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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Environ. Sci.</journal-id>
<journal-title>Frontiers in Environmental Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Environ. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-665X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">860942</article-id>
<article-id pub-id-type="doi">10.3389/fenvs.2022.860942</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Environmental Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Do Oil Price Shocks Matter for Environmental Degradation? Evidence of the Environmental Kuznets Curve in GCC Countries</article-title>
<alt-title alt-title-type="left-running-head">Ebaid et al.</alt-title>
<alt-title alt-title-type="right-running-head">Oil Price Shocks Environmental Degradation</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Ebaid</surname>
<given-names>Ali</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/820983/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Lean</surname>
<given-names>Hooi Hooi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/78764/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Al-Mulali</surname>
<given-names>Usama</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1648610/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Economics Program</institution>, <institution>School of Social Sciences</institution>, <institution>Universiti Sains Malaysia</institution>, <addr-line>Penang</addr-line>, <country>Malaysia</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Faculty of Business</institution>, <institution>Sohar University</institution>, <addr-line>Sohar</addr-line>, <country>Oman</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1012534/overview">Gagan Deep Sharma</ext-link>, Guru Gobind Singh Indraprastha University, India</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1221312/overview">Muntasir Murshed</ext-link>, North South University, Bangladesh</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1568957/overview">Najia Saqib</ext-link>, Prince Sultan University, Saudi Arabia</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Hooi Hooi Lean, <email>learnmy@gmail.com</email>, <email>hooilean@usm.my</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Environmental Economics and Management, a section of the journal Frontiers in Environmental Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>13</day>
<month>05</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>860942</elocation-id>
<history>
<date date-type="received">
<day>24</day>
<month>01</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>14</day>
<month>04</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Ebaid, Lean and Al-Mulali.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Ebaid, Lean and Al-Mulali</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>This paper aims to examine the asymmetric impact of oil price shocks on environmental degradation for a panel of six Gulf Cooperation Council (GCC) countries from 1996 to 2016. We use the dynamic seemingly unrelated regressions (DSUR) approach that considers cross-sectional dependency to reveal the interrelations between oil price shocks and carbon dioxide (CO<sub>2</sub>) emissions. The finding shows that the positive shocks of oil prices have a statistically significant negative effect on CO<sub>2</sub> emissions, while negative shocks of oil prices did not affect CO<sub>2</sub> emissions. More specifically, the positive oil price shocks have negatively influenced the CO<sub>2</sub> emissions in Oman, Bahrain, Saudi Arabia, Qatar, and United Emirates Arab. In turn, the most negative effect is found in Qatar and Saudi Arabia. Meanwhile, the negative shocks of oil prices have statistically significant effects on the CO<sub>2</sub> emission of Oman and Saudi Arabia. While for other countries, it does not have a significant impact. Also, the results support an environmental Kuznets curve in Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates; in contrast, the hypothesis was rejected in Bahrain and Oman. This study could help policymakers adopt renewable energy policies and use energy-saving technologies to sustain economic development and improve environmental quality.</p>
</abstract>
<kwd-group>
<kwd>cross-sectional dependence</kwd>
<kwd>GCC countries</kwd>
<kwd>positive and negative oil price shocks</kwd>
<kwd>CO<sub>2</sub> emission</kwd>
<kwd>environmental kuznets curve</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Environmental degradation is well-known as a result of the dynamic interaction between social, institutional, technological, and economic, especially fluctuations in energy prices (<xref ref-type="bibr" rid="B6">Al-Mulali et al., 2016</xref>; <xref ref-type="bibr" rid="B63">Munir et al., 2019</xref>; <xref ref-type="bibr" rid="B53">Li et al., 2020</xref>; <xref ref-type="bibr" rid="B59">Malik et al., 2020</xref>). Environmental degradation is a worldwide issue in which carbon dioxide (CO<sub>2</sub>) emissions are a significant cause of global temperature increase (<xref ref-type="bibr" rid="B85">Usman et al., 2020</xref>; <xref ref-type="bibr" rid="B12">Anser et al., 2021</xref>). CO<sub>2</sub> has been used consistently as an indication of environmental degradation, with implications for air pollution, global warming and is responsible for climate change (<xref ref-type="bibr" rid="B1">Abokyi et al., 2019</xref>; <xref ref-type="bibr" rid="B21">Bayoumi and Fernandez, 2019</xref>; <xref ref-type="bibr" rid="B30">Charfeddine and Kahia, 2019</xref>; <xref ref-type="bibr" rid="B34">Ehigiamusoe and Lean, 2019</xref>; <xref ref-type="bibr" rid="B35">Ehigiamusoe et al., 2020</xref>; <xref ref-type="bibr" rid="B85">Usman et al., 2020</xref>). CO<sub>2</sub> is produced by burning solid fossil fuel waste, tree and wood products, and chemical reactions (<xref ref-type="bibr" rid="B88">Waqih et al., 2019</xref>). It is one of the most significant greenhouse gases that accounts for about 80% of global greenhouse gas emissions in the world (<xref ref-type="bibr" rid="B53">Li et al., 2020</xref>). This rise in CO<sub>2</sub> levels has resulted in environmental degradation such as erratic precipitation, depletion of the ozone layer, and biodiversity loss (<xref ref-type="bibr" rid="B3">Agbanike et al., 2019</xref>; <xref ref-type="bibr" rid="B4">Ahmed et al., 2020</xref>; <xref ref-type="bibr" rid="B8">Ali et al., 2020</xref>; <xref ref-type="bibr" rid="B15">Ari and Sent&#xfc;rk, 2020</xref>). As a result, CO<sub>2</sub> emissions have been included in this study as an indicator of the environmental degradation that may result from oil price shocks, especially in the Gulf Cooperation Council (GCC), which depends heavily on non-renewable sources such as oil (<xref ref-type="bibr" rid="B42">Haque, 2020</xref>).</p>
<p>Oil prices are viewed as a major contributor to increased economic growth and energy consumption at the expense of environmental quality in the literature (<xref ref-type="bibr" rid="B3">Agbanike et al., 2019</xref>; <xref ref-type="bibr" rid="B66">Murshed and Tanha, 2019</xref>; <xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>). Because of the challenges of environmental quality and climate change, oil price shocks continue to be a major source of concern for policymakers (<xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>). CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B43">He and Richard, 2010</xref>; <xref ref-type="bibr" rid="B40">Hammoudeh et al., 2014</xref>), air pollution (<xref ref-type="bibr" rid="B95">Chen and Lin, 2015</xref>), environmental degradation (<xref ref-type="bibr" rid="B74">Saboori et al., 2016</xref>), promoting energy substitution (<xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>), and energy consumption are all likely to be affected by oil price shocks in the positive and negative parts (<xref ref-type="bibr" rid="B3">Agbanike et al., 2019</xref>).</p>
