MF-X-DMA method show that the cross-correlation is substantial and negatively correlated. Moreover, the results imply the presence of multifractal cross-correlations and that a significant change in the number of COVID-19 cases further impacts carbon price fluctuations. Concerning the Wavelet coherence method results, we can also find a strong (negative) relationship between selected variables, and this strong correlation is observed throughout the whole study period. In addition, we observe that in the first wave of the COVID-19 outbreak, the changes in the COVID-19 cases are leading the CO2 price returns (particularly in the 16-32 time scale). The results of this study can have significant implications for policymakers and contributions for environmental experts and investors.
COVID-19, Carbon pricing, Cross-correlation analysis, EU ETS, Multifractal detrending moving average, Wavelet analysis
41293-41308
Ghazani, Mijid Mirzaee
d8639cef-9c5b-4fc5-b179-cba6d7fb295e
Khosravi, Reza
5780cdc6-9a32-41b6-aab6-6870286dadcd
Barak, Sasan
f82186de-f5b7-4224-9621-a00e7501f2c3
28 January 2022
Ghazani, Mijid Mirzaee
d8639cef-9c5b-4fc5-b179-cba6d7fb295e
Khosravi, Reza
5780cdc6-9a32-41b6-aab6-6870286dadcd
Barak, Sasan
f82186de-f5b7-4224-9621-a00e7501f2c3
Ghazani, Mijid Mirzaee, Khosravi, Reza and Barak, Sasan
(2022)
Nexus of COVID‑19 and carbon prices in the EU emission trading system: evidence from multifractal and the wavelet coherence approaches.
Environmental Science and Pollution Research, 29 (27), .
(doi:10.1007/s11356-021-18304-6).
Abstract
In this paper, we analyzed the role of carbon pricing as a vital tool for achieving the sustainable energy transition and discussed policy implications for reaching this goal in the era of the COVID-19 pandemic. To investigate the connection and cross-correlation between COVID-19 cases and carbon price returns in EU ETS, we applied two novel approaches: the multifractal detrending moving average cross-correlation (MF-X-DMA) and the Wavelet Coherence techniques. The coverage of data is from 2 March 2020 to 19 March 2021. The results of the MF-X-DMA method show that the cross-correlation is substantial and negatively correlated. Moreover, the results imply the presence of multifractal cross-correlations and that a significant change in the number of COVID-19 cases further impacts carbon price fluctuations. Concerning the Wavelet coherence method results, we can also find a strong (negative) relationship between selected variables, and this strong correlation is observed throughout the whole study period. In addition, we observe that in the first wave of the COVID-19 outbreak, the changes in the COVID-19 cases are leading the CO2 price returns (particularly in the 16-32 time scale). The results of this study can have significant implications for policymakers and contributions for environmental experts and investors.
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Accepted/In Press date: 20 December 2021
e-pub ahead of print date: 28 January 2022
Published date: 28 January 2022
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Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.
Keywords:
COVID-19, Carbon pricing, Cross-correlation analysis, EU ETS, Multifractal detrending moving average, Wavelet analysis
Identifiers
Local EPrints ID: 455434
URI: http://eprints.soton.ac.uk/id/eprint/455434
ISSN: 0944-1344
PURE UUID: bf2344c3-30de-41d2-8902-19c5435dac1c
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Date deposited: 21 Mar 2022 17:55
Last modified: 17 Mar 2024 07:10
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Author:
Mijid Mirzaee Ghazani
Author:
Reza Khosravi
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