Analyzing the effect of natural gas, nuclear energy and renewable energy on GDP and carbon emissions: A multi-variate panel data analysis
Internationally, the importance of clean energy is greatly appreciated in the context of sustainable development and to protect the atmosphere. Therefore, the objective of this article is to determine the effect of natural gas, renewable energy and nuclear energy consumption on economic growth and c...
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Veröffentlicht in: | Energy (Oxford) 2021-03, Vol.219, p.119592, Article 119592 |
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creator | Azam, Anam Rafiq, Muhammad Shafique, Muhammad Zhang, Haonan Yuan, Jiahai |
description | Internationally, the importance of clean energy is greatly appreciated in the context of sustainable development and to protect the atmosphere. Therefore, the objective of this article is to determine the effect of natural gas, renewable energy and nuclear energy consumption on economic growth and carbon dioxide emissions in the ten highest CO2 emitting countries within a multivariate context for the duration of 1990–2014. The panel co-integration test, panel fully modified ordinary least squares and panel heterogonous Dumitrescu and Hurlin causality assessment are used to analyze the estimation of long-run elasticity along with the course of causality among the variables. The panel co-integration test confirms the existence of a long-run equilibrium correlation among the variables. The findings of the long run elasticity and causality test reveal that natural gas does not contribute to economic growth and CO2 reduction like nuclear energy and renewable energy. However, except for natural gas, the expansion and improvement of renewable energy and nuclear energy are vital to avoid global warming and climate change as well as to promote economic growth.
•Assessed long term impacts of Renewable Energy, Financial Development and Nuclear Energy on CO2 emissions.•Evaluate the energy consumptions and GDP effects on carbon footprints.•Renewable Energy and Nuclear Energy lead to significant conditions to clean energy production.•Results can help policymakers in the enactment of future policies with carbon emission abatement. |
doi_str_mv | 10.1016/j.energy.2020.119592 |
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•Assessed long term impacts of Renewable Energy, Financial Development and Nuclear Energy on CO2 emissions.•Evaluate the energy consumptions and GDP effects on carbon footprints.•Renewable Energy and Nuclear Energy lead to significant conditions to clean energy production.•Results can help policymakers in the enactment of future policies with carbon emission abatement.</description><identifier>ISSN: 0360-5442</identifier><identifier>EISSN: 1873-6785</identifier><identifier>DOI: 10.1016/j.energy.2020.119592</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Carbon dioxide ; Carbon dioxide emissions ; Causality ; Clean energy ; Climate change ; CO2 emission ; Context ; Data analysis ; Economic development ; Economic growth ; Economics ; Elasticity ; Emissions ; Energy consumption ; GDP ; Global warming ; Integration ; Longitudinal studies ; Natural gas ; Nuclear energy ; Nuclear engineering ; Nuclear reactors ; Renewable energy ; Renewable resources ; Sustainable development</subject><ispartof>Energy (Oxford), 2021-03, Vol.219, p.119592, Article 119592</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright Elsevier BV Mar 15, 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-84a83bb24cdc9002d5fc6627e297e1e1dd3ccbc10f76c3b96f60ff1f1b818b393</citedby><cites>FETCH-LOGICAL-c400t-84a83bb24cdc9002d5fc6627e297e1e1dd3ccbc10f76c3b96f60ff1f1b818b393</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.energy.2020.119592$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,45974</link.rule.ids></links><search><creatorcontrib>Azam, Anam</creatorcontrib><creatorcontrib>Rafiq, Muhammad</creatorcontrib><creatorcontrib>Shafique, Muhammad</creatorcontrib><creatorcontrib>Zhang, Haonan</creatorcontrib><creatorcontrib>Yuan, Jiahai</creatorcontrib><title>Analyzing the effect of natural gas, nuclear energy and renewable energy on GDP and carbon emissions: A multi-variate panel data analysis</title><title>Energy (Oxford)</title><description>Internationally, the importance of clean energy is greatly appreciated in the context of sustainable development and to protect the atmosphere. Therefore, the objective of this article is to determine the effect of natural gas, renewable energy and nuclear energy consumption on economic growth and carbon dioxide emissions in the ten highest CO2 emitting countries within a multivariate context for the duration of 1990–2014. The panel co-integration test, panel fully modified ordinary least squares and panel heterogonous Dumitrescu and Hurlin causality assessment are used to analyze the estimation of long-run elasticity along with the course of causality among the variables. The panel co-integration test confirms the existence of a long-run equilibrium correlation among the variables. The findings of the long run elasticity and causality test reveal that natural gas does not contribute to economic growth and CO2 reduction like nuclear energy and renewable energy. However, except for natural gas, the expansion and improvement of renewable energy and nuclear energy are vital to avoid global warming and climate change as well as to promote economic growth.
