2019
DOI: 10.1016/j.scitotenv.2019.02.063
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Heterogeneous impacts of renewable energy and environmental patents on CO2 emission - Evidence from the BRIICS

Abstract: The study explores the impacts of renewable energy, environmental patents, economic growth 14 and other variables on the CO2 emission per capita from 2000 to 2013 for the BRIICS countries. Using 15 both the panel OLS methods and panel quantile regression method, we find that the effects of the 16 determinant variables are heterogeneous across quantiles. Specifically, renewable energy supply reduces 17 CO2 emissions per capita, with the strongest effect at the 95th quantile. Development of environmental 18 pate… Show more

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Cited by 329 publications
(132 citation statements)
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References 53 publications
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“…Evidence put forward in Exhibit 9 also demonstrate that green energy investments (REit) produce a negative and significant relationship with GHG emissions in all quantiles, and the 80th and 90th quantiles have the strongest impact which largely agrees with Cheng, Ren, Wang, and Yan (2019) survey on the BRICS. On the contrary, labor status (HCit) produces a positive and significant link with GHG emissions in all quantiles.…”
Section: Resultssupporting
confidence: 72%
“…Evidence put forward in Exhibit 9 also demonstrate that green energy investments (REit) produce a negative and significant relationship with GHG emissions in all quantiles, and the 80th and 90th quantiles have the strongest impact which largely agrees with Cheng, Ren, Wang, and Yan (2019) survey on the BRICS. On the contrary, labor status (HCit) produces a positive and significant link with GHG emissions in all quantiles.…”
Section: Resultssupporting
confidence: 72%
“…They advised that China should encourage FDI with advanced production technology. For other recent research, see Jiao et al [ 29 ], Ning and Wang [ 30 ], Shao et al [ 31 ], Cheng et al [ 32 ], and Khan et al [ 33 ].…”
Section: Literature Reviewmentioning
confidence: 99%
“…The mean deviation is greater from the standard deviation. The individual indicator shows a significant effect on each individual variable (Cheng, Ren, Wang, & Yan, 2019;Im et al, 2003;Saqib, Ahmad, & Amezcua-Prieto, 2018;Zhao & Kim, 2009). The given results of analysis have interoperated the distribution t-factors within between valuation.…”
Section: Results and Analysismentioning
confidence: 97%