Artikel

COVID-19 outbreak and CO2 emissions: Macro-financial linkages

In the Dynamic Conditional Correlation with Mixed Data Sampling (DCC-MIDAS) framework, we scrutinize the correlations between the macro-financial environment and CO2 emissions in the aftermath of the COVID-19 diffusion. The main original idea is that the economy's lock-down will alleviate part of the greenhouse gases' burden that human activity induces on the environment. We capture the time-varying correlations between U.S. COVID-19 confirmed cases, deaths, and recovered cases that were recorded by the Johns Hopkins Coronavirus Center, on the one hand; U.S. Total Industrial Production Index and Total Fossil Fuels CO2 emissions from the U.S. Energy Information Administration on the other hand. High-frequency data for U.S. stock markets are included with five-minute realized volatility from the Oxford-Man Institute of Quantitative Finance. The DCC-MIDAS approach indicates that COVID-19 confirmed cases and deaths negatively influence the macro-financial variables and CO2 emissions. We quantify the time-varying correlations of CO2 emissions with either COVID-19 confirmed cases or COVID-19 deaths to sharply decrease by -;15% to -30%. The main takeaway is that we track correlations and reveal a recessionary outlook against the background of the pandemic.

Language
Englisch

Bibliographic citation
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 14 ; Year: 2021 ; Issue: 1 ; Pages: 1-18 ; Basel: MDPI

Classification
Wirtschaft
Subject
COVID-19
CO2 emissions
time-varying correlations
macroeconomy
stock markets
DCC MIDAS

Event
Geistige Schöpfung
(who)
Chevallier, Julien
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2021

DOI
doi:10.3390/jrfm14010012
Handle
Last update
10.03.2025, 11:41 AM CET

Data provider

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Chevallier, Julien
  • MDPI

Time of origin

  • 2021

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