<p>Numerous studies concentrate on the relationship between oil price and macroeconomic indicators (<xref ref-type="bibr" rid="B40">Hammoudeh et al., 2014</xref>; <xref ref-type="bibr" rid="B81">Tan et al., 2014</xref>; <xref ref-type="bibr" rid="B14">Apergis and Payne, 2015</xref>; <xref ref-type="bibr" rid="B41">Hammoudeh et al., 2015</xref>). Oil price fluctuates from time to time, and sometimes this fluctuation comes with shocks. Oil price shocks are formally defined as a change in oil price relative to the price of oil that consumers and companies have expected. In other words, it unexpected component of the oil price (<xref ref-type="bibr" rid="B50">Kilian and Stock, 2015</xref>). Oil price shocks are the most effective tool for managing resource allocation, investment and risk management, reducing the use of fossil fuels, energy conservation, and CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B52">Lean et al., 2015</xref>; <xref ref-type="bibr" rid="B33">Dong et al., 2017</xref>; <xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>).</p>
<p>Furthermore, positive and negative oil price shocks are likely to raise or decrease CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B40">Hammoudeh et al., 2014</xref>; <xref ref-type="bibr" rid="B28">Chai et al., 2016</xref>; <xref ref-type="bibr" rid="B79">Shahbaz et al., 2017</xref>; <xref ref-type="bibr" rid="B59">Malik et al., 2020</xref>). Higher oil prices, for example, could lower CO<sub>2</sub> emissions, according to the research (<xref ref-type="bibr" rid="B43">He and Richard, 2010</xref>; <xref ref-type="bibr" rid="B93">Zaghdoudi, 2017</xref>). Low oil prices may have resulted in greater usage of fossil fuels, which has exacerbated their negative effects on the environment by increasing CO<sub>2</sub> emissions. (<xref ref-type="bibr" rid="B86">Wang and Li, 2016</xref>; <xref ref-type="bibr" rid="B58">Maji et al., 2017</xref>; <xref ref-type="bibr" rid="B3">Agbanike et al., 2019</xref>). Detrimental oil price shocks, according to <xref ref-type="bibr" rid="B82">Ullah et al. (2020)</xref>, may have a negative impact on economic growth and maintain dirty environments in carbon emitters. Oil price shocks, in other words, may have asymmetric effects on CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B32">Constantinos et al., 2019</xref>; <xref ref-type="bibr" rid="B13">Apergis and Gangopadhyay, 2020</xref>; <xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>). Oil price shocks are an important variable because changes in energy costs can have a significant impact on pollution and CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B6">Al-Mulali et al., 2016</xref>; <xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>). As a result, while making environmental decisions to achieve sustainable development, a policy framework is essential. Understanding how oil price shocks affect CO<sub>2</sub> emissions in the GCC is critical for long-term economic development (GCC).</p>
<p>The relationship between oil price shocks and CO<sub>2</sub> emission has grabbed much attention from policymakers and researchers, where the focus is to reduce CO<sub>2</sub> emissions without affecting economic growth. Also, the intention to move towards the positive and negative shocks of oil prices has become imperative for environmental quality. Meanwhile, governments, market participants, and policymakers pay close attention to how oil price shocks affect the environment by raising CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B66">Murshed and Tanha, 2019</xref>; <xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>). On the other hand, to minimize the impact of positive and negative oil price shocks on environmental pollution or CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B13">Apergis, and Gangopadhyay, 2020</xref>), the use of clean and renewable energy sources has been urged (<xref ref-type="bibr" rid="B87">Wang et al., 2019</xref>). As a result, looking at the links between oil prices and environmental deterioration (for example, CO<sub>2</sub> emissions) can reveal significant behavioral biases in energy policy-making. Therefore, the symmetric effects of oil price shocks on CO<sub>2</sub> emissions must be re-examined.</p>
<p>Oil prices can drop dramatically in a matter of days, causing damage to any production or financing plans that rely on oil earnings in countries that rely on oil revenues. As a result, economic activities and growth may be affected. According to the Environmental Kuznets Curve (EKC) theory, economic expansion has a significant impact on pollution levels (<xref ref-type="bibr" rid="B51">Kuznets, 1955</xref>). As a result, the two most essential engines of economic activity are the price of oil and pricing margins. Oil waste, on the other hand, is a consequence of consumption and is an important pollutant in the environment. As a result, understanding how oil price shocks influence the environment is critical.</p>
<p>Policymakers and scholars have focused their attention on the relationship between oil price shocks and carbon emissions, intending to reduce CO<sub>2</sub> without affecting economic growth (<xref ref-type="bibr" rid="B58">Maji et al., 2017</xref>; <xref ref-type="bibr" rid="B3">Agbanike et al., 2019</xref>; <xref ref-type="bibr" rid="B82">Ullah et al., 2020</xref>). Oil price shocks and their impact on CO<sub>2</sub> emissions are a fascinating topic that needs to be investigated, particularly in light of the two extreme situations seen in the last decade, namely the peak in oil prices in 2008 and the ongoing drop in crude oil prices since 2014. (<xref ref-type="bibr" rid="B32">Constantinos et al., 2019</xref>). This study focuses on GCC-6 countries of Oman, Kuwait, Bahrain, UAE, Bahrain, Saudi Arabia, and Qatar as it is at the forefront of this problem. GCC-6 countries account for approximately 30% of the total crude oil reserves of the world (<xref ref-type="bibr" rid="B42">Haque, 2020</xref>) but provide about 33% of global primary energy consumption (<xref ref-type="bibr" rid="B45">IEA 2019</xref>). This implies that changes in oil prices will have significant effects on the environment.</p>
<p>For example, the Kingdom of Saudi Arabia is the ninth-largest CO<sub>2</sub> emitter in the Arab Gulf region, with 601,046 tonnes produced annually at a rate of 5.2 per cent (<xref ref-type="bibr" rid="B91">World Bank, 2016</xref>). Kuwait has some of the highest CO<sub>2</sub> emissions in the world (<xref ref-type="bibr" rid="B46">International Energy Agency, 2005</xref>), with CO<sub>2</sub> emissions per capita reaching 23.91 metric tonnes in 2018. (World Data Atlas, 2018). With CO<sub>2</sub> emissions of 218, 788, 684 tonnes in 2015 and an annual change of &#x2b;4.43 per cent, the UAE ranks among the world&#x2019;s greatest per capita emissions from fossil fuel burning (Global Benchmarks, 2016). Such variations in CO<sub>2</sub> emissions are one of the most difficult dangers to the environment in the GCC region, which is causing environmental damage. Therefore, we consider these countries as an appropriate sample based on their significant share of CO<sub>2</sub> emissions.</p>
<p>Oil-exporting countries, such as the GCC, rely largely on revenue from oil exports. As a result, the low price of oil has an impact on many elements of life in these countries, particularly economic activities and investment plans. Given oil price fluctuations have an impact on output, it is logical to expect them to have an impact on real GDP (<xref ref-type="bibr" rid="B19">Bergmann, 2019</xref>; <xref ref-type="bibr" rid="B68">Naseer et al., 2016</xref>). Venezuela is an outstanding example of the significance of negative oil price shocks to countries that rely on oil exports as their principal source of revenue over the previous 5&#xa0;years. Oil price shocks also have an impact on environmental pollution, as oil production and consumption activities are among the most significant polluters in the environment (<xref ref-type="bibr" rid="B26">Bruvoll and Medin, 2003</xref>). Furthermore, it is widely acknowledged that rising oil costs may compel countries to lower their energy consumption (<xref ref-type="bibr" rid="B6">Al-Mulali et al., 2016</xref>; <xref ref-type="bibr" rid="B3">Agbanike et al., 2019</xref>; <xref ref-type="bibr" rid="B42">Haque, 2020</xref>). As a result of the rise in energy prices, less energy will be consumed, resulting in lower CO<sub>2</sub> emissions (<xref ref-type="bibr" rid="B6">Al-Mulali et al., 2016</xref>; <xref ref-type="bibr" rid="B53">Li et al., 2020</xref>; <xref ref-type="bibr" rid="B59">Malik et al., 2020</xref>).</p>
