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    A visualization review analysis of the last two decades for environmental Kuznets curve "EKC" based on co-citation analysis theory and pathfinder network scaling algorithms
    (SPRINGER HEIDELBERG, 2021) Öztürk, İlhan; Koondhar, Mansoor Ahmed; Shahbaz, Muhammad; Memon, Kamran Ali; Kong, Rong
    Environmental Kuznets curve (EKC) is a statistical tool to examine the cointegration and causality nexus between economic growth and carbon emissions. The EKC is widely used in energy and environmental economics studies. Although a large number of researchers have analyzed the EKC by applying different statistical models, some review work has been summarized to draw a pictorial view of extending studies in this research field. However, still, the macroscopic overview needs to be considered. Therefore, this study aims to contribute to the literature for finding a new pathway for further research employing, and to facilitate this research, scientometric analysis is carried out by feature in CiteSpace. The dataset was screened and found 2384 records out of 59,225 Web of Science (WoS) references, and the records for the timespan 1999–2019 was used to visualize the knowledge map and outcome of the scientific enterprise. The visualization results reveal the most influencing studies, institutions, authors, countries, keywords, and category cloud, in the research field of EKC. This article reveals that the research on EKC in alignment with green and sustainable technology science requires more attention. Further, this article would help authors and publishers make their decisions for the research of EKC and planning for future perspectives to contribute to academic development and applied methodology.
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    Öğe
    Revisiting the relationship between carbon emission, renewable energy consumption, forestry, and agricultural financial development for China
    (Springer Heidelberg, 2021) Koondhar, Mansoor Ahmed; Shahbaz, Muhammad; Ozturk, Ilhan; Randhawa, Abid Ali; Kong, Rong
    Globally, the use of modern technologies is increasing along with carbon emission due to the consumption of fossil fuels to operate modern technologies. Therefore, in this study, we aimed to investigate the relationship between carbon emission, renewable energy consumption, forestry, and agricultural value added per capita from 1998 to 2018. The auto-regressive distribution lag model was estimated for long-run and short-run correlation analysis. The results of this study revealed that carbon emission decreases owed increases in forest areas in the long and well as short-run nexus. Furthermore, in the short run, carbon emission decreases due to an increase in renewable energy consumption. In addition, the carbon emission was run in an upward direction parallel to agricultural financial development. Furthermore, this study confirmed that the unidirectional causality between variables by estimating the non-Granger causality test. Therefore, this study suggests that to combat carbon emissions with carbon emission, it is necessary to switch from nonrenewable energy to renewable energies and organic fertilizer consumption along with afforestation to make the climate free from carbon.