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Regime switching effect of COVID-19 pandemic on renewable electricity generation in Denmark

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  • Shah, Muhammad Ibrahim
  • Kirikkaleli, Dervis
  • Adedoyin, Festus Fatai

Abstract

Denmark has achieved remarkable success in renewable energy generation over the last several decades. However, the country's goals of meeting its 50% energy demand from renewable by 2030 and becoming independent of fossil fuel by 2050 are currently in jeopardy due to the COVID-19 pandemic, which emerged at the end of December 2019 in the Chinese city of Wuhan. This study, therefore, tries to see how COVID-19 affects renewable electricity generation in Denmark using the advanced econometric framework. Several nonlinear estimation techniques such as Fourier ADL cointegration analysis and Markov Switching regression are used to estimate the relationship between the three channels of COVID-19 and renewable electricity generation. The result from the Markov Switching regression reveals that renewable electricity production in Denmark is adversely affected by the enforced lockdown as captured via the stringency index, economic support provided to tackle the pandemic, and daily confirmed deaths of COVID-19. Moreover, the causality test shows that the stringency index and daily confirmed deaths of COVID-19 are important predictors of renewable electricity, but the economic support index has weak causality with renewable electricity. The study finally presents some crucial policy suggestions for Denmark which can help the country achieve its renewable production goals.

Suggested Citation

  • Shah, Muhammad Ibrahim & Kirikkaleli, Dervis & Adedoyin, Festus Fatai, 2021. "Regime switching effect of COVID-19 pandemic on renewable electricity generation in Denmark," Renewable Energy, Elsevier, vol. 175(C), pages 797-806.
    • Handle: RePEc:eee:renene:v:175:y:2021:i:c:p:797-806
    DOI: 10.1016/j.renene.2021.05.028
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    4. Fareed, Zeeshan & Pata, Ugur Korkut, 2022. "Renewable, non-renewable energy consumption and income in top ten renewable energy-consuming countries: Advanced Fourier based panel data approaches," Renewable Energy, Elsevier, vol. 194(C), pages 805-821.
    5. Daniel Stefan Armeanu & Stefan Cristian Gherghina & Jean Vasile Andrei & Camelia Catalina Joldes, 2022. "Modeling the impact of the COVID‐19 outbreak on environment, health sector and energy market," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 1387-1416, October.
    6. Li, Yi & Liu, Tianya & Xu, Jinpeng, 2023. "Analyzing the economic, social, and technological determinants of renewable and nonrenewable electricity production in China: Findings from time series models," Energy, Elsevier, vol. 282(C).
    7. Carla Cristiane Sokulski & Murillo Vetroni Barros & Rodrigo Salvador & Evandro Eduardo Broday & Antonio Carlos de Francisco, 2022. "Trends in Renewable Electricity Generation in the G20 Countries: An Analysis of the 1990–2020 Period," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    8. 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).
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