<p>In the context of GCC-6 countries, this study poses the following research questions based on the previous discussion: Is it true that the EKC hypothesis holds in GCC? Is there a link between oil price shocks and environmental degradation? Do negative and positive oil price shocks affect CO<sub>2</sub> emissions? Aside from the theoretical foundation for the EKC, the hypothesis intuitively assumes a direct and explicit relationship between production and CO<sub>2</sub> emission. Apart from a few recent attempts, <xref ref-type="bibr" rid="B23">Boufateh (2019)</xref>, noticed the absence of the oil price element as a common feature of all publications on the EKC theory. The author suggested that adding more variables to the EKC hypothesis should be justified in such a way that the new variables reflect shock transmission pathways from production to CO<sub>2</sub> emissions, or at the very least proxies which are designed to take the place of these variables to guarantee that there is no endogeneity issue.</p>
<p>As a result, the aim is to test the EKC hypothesis and to study the implications of asymmetric oil price shocks on the verification of this hypothesis and on per capita CO<sub>2</sub> emission in the GCC. To begin, we used oil prices shocks (both negative and positive) to examine their impact on GCC carbon emissions, which is a novel contribution. However, the literature on the oil price shocks (both positive and negative shocks) and CO<sub>2</sub> emissions in GCC is limited. Within the existing GCC literature, support for the EKC hypothesis is still disputed in the case of Pakistan (<xref ref-type="bibr" rid="B6">Al-Mulali et al., 2016</xref>; <xref ref-type="bibr" rid="B42">Haque, 2020</xref>). Second, we have extended earlier research such as <xref ref-type="bibr" rid="B6">Al-Mulali and Ozturk (2016)</xref> and <xref ref-type="bibr" rid="B42">Haque (2020)</xref> by excluding energy consumption from our model to avoid biassing our findings, resulting in a more definitive EKC hypothesis and negative and positive oil price shocks as determinants of CO<sub>2</sub> emission in GCC.</p>
<p>Thirdly, this study selects 6 GCC countries, based on data availability, to investigate a gap in the empirical literature about the influence of oil price shocks (both positive and negative shocks) on CO<sub>2</sub> emissions in the GCC region using data from 1996 to 2016. Lastly, we have used a dynamic seemingly unrelated regression (DSUR) technique which assumes the long-term cross-sectional dependency (<xref ref-type="bibr" rid="B72">Pesaran, 2007</xref>) across the sample countries to examine the relationship between the variable of the study to assess how positive and negative price shocks impact CO<sub>2</sub> emission in the case of GCC. Shortly, this model has the advantage of being able to the knowledge of researchers&#x2019; and academicians&#x2019; expertise eager to employ panel data analysis and to overcome the contemporaneous correlation in the data. Also, we have been argued that linear ARDL and DOLS estimates methodology to explore the symmetric long-run relationship between the oil price shocks on CO<sub>2</sub> emissions.</p>
<p>Our empirical results confirm positive shocks of oil prices have a statistically significant negative effect on CO<sub>2</sub> emissions. Furthermore, they also confirm the presence of the EKC hypothesis in the selected GCC countries. Therefore, the findings of this study will make it possible for policymakers to better assimilate the predictive power of oil prices shocks (both negative and positive) price on CO<sub>2</sub> emissions in GCC. As a result, the GCC countries will be able to devise strategies to mitigate the effects of rising and falling oil prices on CO<sub>2</sub> emissions. The association between price shocks and CO<sub>2</sub> emissions will be used by governments to develop a risk management approach for dealing with energy price volatility. It would also make it easier to develop environmental policies and programs that address oil price volatility and a greater emphasis on clean economic growth, which might be more effective for environmental sustainability, government budget protection, and achieving stability. It would also help politicians establish suitable energy price policies and pay close attention to its leveraging effects, which would help GCC countries decrease environmental challenges and promote energy conservation in the long term.</p>
<p>The remainder section of this paper is structured as follows. <xref ref-type="sec" rid="s2">Section 2</xref> introduces the literature review of the research. <xref ref-type="sec" rid="s3">Section 3</xref> provides an overview of the GCC countries&#x2019; economies. <xref ref-type="sec" rid="s4">Section 4</xref> explains the data sources and methodology; <xref ref-type="sec" rid="s5">Section 5</xref> presents the results, <xref ref-type="sec" rid="s6">Section 6</xref> displays a discussion, and <xref ref-type="sec" rid="s7">Section 7</xref> gives the conclusion and policy implications.</p>
</sec>
<sec id="s2">
<title>2 Literature Review</title>
<p>A vast literature examines the effects of oil price shocks on different environmental degradation variables for oil-exporting and importing countries. For example, <xref ref-type="bibr" rid="B27">Cashin et al. (2014)</xref> argued that oil price shocks, directly and indirectly, affect the environment and ecology of oil-exporting and importing countries. The direct impact is a change in oil production and consumption, and the indirect effect is the shift of shocks through international trade. <xref ref-type="bibr" rid="B86">Wang and Li (2016)</xref> found that an increase (decrease) in oil prices reduces (increases) carbon intensity. Using the panel cointegration methodology (panel FMOLS and DOLS), <xref ref-type="bibr" rid="B93">Zaghdoudi (2017)</xref> discovered that oil prices have a statistically significant effect on CO<sub>2</sub> emission in the OECD countries. <xref ref-type="bibr" rid="B32">Constantinos et al. (2019)</xref> examined the relationship between crude oil prices and the volume of carbon emissions. The findings revealed that a rise or decrease in crude oil prices causes an asymmetric decline. This result is only applicable in the long term, as inelastic demand for crude oil may not translate to a reduction in carbon emissions in the short term.</p>
<p>In the short run, asymmetric effects are confirmed, running only from carbon emissions to crude oil prices. <xref ref-type="bibr" rid="B23">Boufateh (2019)</xref> realized that oil price shocks affect CO<sub>2</sub> emissions differently in China and the United States by applying the nonlinear ARDL approach. The results showed that positive and negative changes in crude oil prices have an impact on CO<sub>2</sub> emissions. <xref ref-type="bibr" rid="B53">Li et al. (2020)</xref> uncovered symmetric impacts of energy prices on CO<sub>2</sub> emissions in China. After controlling for other economic and energy market parameters as well as regional correlations of these variables, the results demonstrate that energy pricing has a considerable negative impact on China&#x2019;s CO<sub>2</sub> emissions. Likewise, the influence of low and high oil prices on CO<sub>2</sub> emissions in China was studied by <xref ref-type="bibr" rid="B22">Bilgili et al. (2020)</xref>. This study confirmed previous findings that oil prices have a negative impact on CO<sub>2</sub> emissions from 1960 to 2014. <xref ref-type="bibr" rid="B82">Ullah et al. (2020)</xref> found that the positive and negative changes in oil prices affect carbon emissions differently in the top ten carbon emitters countries in the short and long run. In a recent study, <xref ref-type="bibr" rid="B83">Umar et al. (2020)</xref> revealed that a 1% increase in energy price leads to a 0.02% decrease in carbon emission in 13 African nations.</p>
