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Time–frequency co-movement between COVID-19, crude oil prices, and atmospheric CO2 emissions: Fresh global insights from partial and multiple coherence approach

Author

Listed:
  • Yasir Habib

    (Beijing Institute of Technology)

  • Enjun Xia

    (Beijing Institute of Technology)

  • Zeeshan Fareed

    (Huzhou University)

  • Shujahat Haider Hashmi

    (Huazhong University of Science and Technology)

Abstract

This paper endeavors to analyze and provide fresh global insights from the asymmetric nexus between the recent outbreak of COVID-19, crude oil prices, and atmospheric CO2 emissions. The analysis employs a unique Morlet’s wavelet method. More precisely, this paper implements comprehensive wavelet coherence analysis tools, including continuous wavelet coherence, partial wavelet coherence, and multiple wavelet coherence to the daily dataset spanning from December 31, 2019 to May 31, 2020. From the frequency perspective, this paper finds significant wavelet coherence and vigorous lead and lag connections. This analysis ascertains significant movement in variables over frequency and time domain. These results demonstrate strong but varying connotations between studied variables. The results also indicate that COVID-19 impacts crude oil prices and the most contributor to the reduction in CO2 emissions during the pandemic period. This study offers practical and policy implications and endorsements for individuals, environmental experts, and investors. Graphic abstract

Suggested Citation

  • Yasir Habib & Enjun Xia & Zeeshan Fareed & Shujahat Haider Hashmi, 2021. "Time–frequency co-movement between COVID-19, crude oil prices, and atmospheric CO2 emissions: Fresh global insights from partial and multiple coherence approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(6), pages 9397-9417, June.
    • Handle: RePEc:spr:endesu:v:23:y:2021:i:6:d:10.1007_s10668-020-01031-2
    DOI: 10.1007/s10668-020-01031-2
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    References listed on IDEAS

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    1. Editorial, 2020. "Covid-19 and Climate Change," Journal, Review of Agrarian Studies, vol. 10(1), pages 5-6, January-J.
    2. Vacha, Lukas & Barunik, Jozef, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Energy Economics, Elsevier, vol. 34(1), pages 241-247.
    3. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    4. Chaker Aloui & Besma Hkiri & Shawkat Hammoudeh & Muhammad Shahbaz, 2018. "A Multiple and Partial Wavelet Analysis of the Oil Price, Inflation, Exchange Rate, and Economic Growth Nexus in Saudi Arabia," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(4), pages 935-956, March.
    5. Goodell, John W. & Goutte, Stephane, 2021. "Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 38(C).
    6. François Benhmad, 2012. "Modeling Nonlinear Granger Causality between the Oil price and U.S Dollar," Post-Print hal-03062497, HAL.
    7. Hkiri, Besma & Hammoudeh, Shawkat & Aloui, Chaker & Shahbaz, Muhammad, 2018. "The interconnections between U.S. financial CDS spreads and control variables: New evidence using partial and multivariate wavelet coherences," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 237-257.
    8. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
    9. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
    10. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
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    Cited by:

    1. Shabir Mohsin Hashmi & Xuyou Yu & Qasim Raza Syed & Li Rong, 2024. "Testing the environmental Kuznets curve (EKC) hypothesis amidst climate policy uncertainty: sectoral analysis using the novel Fourier ARDL approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(7), pages 16503-16522, July.
    2. Krzysztof Dmytrów & Joanna Landmesser & Beata Bieszk-Stolorz, 2021. "The Connections between COVID-19 and the Energy Commodities Prices: Evidence through the Dynamic Time Warping Method," Energies, MDPI, vol. 14(13), pages 1-23, July.
    3. Shah, Muhammad Ibrahim & Foglia, Matteo & Shahzad, Umer & Fareed, Zeeshan, 2022. "Green innovation, resource price and carbon emissions during the COVID-19 times: New findings from wavelet local multiple correlation analysis," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    4. Haxhimusa, Adhurim & Liebensteiner, Mario, 2021. "Effects of electricity demand reductions under a carbon pricing regime on emissions: lessons from COVID-19," Energy Policy, Elsevier, vol. 156(C).

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