Dynamic relationships between energy use, income, and environmental degradation in Afghanistan
This study examines the dynamic relationship between energy use, income, and environmental degradation in Afghanistan using annual data from 1970 to 2016. The dynamic causal relationship among variables are being tested; grounded by four testable hypotheses (growth, conservation, feedback, and neutr...
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my.uniten.dspace-257492023-05-29T16:13:46Z Dynamic relationships between energy use, income, and environmental degradation in Afghanistan Yusoff N.Y.B.M. Bekhet H.A. Mahrwarz S.M. 55812094300 37100908800 57215855853 This study examines the dynamic relationship between energy use, income, and environmental degradation in Afghanistan using annual data from 1970 to 2016. The dynamic causal relationship among variables are being tested; grounded by four testable hypotheses (growth, conservation, feedback, and neutrality). The F-bounds test, Dynamic OLS, and VECM Granger causality are utilized. The empirical results confirm that there is a long-run relationship among the variables and the energy use and GDP both affects the CO2 emissions in the long run. The conservation and environmental policies would have detrimental impact to economic growth of Afghanistan, as this country become an energy dependent country. In the short run, there is bidirectional causality running from energy use and economic growth. These results support the �feedback hypothesis� and possesses some policy implications which suggests that economic development and energy use may be jointly determined since economic growth is closely related to energy consumption. � 2020, Econjournals. All rights reserved. Final 2023-05-29T08:13:46Z 2023-05-29T08:13:46Z 2020 Article 10.32479/ijeep.8249 2-s2.0-85082142090 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082142090&doi=10.32479%2fijeep.8249&partnerID=40&md5=52b033f08fd720d97552c415a027cab3 https://irepository.uniten.edu.my/handle/123456789/25749 10 3 51 61 All Open Access, Gold, Green Econjournals Scopus |
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This study examines the dynamic relationship between energy use, income, and environmental degradation in Afghanistan using annual data from 1970 to 2016. The dynamic causal relationship among variables are being tested; grounded by four testable hypotheses (growth, conservation, feedback, and neutrality). The F-bounds test, Dynamic OLS, and VECM Granger causality are utilized. The empirical results confirm that there is a long-run relationship among the variables and the energy use and GDP both affects the CO2 emissions in the long run. The conservation and environmental policies would have detrimental impact to economic growth of Afghanistan, as this country become an energy dependent country. In the short run, there is bidirectional causality running from energy use and economic growth. These results support the �feedback hypothesis� and possesses some policy implications which suggests that economic development and energy use may be jointly determined since economic growth is closely related to energy consumption. � 2020, Econjournals. All rights reserved. |
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55812094300 |
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55812094300 Yusoff N.Y.B.M. Bekhet H.A. Mahrwarz S.M. |
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Article |
author |
Yusoff N.Y.B.M. Bekhet H.A. Mahrwarz S.M. |
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Yusoff N.Y.B.M. Bekhet H.A. Mahrwarz S.M. Dynamic relationships between energy use, income, and environmental degradation in Afghanistan |
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Yusoff N.Y.B.M. |
title |
Dynamic relationships between energy use, income, and environmental degradation in Afghanistan |
title_short |
Dynamic relationships between energy use, income, and environmental degradation in Afghanistan |
title_full |
Dynamic relationships between energy use, income, and environmental degradation in Afghanistan |
title_fullStr |
Dynamic relationships between energy use, income, and environmental degradation in Afghanistan |
title_full_unstemmed |
Dynamic relationships between energy use, income, and environmental degradation in Afghanistan |
title_sort |
dynamic relationships between energy use, income, and environmental degradation in afghanistan |
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Econjournals |
publishDate |
2023 |
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1806423238935314432 |
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13.222552 |