<p>Some studies examine the effects of oil price shocks on CO<sub>2</sub> emissions in oil-exporting countries. For example, <xref ref-type="bibr" rid="B43">He and Richard (2010)</xref> retrieved that oil prices have negative effects on CO<sub>2</sub> emissions in Canada. <xref ref-type="bibr" rid="B71">Payne (2012)</xref> indicated a significant long-term negative impact of oil prices on carbon dioxide emissions in the United States. <xref ref-type="bibr" rid="B40">Hammoudeh et al. (2014)</xref> found that positive oil price shocks have a negative impact on CO<sub>2</sub> emissions. <xref ref-type="bibr" rid="B74">Saboori et al. (2016)</xref> found evidence of the favorable effects of high oil prices on the environment in the context of OPEC countries. To put it another way, an increase in oil prices in exporting countries will drive their citizens to seek higher environmental quality. <xref ref-type="bibr" rid="B58">Maji et al. (2017)</xref> noticed that lower oil prices can increase carbon emissions and reduce environmental quality in Malaysia. <xref ref-type="bibr" rid="B70">Nwani (2017)</xref> showed that higher crude oil prices create economic conditions that generate more energy consumption and CO<sub>2</sub> emissions in Ecuador. <xref ref-type="bibr" rid="B3">Agbanike et al. (2019)</xref> discovered that rising crude oil prices increase energy consumption, government consumption expenditure, and energy consumption all result in CO<sub>2</sub> emissions, which have a detrimental impact on economic growth in Venezuela&#x2019;s oil-rich economy.</p>
<p>As for oil-importing countries, some studies examine the effects of oil price shocks on CO<sub>2</sub> emissions in oil-importing countries. <xref ref-type="bibr" rid="B18">Balaguer and Cantavella (2015)</xref> found that oil prices have negative effects on CO<sub>2</sub> emissions in Spain. Using the ARDL model, <xref ref-type="bibr" rid="B2">Abumunshar et al. (2020)</xref> investigated the causal relationship between oil price and Turkey&#x2019;s carbon emissions. The ARDL long-run coefficients revealed that oil prices had a long-term negative impact on CO<sub>2</sub> emissions in Turkey. In addition, the findings show that nonrenewable energy, such as oil, natural gas, and coal, increased CO<sub>2</sub> emissions. <xref ref-type="bibr" rid="B49">Jiao et al. (2021)</xref>, reveal higher oil prices and income inequality helped reduce carbon emissions in India using the NARDL technique in the long run from 1980 to 2018. Among the other important determinants of CO<sub>2</sub> emissions, <xref ref-type="bibr" rid="B64">Murshed (2020)</xref> discovered that higher crude oil prices reduce CO<sub>2</sub> emissions. A rise in the real price of crude oil reduces 0.16&#x2013;0.44%, on average, ceteris paribus. This could be attributed to higher oil costs lowering demand and the usage of crude oil, resulting in lower CO<sub>2</sub> emissions across selected South Asian economies: Bangladesh, Pakistan, India, Nepal, Sri Lanka, and the Maldives. Similarly, <xref ref-type="bibr" rid="B65">Murshed (2021)</xref> discovered that while liquefied petroleum gas (LPG) is a fossil fuel, it is a cleaner fuel than typically consumed fossil fuels like crude oil and coal, which helps to cut CO<sub>2</sub> emissions in South Asian countries. <xref ref-type="bibr" rid="B13">Apergis and Gangopadhyay (2020)</xref> attained that long-term relationships between pollution, energy use, and oil prices have been characterized by nonlinear and asymmetric linkages to indicate hidden co-complementarity. <xref ref-type="bibr" rid="B59">Malik et al. (2020)</xref> observed that an oil price increase will increase CO<sub>2</sub> emissions in the short run while reducing emissions in the long run in Pakistan. <xref ref-type="bibr" rid="B53">Li et al. (2020)</xref> found symmetric impacts of energy prices on CO<sub>2</sub> emissions in China.</p>
<p>Contrary to the expectations, some empirical studies showed that an enhancement (decline) in oil price has a positive (negative) impact on CO<sub>2</sub> emissions. <xref ref-type="bibr" rid="B62">Mensah et al. (2019)</xref> analyzed the effect of fossil fuel energy use, economic growth, and CO<sub>2</sub> emissions. They found the unidirectional causality from oil price to CO<sub>2</sub> emissions. <xref ref-type="bibr" rid="B31">Chaudhry et al. (2020)</xref> located that a decrease in oil price significantly affects environmental degradation in Pakistan. <xref ref-type="bibr" rid="B54">Lin and Jia (2019)</xref> obtained that higher energy price leads to a higher reduction of CO<sub>2</sub> emissions. <xref ref-type="bibr" rid="B94">Zhang et al. (2019)</xref> demonstrated that energy price contributes to a decrease in CO<sub>2</sub> emissions in China. <xref ref-type="bibr" rid="B87">Wang et al. (2019)</xref> revealed that removing oil price distortion will reduce CO<sub>2</sub> emissions of China&#x2019;s transport sector by 599 million tons in the studying period. <xref ref-type="bibr" rid="B37">Gbatu et al. (2019)</xref> investigated the short-and-long-run associations between CO<sub>2</sub> emissions and Liberia&#x2019;s key macroeconomic variables. According to ARDL and DOLS estimates, the results show a significant positive impact of oil price on CO<sub>2</sub> emissions in the long run. <xref ref-type="bibr" rid="B56">Mahmood et al. (2020)</xref> indicated a positive asymmetric impact of oil income share on CO<sub>2</sub> emissions in Saudi Arabia.</p>
<p>In terms of the GCC countries, most studies focus on examining the relationship between oil prices and the real GDP and energy consumption (see, for example, <xref ref-type="bibr" rid="B69">Nusair, 2016</xref>; <xref ref-type="bibr" rid="B67">Nasir et al., 2019</xref>; <xref ref-type="bibr" rid="B42">Haque, 2020</xref>). Only a few studies examine the relationship between oil price shocks and CO<sub>2</sub> emissions in the GCC countries or are limited to individual country studies. For example, <xref ref-type="bibr" rid="B10">Alshehry and Belloumi (2015)</xref> explored oil prices on GDP growth and CO<sub>2</sub> for Saudi Arabia. They find out that an upward trend in oil prices increases oil usage and deteriorates the environment by emitting more carbon emissions. However, focusing on single countries did not consider the shocks in oil prices (positive and negative). The results of this study are expected to encourage further studies on the potential relationship between oil price shocks and CO<sub>2</sub> emissions in all GCC countries.</p>
<p>In the recent research, <xref ref-type="bibr" rid="B42">Haque (2020)</xref> examined the nexus among changes in GDP per capita, crude oil price shocks, carbon emissions, trade, and population in GCC countries from 1985&#x2013;to 2014. The author found that oil price shocks negatively affect energy consumption, while the higher the energy consumption would increase CO<sub>2</sub> emissions. Mohammed et al. (2022) argued that oil is a major source of income and exports in the GCC countries, but it is pollution-oriented and accelerates CO<sub>2</sub> emissions in production and consumption activities. <xref ref-type="bibr" rid="B9">Aljadani et al. (2021)</xref> discovered that whereas oil price strengthens the link between economic growth and environmental quality at the level, quadratic, and cubic levels, oil rent weakens it. Furthermore, in the context of a COVID-19 outbreak, the long-term incidences of positive shocks to oil prices are not similar to the negative shock to CO<sub>2</sub> emissions, implying the existence of asymmetric consequences on CO<sub>2</sub> emissions in long-term forms. According to this study, an oil price shock could be beneficial to the Saudi economy&#x2019;s macroeconomic guidance in 2019&#x2013;2020. Therefore, a study on the relationship between oil price shocks and CO<sub>2</sub> emissions lacks in GCC from the reviewed literature. This study will contribute to the existing literature in this area by studying the impact of oil price shocks and CO<sub>2</sub> emissions.</p>
</sec>
<sec id="s3">
<title>3 Overview of the GCC Countries&#x2019; Economy</title>
<p>The GCC countries rely on economic and financial sources of income. This is because the oil sector accounts for a substantial portion of the government revenues in the GCC economy, and an increase in the oil sector has both direct and indirect effects on pollution emissions. The oil industry exports a lot of pollution as a direct result of its operations. The oil sector helps the economy of the GCC members flourish through exerting indirect influence. As a result of the booming oil sector, GCC governments can spend more on their economies, increasing pollution emissions as a result of the expansionary fiscal policy (<xref ref-type="bibr" rid="B55">Mahmood et al., 2022</xref>).</p>
