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dc.contributor.authorAdebayo, T. S.en
dc.contributor.authorAltuntaş, M.en
dc.contributor.authorGoyibnazarov, S.en
dc.contributor.authorAgyekum, E. B.en
dc.contributor.authorZawbaa, H. M.en
dc.contributor.authorKamel, S.en
dc.date.accessioned2024-04-22T15:52:30Z-
dc.date.available2024-04-22T15:52:30Z-
dc.date.issued2022-
dc.identifier.citationAdebayo, TS, Altuntaş, M, Goyibnazarov, S, Agyekum, EB, Zawbaa, HM & Kamel, S 2022, 'Dynamic effect of disintegrated energy consumption and economic complexity on environmental degradation in top economic complexity economies', Energy Reports, Том. 8, стр. 12832-12842. https://doi.org/10.1016/j.egyr.2022.09.161harvard_pure
dc.identifier.citationAdebayo, T. S., Altuntaş, M., Goyibnazarov, S., Agyekum, E. B., Zawbaa, H. M., & Kamel, S. (2022). Dynamic effect of disintegrated energy consumption and economic complexity on environmental degradation in top economic complexity economies. Energy Reports, 8, 12832-12842. https://doi.org/10.1016/j.egyr.2022.09.161apa_pure
dc.identifier.issn2352-4847
dc.identifier.otherFinal2
dc.identifier.otherAll Open Access; Gold Open Access; Green Open Access3
dc.identifier.otherhttps://doi.org/10.1016/j.egyr.2022.09.1611
dc.identifier.otherhttps://doi.org/10.1016/j.egyr.2022.09.161pdf
dc.identifier.urihttp://elar.urfu.ru/handle/10995/132318-
dc.description.abstractThe current paper explores the influence of disintegrated energy and economic complexity on CO2 emissions (CO2) in the top economic complexity economies. The model also incorporates other drivers of CO2, such as technological innovation and economic growth. The current research utilizes data stretching from 1993 to 2018. The research employed Westerlund cointegration, fully modified OLS (FMOLS), dynamic OLS (DOLS), and method of moments quantile regression (MMQR) to evaluate these interconnections. The outcomes of the slope heterogeneity and cross-sectional dependence affirmed the use of second-generation techniques. The study confirmed the long-run association between CO2 and the regressors. The results of the MMQR disclosed that in each quantile (0.1–0.90), renewable energy enhances the quality of the environment, while economic complexity and nonrenewable energy intensify CO2. In addition, technological innovation enhances the quality of the environment from 0.1–0.70 quantiles, while from 0.80–90 quantiles, technological innovation intensifies CO2. The EKC is also validated in each quantile (0.1–0.90). The DOLS, FE-OLS, and FMOLS outcomes also affirm the MMQR outcomes. These outcomes encourage policymakers to implement holistic economic and environmental policies that prioritize greener production processes for environmental reasons and meet the United Nations SDGs 7, 8, 13, and 17. © 2022 The Author(s)en
dc.description.sponsorshipEuropean Union's Horizon 2020 Research and Enterprise Irelanden
dc.description.sponsorshipEuropean Union’s Horizon 2020 Research and Enterprise Irelanden
dc.description.sponsorshipNational Research and Development Agency of Chile, (ANID/Fondap/15110019)en
dc.description.sponsorshipH2020 Marie Skłodowska-Curie Actions, MSCA, (847402)en
dc.description.sponsorshipMinistry of Education and Science of the Russian Federation, Minobrnauka, (FEUZ-2022-0031)en
dc.description.sponsorshipFunding text 1: The authors thank the support of the National Research and Development Agency of Chile (ANID) , ANID/Fondap/15110019 .en
dc.description.sponsorshipFunding text 2: The author (Ephraim Bonah Agyekum) acknowledges the research funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University Program of Development within the Priority-2030 Program), the youth laboratory with Grant number FEUZ-2022-0031 .en
dc.description.sponsorshipFunding text 3: The work of Hossam M. Zawbaa was supported by the European Union’s Horizon 2020 Research and Enterprise Ireland under the Marie Skłodowska-Curie Grant 847402 .en
