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Please use this identifier to cite or link to this item: https://digital.lib.ueh.edu.vn/handle/UEH/70338
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dc.contributor.authorMuhammad Sadiq-
dc.contributor.otherKa Yin Chau-
dc.contributor.otherNguyen Tran Thai Ha-
dc.contributor.otherThi Thu Hien Phan-
dc.contributor.otherThanh Quang Ngo-
dc.contributor.otherPham Quang Huy-
dc.date.accessioned2023-11-29T08:45:13Z-
dc.date.available2023-11-29T08:45:13Z-
dc.date.issued2023-
dc.identifier.issn1674-9871 (Print), 2588-9192 (Online)-
dc.identifier.urihttps://digital.lib.ueh.edu.vn/handle/UEH/70338-
dc.description.abstractA sharp increase in economic and human development has multiplied the carbon intensity due to which there is a significant need of effective strategies in order to curb carbon emissions. Thus, the present study aims to examine the effective of green finance, eco-innovation, renewable energy output (REO), renewable energy consumption (REC), and carbon taxes on carbon dioxide (CO2) emissions in BRICS countries in the time of 2001–2020. Cross-sectional autoregressive distributed lag (CS ARDL) is used to test the connection among the variables. Empirical estimations of CS-ARDL approach validates the effectiveness of green finance, eco-innovation, REO, REC, carbon taxes, and industrialization as the relationship of these factors with carbon emissions is negative in nature in BRICS economies. Based on the evidences, the study recommends the formulation of environmentally friendly practices and advancement in green finances to mitigate carbon emissions.en
dc.formatPortable Document Format (PDF)-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.relation.ispartofGeoscience Frontiers-
dc.rightsChina University of Geosciences (Beijing), Peking University-
dc.subjectGreen financeen
dc.subjectEco-innovationen
dc.subjectRenewable energy outputen
dc.subjectCarbon taxesen
dc.subjectEnvironmental degradationen
dc.subjectCO2 emissionsen
dc.titleThe impact of green finance, eco-innovation, renewable energy and carbon taxes on CO2 emissions in BRICS countries: Evidence from CS ARDL estimationen
dc.typeJournal Articleen
dc.identifier.doihttps://doi.org/10.1016/j.gsf.2023.101689-
ueh.JournalRankingScopus-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.cerifentitytypePublications-
item.fulltextOnly abstracts-
item.openairetypeJournal Article-
item.languageiso639-1en-
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