<p>The oil production in these countries is highly interrelated to economic activity, fiscal revenue, export earnings, and foreign exchange (The Economic Outlook and Policy Challenges in the GCC Countries 2017). Hydrocarbon and governmental activities heavily funded by oil revenues account for the majority of total GDP in most GCC countries, which are the oil-exporting countries and rentier state countries. Furthermore, non-governmental sectors (non-oil sectors) often depend on oil. The primary sources of manufacturing value-added in GCC oil exporters include refinery, chemical, and other mining/extractive industries. Most of these activities derive from the oil industry. Concerning the fiscal revenue in the GCC, oil is the primary source of government revenue in most GCC countries. In 2014, the share of oil revenue in total revenue ranged from 24 per cent in Bahrein to 90 per cent in Kuwait, with 77 per cent as the average.</p>
<p>Similarly, regarding exports in all GCC except the UAE, oil is the main export product because it accounts for above 80 per cent of total exports in half of GCC, and above 60 per cent in all of them except the UAE (<xref ref-type="bibr" rid="B47">IMF annual report, 2016</xref>). Apart from economic issues in the GCC countries, environmental problems appear to be one of the urgent issues in GCC. Based on the <italic>Environmental Performance Index</italic> (EPI) index, all six countries occupy the centre. This situation became worse with significant revenues from the high oil price in the last 10&#xa0;years after toppling Saddam Hussein&#x2019;s regime in Iraq.</p>
<p>According to the Annual meeting of Arab ministries of finance held in April 2016, the report explains the relationship between oil price and economic growth. It also describes the six countries as countries that heavily depend on oil prices. In these countries, fiscal revenue, economic activity, export earnings, and foreign exchange rely on oil production.</p>
<p>In 2010, while crude oil&#x2019;s share of the world&#x2019;s fossil fuel consumption was 38%, the share of coal was 35%, and the share of natural gas was 27% of the total fossil fuel consumption. Thus, crude oil is the most significant demanded fossil fuel globally, and its fluctuations and determinant factors are among the most encouraging topics for energy researchers and economists. One important question arrive here: Do the oil price shocks impact environmental degradation in the short or long term in GCC countries? In addition, if the impact is exciting, is it asymmetric or symmetric or linear or nonlinear, what is its effect on the quality of the environment in the GCC.</p>
</sec>
<sec id="s4">
<title>4 Model, Data Description, and Methodology</title>
<sec id="s4-1">
<title>4.1 Model Specification</title>
<p>To investigate the effect of oil price shocks on environmental degradation, we specify the following empirical model (<xref ref-type="bibr" rid="B2">Abumunshar et al. (2020)</xref>; <xref ref-type="bibr" rid="B44">Husaini et al., 2021</xref>):<disp-formula id="e1">
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<label>(1)</label>
</disp-formula>where CO<sub>2</sub> is CO<sub>2</sub> emissions of country i in year&#xa0;t, GDPP and <inline-formula id="inf1">
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</inline-formula> are real GDP per capita and its square. EU is energy consumption per capita, oilP is oil prices and <inline-formula id="inf2">
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</inline-formula> is error terms. All variables are transformed to the natural logarithm because it allows us to interpret the results as elasticity.</p>
<p>According to EKC, we expect <inline-formula id="inf3">
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<p>To investigate the nonlinear effects of oil price shocks, we follow <xref ref-type="bibr" rid="B96">Shin et al. (2014)</xref>, <xref ref-type="bibr" rid="B117">Badeeb and Lean (2018)</xref>, <xref ref-type="bibr" rid="B17">Badeeb et al. (2021)</xref> and <xref ref-type="bibr" rid="B44">Husaini and Lean (2021)</xref> to decompose the oil price to positive <inline-formula id="inf7">
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</mml:math>
<label>(3)</label>
</disp-formula>
</p>
<p>Two variables <inline-formula id="inf9">
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</inline-formula> are defined in a cumulative form, and as can be seen, each positive and negative component has a permanent impact on the underlying variable. We incorporate the positive and negative components of oil price to investigate the nonlinear effects of oil price on CO<sub>2</sub> emission as the following regression model:<disp-formula id="e4">
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<label>(4)</label>
</disp-formula>
</p>
</sec>
<sec id="s4-2">
<title>4.2 Data Description</title>
<p>We compile the dependent and explanatory variables dataset for the six GCC countries, i.e., Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates, over 1996 to 2016. We collect the annual data on CO<sub>2</sub> emissions (metric tons per capita), and energy consumption per capita (million Btu per Person) from World Development Indicators (2020). We get the data of real GDP per capita from Pen World Table (PWT) version 9.1 and West Texas Intermediate (WTI) (US $ per bb) from the United States Energy Information Administration.</p>
<p>In <xref ref-type="fig" rid="F1">Figure 1</xref>, we display the bilateral relationship between explanatory variables and CO<sub>2</sub> emission, all of which are in logs form. In panel A, we present the bilateral relationship between real GDP per capita and CO<sub>2</sub> emission per capita and show the estimated line in red colour. The estimated line is <inline-formula id="inf11">
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<mml:mrow>
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<mml:mrow>
<mml:mn>0.208</mml:mn>
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</mml:mrow>
</mml:math>
</inline-formula> by pooled least squares estimator. As can be seen, the nonlinear effects of real income on CO<sub>2</sub> emissions are not rejected, and thus, the environmental Kuznets hypothesis among GCC countries is not rejected.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>bilateral correlation between explanatory variables and LCO<sub>2</sub>.</p>
</caption>
<graphic xlink:href="fenvs-10-860942-g001.tif"/>
</fig>
<p>In panels B and C, we present the bilateral relationship between CO<sub>2</sub> emission and energy use and CO<sub>2</sub> emission and oil prices. We can see that increasing energy use and oil prices will increase the CO<sub>2</sub> emission in the GCC countries. In panels D and E, the bilateral relations between CO<sub>2</sub> emission and positive components of oil prices and negative components are presented. Thus, there is a positive link between CO<sub>2</sub> emission and positive shocks in oil prices and a negative linkage between CO<sub>2</sub> emission and negative shocks in oil prices.</p>
<p>We present the descriptive statistics in <xref ref-type="table" rid="T1">Table 1</xref>. The results of the Jarque-Bera test indicate all variables except positive components of oil prices are distributed non-normally at the 5% significant level. In panel B, we present the bilateral correlation matrix. There is a positive linkage between CO<sub>2</sub> emission and all explanatory variables except negative shocks in oil prices. Except for the coefficient of <inline-formula id="inf12">
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</mml:math>
</inline-formula>, the signs of correlation between other variables are in line with our expectations.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Descriptive statistics.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left"/>
<th align="center">
<inline-formula id="inf34">
<mml:math id="m44">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>O</mml:mi>
<mml:msub>
<mml:mn>2</mml:mn>