•Assessed long term impacts of Renewable Energy, Financial Development and Nuclear Energy on CO2 emissions.•Evaluate the energy consumptions and GDP effects on carbon footprints.•Renewable Energy and Nuclear Energy lead to significant conditions to clean energy production.•Results can help policymakers in the enactment of future policies with carbon emission abatement.</description><subject>Carbon dioxide</subject><subject>Carbon dioxide emissions</subject><subject>Causality</subject><subject>Clean energy</subject><subject>Climate change</subject><subject>CO2 emission</subject><subject>Context</subject><subject>Data analysis</subject><subject>Economic development</subject><subject>Economic growth</subject><subject>Economics</subject><subject>Elasticity</subject><subject>Emissions</subject><subject>Energy consumption</subject><subject>GDP</subject><subject>Global warming</subject><subject>Integration</subject><subject>Longitudinal studies</subject><subject>Natural gas</subject><subject>Nuclear energy</subject><subject>Nuclear engineering</subject><subject>Nuclear reactors</subject><subject>Renewable energy</subject><subject>Renewable resources</subject><subject>Sustainable development</subject><issn>0360-5442</issn><issn>1873-6785</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9UMtOwzAQtBBIlMIfcLDElRTbedkckKoCBakSHOBsOc66uEqdYidF5Q_4a1wCV077nN2ZQeickgkltLhaTcCBX-4mjLDYoiIX7ACNKC_TpCh5fohGJC1IkmcZO0YnIawIITkXYoS-pk41u0_rlrh7AwzGgO5wa7BTXe9Vg5cqXGLX6waUx8MbrFyNfcw_VNXAX7N1eH77_DPTylexhLUNwbYuXOMpXvdNZ5Ot8lZ1gDfKQYNr1akIiASCDafoyKgmwNlvHKPX-7uX2UOyeJo_zqaLRGeEdAnPFE-rimW61oIQVudGFwUrgYkSKNC6TrWuNCWmLHRaicIUxBhqaMUpr1KRjtHFcHfj2_ceQidXbe8jiSBZJkhJGec8bmXDlvZtCB6M3Hi7Vn4nKZF70-VKDsLl3nQ5mB5hNwMMooKtBS-DtuA01NZHY2Xd2v8PfANYwo5j</recordid><startdate>20210315</startdate><enddate>20210315</enddate><creator>Azam, Anam</creator><creator>Rafiq, Muhammad</creator><creator>Shafique, Muhammad</creator><creator>Zhang, Haonan</creator><creator>Yuan, Jiahai</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope></search><sort><creationdate>20210315</creationdate><title>Analyzing the effect of natural gas, nuclear energy and renewable energy on GDP and carbon emissions: A multi-variate panel data analysis</title><author>Azam, Anam ; 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Therefore, the objective of this article is to determine the effect of natural gas, renewable energy and nuclear energy consumption on economic growth and carbon dioxide emissions in the ten highest CO2 emitting countries within a multivariate context for the duration of 1990–2014. The panel co-integration test, panel fully modified ordinary least squares and panel heterogonous Dumitrescu and Hurlin causality assessment are used to analyze the estimation of long-run elasticity along with the course of causality among the variables. The panel co-integration test confirms the existence of a long-run equilibrium correlation among the variables. The findings of the long run elasticity and causality test reveal that natural gas does not contribute to economic growth and CO2 reduction like nuclear energy and renewable energy. However, except for natural gas, the expansion and improvement of renewable energy and nuclear energy are vital to avoid global warming and climate change as well as to promote economic growth.
•Assessed long term impacts of Renewable Energy, Financial Development and Nuclear Energy on CO2 emissions.•Evaluate the energy consumptions and GDP effects on carbon footprints.•Renewable Energy and Nuclear Energy lead to significant conditions to clean energy production.•Results can help policymakers in the enactment of future policies with carbon emission abatement.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.energy.2020.119592</doi></addata></record> |
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subjects | Carbon dioxide Carbon dioxide emissions Causality Clean energy Climate change CO2 emission Context Data analysis Economic development Economic growth Economics Elasticity Emissions Energy consumption GDP Global warming Integration Longitudinal studies Natural gas Nuclear energy Nuclear engineering Nuclear reactors Renewable energy Renewable resources Sustainable development |
title | Analyzing the effect of natural gas, nuclear energy and renewable energy on GDP and carbon emissions: A multi-variate panel data analysis |
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