Evaluating the impact of technological innovation and energy efficiency on load capacity factor: empirical analysis of India
In: Environmental science and pollution research: ESPR, Band 31, Heft 4, S. 5610-5624
ISSN: 1614-7499
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In: Environmental science and pollution research: ESPR, Band 31, Heft 4, S. 5610-5624
ISSN: 1614-7499
In: International journal of trade and global markets, Band 1, Heft 1, S. 1
ISSN: 1742-755X
In: International journal of trade and global markets, Band 16, Heft 1/2/3, S. 96
ISSN: 1742-755X
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In: Environmental science and pollution research: ESPR, Band 26, Heft 11, S. 11191-11211
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 30, Heft 38, S. 88861-88875
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 30, Heft 6, S. 16372-16385
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 28, Heft 41, S. 57582-57601
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 28, Heft 11, S. 13454-13468
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 27, Heft 9, S. 10115-10128
ISSN: 1614-7499
In: Economic change & restructuring, Band 57, Heft 3
ISSN: 1574-0277
AbstractThe objective of this paper is to assess the dynamic volatility connectedness between fossil energy, clean energy, and major assets i.e., Bonds, Bitcoin, Dollar index, Gold, and Standard and Poor's 500 from September 17, 2014 to October 11, 2022. The main motivation of the study relates to examining the dynamic volatility connectedness mentioned during periods of important events such as the recent coronavirus pandemic and the Russia–Ukraine conflict which has shown the vulnerability of economic and financial assets, energy commodities, and clean energy. The novel Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) approach is employed for the investigation of the sample period mentioned. Empirical analysis reveals that both the total and net volatility connectedness between assets is time-varying. The highest connectedness among the assets is observed with the onset of the coronavirus (COVID-19) pandemic, and it increases with some important international events, such as the Russia–Ukraine conflict, the referendum of Brexit, China–US trade war, and Brexit day. On average, the result shows that 32.8% of the volatility in one asset spills over to all other assets. The DCC-GARCH results also indicate that crude oil, bonds, and Bitcoin act as almost pure volatility transmitters, whereas the Dollar index, gold, and S&P500 act as volatility receivers. On the other hand, clean energy is found neutral to external shocks until the first quarter of 2020 and after that time, it starts to behave as a volatility transmitter. Based on the obtained results, we offer some specific policy implications that are beneficial to the US economy and other countries.
Graphical Abstract
Dynamic volatility connectedness between fossil energy, clean energy, and major assets (Bonds, Bitcoin, Dollar index, Gold, and Standard and Poor's 500)
In: Environmental science and pollution research: ESPR, Band 31, Heft 10, S. 14912-14926
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 27, Heft 32, S. 40456-40474
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 27, Heft 32, S. 40109-40120
ISSN: 1614-7499