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<mml:mi>t</mml:mi>
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</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
<th align="center">
<inline-formula id="inf35">
<mml:math id="m45">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
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</inline-formula>
</th>
<th align="center">
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<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
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</inline-formula>
</th>
<th align="center">
<inline-formula id="inf37">
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</inline-formula>
</th>
<th align="center">
<inline-formula id="inf38">
<mml:math id="m48">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
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<mml:mi>n</mml:mi>
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<mml:mi>g</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
<th align="center">
<inline-formula id="inf39">
<mml:math id="m49">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>p</mml:mi>
<mml:mi>o</mml:mi>
<mml:msub>
<mml:mi>s</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Mean</td>
<td align="char" char=".">3.059</td>
<td align="char" char=".">5.949</td>
<td align="char" char=".">10.479</td>
<td align="char" char=".">3.537</td>
<td align="char" char=".">&#x2212;1.709</td>
<td align="char" char=".">1.609</td>
</tr>
<tr>
<td align="left">Std. Dev.</td>
<td align="char" char=".">0.570</td>
<td align="char" char=".">0.651</td>
<td align="char" char=".">0.725</td>
<td align="char" char=".">0.606</td>
<td align="char" char=".">0.865</td>
<td align="char" char=".">1.301</td>
</tr>
<tr>
<td align="left">Skewness</td>
<td align="char" char=".">&#x2212;0.459</td>
<td align="char" char=".">&#x2212;0.717</td>
<td align="char" char=".">0.126</td>
<td align="char" char=".">0.438</td>
<td align="char" char=".">0.136</td>
<td align="char" char=".">0.285</td>
</tr>
<tr>
<td align="left">Kurtosis</td>
<td align="char" char=".">3.235</td>
<td align="char" char=".">3.077</td>
<td align="char" char=".">2.138</td>
<td align="char" char=".">1.886</td>
<td align="char" char=".">2.512</td>
<td align="char" char=".">1.547</td>
</tr>
<tr>
<td align="left">Jarque-Bera</td>
<td align="char" char=".">8.291</td>
<td align="char" char=".">19.082</td>
<td align="char" char=".">7.457</td>
<td align="char" char=".">18.564</td>
<td align="char" char=".">2.887</td>
<td align="char" char=".">22.534</td>
</tr>
<tr>
<td align="left">Probability</td>
<td align="char" char=".">0.016</td>
<td align="char" char=".">0.000</td>
<td align="char" char=".">0.024</td>
<td align="char" char=".">0.000</td>
<td align="char" char=".">0.236</td>
<td align="char" char=".">0.000</td>
</tr>
<tr>
<td align="left">Variable</td>
<td align="center">
<inline-formula id="inf40">
<mml:math id="m50">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>O</mml:mi>
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<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
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</mml:mrow>
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</inline-formula>
</td>
<td align="center">
<inline-formula id="inf41">
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<mml:mrow>
<mml:mi>E</mml:mi>
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<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
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</inline-formula>
</td>
<td align="center">
<inline-formula id="inf42">
<mml:math id="m52">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
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<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="center">
<inline-formula id="inf43">
<mml:math id="m53">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="center">
<inline-formula id="inf44">
<mml:math id="m54">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>n</mml:mi>
<mml:mi>e</mml:mi>
<mml:msub>
<mml:mi>g</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf45">
<mml:math id="m55">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.952</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf46">
<mml:math id="m56">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.631</td>
<td align="char" char=".">0.612</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf47">
<mml:math id="m57">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.623</td>
<td align="char" char=".">0.603</td>
<td align="char" char=".">0.999</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf48">
<mml:math id="m58">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.134</td>
<td align="char" char=".">0.140</td>
<td align="char" char=".">0.520</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf49">
<mml:math id="m59">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>n</mml:mi>
<mml:mi>e</mml:mi>
<mml:msub>
<mml:mi>g</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.175</td>
<td align="char" char=".">&#x2212;0.237</td>
<td align="char" char=".">&#x2212;0.321</td>
<td align="char" char=".">&#x2212;0.551</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf50">
<mml:math id="m60">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>p</mml:mi>
<mml:mi>o</mml:mi>
<mml:msub>
<mml:mi>s</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.179</td>
<td align="char" char=".">0.223</td>
<td align="char" char=".">0.455</td>
<td align="char" char=".">0.832</td>
<td align="char" char=".">&#x2212;0.922</td>
<td align="left"/>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s4-3">
<title>4.3 Methodology</title>
<p>We apply the second generation of panel data estimators to estimate the regression models 1) and (4). Hence, we follow a four-step estimation strategy. In the first step, we test the null hypothesis of cross-sectional dependence. In the second step, the stochastic properties of variables are tested using the second generation of the panel unit root test, namely <xref ref-type="bibr" rid="B72">Pesaran (2007)</xref> panel unit root test. In the third step, existing long-run relationships between variables in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> are tested using <xref ref-type="bibr" rid="B89">Westerlund (2007)</xref> panel cointegration test, which allows for cross-sectional dependence. Finally, in step four, the long-run relationship among variables in the <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> are estimated using two first-generation panel data estimators, namely FMOLS and DOLS and the second-panel data dynamic SUR estimator.</p>
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</inline-formula> are the number of members, the period of the panel, and the estimated pair-wise correlation between members of panel data of each variable in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref>. The null hypothesis of the mentioned tests is no cross-section dependence and except LM test, which is distributed asymptotically as <inline-formula id="inf14">
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</inline-formula> distribution, the other three tests are asymptotically standard normal. We have to apply the second generation of panel data estimators to estimate the regression models (1) and (4) by rejecting the null hypothesis of no cross-sectional dependence.</p>
<p>We apply the <xref ref-type="bibr" rid="B72">Pesaran (2007)</xref>&#x2019;s cross-sectional augmented Dickey-Fuller (CADF) unit root test to examine the stochastic properties of variables in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref>. Suppose the results of unit root tests indicate that all variables are integrated of order 1 (i.e., I(1)). In that case, the long-run relationship among variables should be tested using second generation of panel co-integration tests. In this paper, we test the null hypothesis of no cointegration using the second generation of the tests, namely <xref ref-type="bibr" rid="B89">Westerlund (2007)</xref>&#x2019;s panel co-integration test which is robust to cross-sectional dependence.</p>
<p>
<xref ref-type="bibr" rid="B89">Westerlund (2007)</xref> developed the following error correction model to test the null hypothesis of no cointegration:<disp-formula id="e9">