dc.description.sponsorshipFunding text 4: The work of Hossam M. Zawbaa was supported by the European Union's Horizon 2020 Research and Enterprise Ireland under the Marie Skłodowska-Curie Grant 847402. The author (Ephraim Bonah Agyekum) acknowledges the research funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University Program of Development within the Priority-2030 Program), the youth laboratory with Grant number FEUZ-2022-0031. The authors thank the support of the National Research and Development Agency of Chile (ANID), ANID/Fondap/15110019.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherElsevier Ltden
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.rightscc-by-nc-ndother
dc.sourceEnergy Reports2
dc.sourceEnergy Reportsen
dc.subjectCO<SUB>2</SUB>EMISSIONSen
dc.subjectDISINTEGRATED ENERGY CONSUMPTIONen
dc.subjectECONOMIC COMPLEXITYen
dc.subjectTECHNOLOGICAL INNOVATIONen
dc.subjectCARBON DIOXIDEen
dc.subjectECONOMIC AND SOCIAL EFFECTSen
dc.subjectECONOMICSen
dc.subjectENVIRONMENTAL PROTECTIONen
dc.subjectMETHOD OF MOMENTSen
dc.subject'CURRENTen
dc.subjectCO 2 EMISSIONen
dc.subjectDISINTEGRATED ENERGY CONSUMPTIONen
dc.subjectDYNAMIC EFFECTSen
dc.subjectECONOMIC COMPLEXITYen
dc.subjectENERGYen
dc.subjectENERGY ECONOMICSen
dc.subjectENERGY-CONSUMPTIONen
dc.subjectQUANTILE REGRESSIONen
dc.subjectTECHNOLOGICAL INNOVATIONen
dc.subjectENERGY UTILIZATIONen
dc.titleDynamic effect of disintegrated energy consumption and economic complexity on environmental degradation in top economic complexity economiesen
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.1016/j.egyr.2022.09.161-
dc.identifier.scopus85139996647-
local.contributor.employeeAdebayo T.S., Department of Economics, Faculty of Economics and Administrative Science, Cyprus International University, Nicosia, Northern Cyprus, 99040, Turkeyen
local.contributor.employeeAltuntaş M., Faculty of Economics, Administrative and Social Sciences, Department of Economics, Nisantasi University, Turkeyen
local.contributor.employeeGoyibnazarov S., Department of Human Resources Management, Tashkent State University of Economics, Uzbekistanen
local.contributor.employeeAgyekum E.B., Department of Nuclear and Renewable Energy, Ural Federal University Named after the First President of Russia Boris, 19 Mira Street, Yeltsin, Ekaterinburg, 620002, Russian Federationen
local.contributor.employeeZawbaa H.M., Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypt, Technological University Dublin, Dublin, Irelanden
local.contributor.employeeKamel S., Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan, 81542, Egypten
local.description.firstpage12832
local.description.lastpage12842
local.issue4
local.volume8
dc.identifier.wos000877517000004-
local.contributor.departmentDepartment of Economics, Faculty of Economics and Administrative Science, Cyprus International University, Nicosia, Northern Cyprus, 99040, Turkeyen
local.contributor.departmentFaculty of Economics, Administrative and Social Sciences, Department of Economics, Nisantasi University, Turkeyen
local.contributor.departmentDepartment of Human Resources Management, Tashkent State University of Economics, Uzbekistanen
local.contributor.departmentDepartment of Nuclear and Renewable Energy, Ural Federal University Named after the First President of Russia Boris, 19 Mira Street, Yeltsin, Ekaterinburg, 620002, Russian Federationen
local.contributor.departmentFaculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypten
local.contributor.departmentTechnological University Dublin, Dublin, Irelanden
local.contributor.departmentElectrical Engineering Department, Faculty of Engineering, Aswan University, Aswan, 81542, Egypten
local.identifier.pure8ee251d8-485c-4861-8715-77dffe867d91uuid
local.identifier.pure31571301-
local.identifier.eid2-s2.0-85139996647-
local.identifier.wosWOS:000877517000004-
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