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</inline-formula>, which is related to model with intercept and linear trend. To test the null hypothesis of no cointegration, <xref ref-type="bibr" rid="B89">Westerlund (2007)</xref> developed four test statistics under the alternative hypothesis, including <inline-formula id="inf20">
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<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>&#x3b1;</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mtext>&#x2009;</mml:mtext>
<mml:mtext>and</mml:mtext>
<mml:mtext>&#x2009;</mml:mtext>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>&#x3b1;</mml:mi>
<mml:mo>&#xa0;</mml:mo>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>. The alternative hypothesis of two tests <inline-formula id="inf21">
<mml:math id="m30">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#xa0;</mml:mo>
<mml:mtext>and</mml:mtext>
<mml:mo>&#xa0;</mml:mo>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>&#x3b1;</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> (which are called panel statistics) is <inline-formula id="inf22">
<mml:math id="m31">
<mml:mrow>
<mml:msub>
<mml:mi>&#x3c1;</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:mi>&#x3c1;</mml:mi>
<mml:mo>&#x3c;</mml:mo>
<mml:mn>0</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> for all members of the panel and the alternative hypothesis of two tests <inline-formula id="inf23">
<mml:math id="m32">
<mml:mrow>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
<mml:mo>&#xa0;</mml:mo>
<mml:mtext>and</mml:mtext>
<mml:mo>&#xa0;</mml:mo>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>&#x3b1;</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> (which are called mean group statistics) is <inline-formula id="inf24">
<mml:math id="m33">
<mml:mrow>
<mml:msub>
<mml:mi>&#x3c1;</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>&#x3c;</mml:mo>
<mml:mn>0</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> for at least one member of the panel. <xref ref-type="bibr" rid="B89">Westerlund (2007)</xref> offers the bootstrapped <italic>p</italic>-values for all four test statistics, which are robust in the presence of common factors in the time series.</p>
<p>By rejecting the null hypothesis of no cointegration, the long-run relationship among variables in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> is estimated by second-generation estimators of panel data, which can control for cross-sectional dependence. In this paper, we estimate the long-run relationship between CO<sub>2</sub> emission and explanatory variables in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> using DSUR estimator, which was developed by <xref ref-type="bibr" rid="B60">Mark et al. (2005)</xref> by taking into account the cross-sectional dependence.</p>
<p>Consider a two-variable regression model with <inline-formula id="inf25">
<mml:math id="m34">
<mml:mrow>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> as the dependent variable and <inline-formula id="inf26">
<mml:math id="m35">
<mml:mrow>
<mml:msub>
<mml:mi>x</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> as an explanatory variable, where <inline-formula id="inf27">
<mml:math id="m36">
<mml:mrow>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf28">
<mml:math id="m37">
<mml:mrow>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf29">
<mml:math id="m38">
<mml:mrow>
<mml:msub>
<mml:mi>x</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> are I(1) and cointegrated. To estimate the regression model using DSUR approach, we specified the following system regression model with N (i &#x3d; 1,2,&#x2026;,N) equations and applied the DSUR method to estimate it:<disp-formula id="e10">
<mml:math id="m39">
<mml:mrow>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi>&#x3b1;</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3d1;</mml:mi>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3d1;</mml:mi>
<mml:mrow>
<mml:mn>2</mml:mn>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>x</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>l</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>h</mml:mi>
</mml:mrow>
<mml:mi>h</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3c4;</mml:mi>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mi mathvariant="normal">&#x394;</mml:mi>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>h</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mstyle>
<mml:mo>&#x2b;</mml:mo>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>l</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>h</mml:mi>
</mml:mrow>
<mml:mi>h</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3c4;</mml:mi>
<mml:mrow>
<mml:mn>2</mml:mn>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mi mathvariant="normal">&#x394;</mml:mi>
<mml:msub>
<mml:mi>x</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>h</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>&#x3b5;</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
<label>(10)</label>
</disp-formula>where y and x are dependent and explanatory variables, h is a number of lag(s) and lead(s) of dependent and explanatory variables. The lag(s) and lead(s) terms are included in the system regression models to control the endogeneity error terms. <xref ref-type="bibr" rid="B60">Mark et al. (2005)</xref> developed a two-step procedure to estimate the system <xref ref-type="disp-formula" rid="e10">Eq. 10</xref>. In the first step, the <inline-formula id="inf30">
<mml:math id="m40">
<mml:mrow>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is regressed on lags and leads terms i.e. <inline-formula id="inf31">
<mml:math id="m41">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>l</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>h</mml:mi>
</mml:mrow>
<mml:mi>h</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3c4;</mml:mi>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mi mathvariant="normal">&#x394;</mml:mi>
<mml:msub>
<mml:mi>y</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf32">
<mml:math id="m42">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>l</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>h</mml:mi>
</mml:mrow>
<mml:mi>h</mml:mi>
</mml:munderover>
<mml:mrow>
<mml:msub>
<mml:mi>&#x3c4;</mml:mi>
<mml:mrow>
<mml:mn>2</mml:mn>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mi mathvariant="normal">&#x394;</mml:mi>
<mml:msub>
<mml:mi>x</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> using OLS estimator to the error terms&#x2019; endogeneity. In the second step, to allow for cross-sectional dependence among the residuals, the SUR method is run on the OLS residuals of the first step. The covariance matrix of estimated residuals is used as a weight to capture the cross-sectional dependence.</p>
</sec>
</sec>
<sec id="s5">
<title>5 Empirical Results</title>
<p>In <xref ref-type="table" rid="T2">Table 2</xref>, we offer the test statistics of the <xref ref-type="bibr" rid="B24">Breusch and Pagan (1980)</xref>&#x2019;s LM test, <xref ref-type="bibr" rid="B19">Baltagi et al. (2012)</xref>&#x2019;s bias-corrected scaled LM test (BC-LM test), <xref ref-type="bibr" rid="B73">Pesaran (2004)</xref>&#x2019;s scaled LM test (S-LM test), and <xref ref-type="bibr" rid="B73">Pesaran (2004)</xref>&#x2019;s CD test (CD test). As seen, the test statistics indicate the null hypothesis of no cross-sectional dependence is rejected at a 1% significant level except CD tests for <inline-formula id="inf33">
<mml:math id="m43">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>O</mml:mi>
<mml:msub>
<mml:mn>2</mml:mn>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Results of cross-sectional dependence tests.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variables</th>
<th align="center">
<inline-formula id="inf54">
<mml:math id="m64">
<mml:mrow>
<mml:mi>L</mml:mi>
<mml:mi>M</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
<th align="center">
<inline-formula id="inf55">
<mml:math id="m65">
<mml:mrow>
<mml:mi>S</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>L</mml:mi>
<mml:mi>M</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
<th align="center">
<inline-formula id="inf56">
<mml:math id="m66">
<mml:mrow>
<mml:mi>B</mml:mi>
<mml:mi>C</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>L</mml:mi>
<mml:mi>M</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
<th align="center">
<inline-formula id="inf57">
<mml:math id="m67">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>D</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">
<inline-formula id="inf58">
<mml:math id="m68">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>O</mml:mi>
<mml:msub>
<mml:mn>2</mml:mn>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">91.04953&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">13.88468&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">13.8036&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">-0.75683&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf59">
<mml:math id="m69">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">102.2958&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">15.93796&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">15.85688&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">5.90594&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf60">
<mml:math id="m70">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">312.2952&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">54.27843&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">54.19735&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">11.10841&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf61">
<mml:math id="m71">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">314.3915&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">54.66117&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">54.58008&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">11.19689&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf62">
<mml:math id="m72">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">570&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">101.3287&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">101.2476&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">23.87467&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf63">
<mml:math id="m73">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>p</mml:mi>
<mml:mi>o</mml:mi>
<mml:msub>
<mml:mi>s</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">555&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">98.59006&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">98.50673&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">23.55844&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf64">
<mml:math id="m74">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>n</mml:mi>
<mml:mi>e</mml:mi>
<mml:msub>
<mml:mi>g</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">555&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">98.59006&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">98.50673&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">23.55844&#x2a;&#x2a;&#x2a;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: figures indicate the test statistic of cross-sectional dependence tests. <inline-formula id="inf65">
<mml:math id="m75">
<mml:mrow>
<mml:mi>L</mml:mi>
<mml:mi>M</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula id="inf66">
<mml:math id="m76">
<mml:mrow>
<mml:mi>S</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>L</mml:mi>
<mml:mi>M</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula id="inf67">
<mml:math id="m77">
<mml:mrow>
<mml:mi>B</mml:mi>
<mml:mi>C</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>L</mml:mi>
<mml:mi>M</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>, and CD are related to <xref ref-type="bibr" rid="B24">Breusch and Pagan (1980)</xref>&#x2019;s LM test, <xref ref-type="bibr" rid="B73">Pesaran (2004)</xref>&#x2019;s scaled LM test, <xref ref-type="bibr" rid="B19">Baltagi et al. (2012)</xref>&#x2019;s bias-corrected scaled LM test, and <xref ref-type="bibr" rid="B73">Pesaran (2004)</xref>&#x2019;s CD test. &#x2a;&#x2a;&#x2a; represents 1% level of significance.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>
<xref ref-type="bibr" rid="B72">Pesaran (2007)</xref>&#x2019;s CADF panel unit root test is applied to test the null hypothesis of an existing unit root in the data generating process of the variables. In contrast, three variables <inline-formula id="inf51">
<mml:math id="m61">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula id="inf52">
<mml:math id="m62">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>p</mml:mi>
<mml:mi>o</mml:mi>
<mml:msub>
<mml:mi>s</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, and <inline-formula id="inf53">
<mml:math id="m63">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>p</mml:mi>
<mml:mi>o</mml:mi>
<mml:msub>
<mml:mi>s</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> are time series variables. Thus, we apply the conventional ADF unit root test to test the null hypothesis of an existing unit root in the data generating process of the variables. We test the null hypothesis of unit root for two models; model with intercept and model with intercept and linear trend. Each model is considered for two cases; level and first difference of variables. The results of unit root tests are prepared in <xref ref-type="table" rid="T3">Table 3</xref>.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>The results of CADF and ADF unit root tests.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="5" align="left">Panel A: The results of CADF unit root test</th>
</tr>
<tr>
<th align="left"/>
<th colspan="2" align="center">Constant</th>
<th colspan="2" align="center">Trend</th>
</tr>
<tr>
<th align="left"/>
<th align="center">Level</th>
<th align="center">First difference</th>
<th align="center">Level</th>
<th align="center">First difference</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">
<inline-formula id="inf75">
<mml:math id="m85">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;2.894&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;4.365&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.326</td>
<td align="char" char=".">&#x2212;4.456&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf76">
<mml:math id="m86">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;2.894&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;4.365&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.326</td>
<td align="char" char=".">&#x2212;4.456&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf77">
<mml:math id="m87">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>O</mml:mi>
<mml:msub>
<mml:mn>2</mml:mn>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;3.054&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;5.177&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.441</td>
<td align="char" char=".">&#x2212;4.031&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf78">
<mml:math id="m88">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;1.048</td>
<td align="char" char=".">&#x2212;3.749&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;1.403</td>
<td align="char" char=".">&#x2212;2.129</td>
</tr>
<tr>
<td colspan="5" align="left">Critical values of CADF unit root test</td>
</tr>
<tr>
<td align="left">&#x2003;10%</td>
<td align="char" char=".">&#x2212;2.210</td>
<td align="char" char=".">&#x2212;2.730</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;5%</td>
<td align="char" char=".">&#x2212;2.330</td>
<td align="char" char=".">&#x2212;2.860</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;1%</td>
<td align="char" char=".">&#x2212;2.570</td>
<td align="char" char=".">&#x2212;3.100</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td colspan="5" align="left">
<bold>Panel B: The results of the univariate ADF unit root test</bold>
</td>
</tr>
<tr>
<td align="left"/>
<td align="center">
<bold>Level</bold>
</td>
<td align="center">
<bold>first difference</bold>
</td>
<td align="center">
<bold>Level</bold>
</td>
<td align="center">
<bold>first difference</bold>
</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf79">
<mml:math id="m89">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;1.157</td>
<td align="char" char=".">&#x2212;6.049&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.184</td>
<td align="char" char=".">&#x2212;6.006&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf80">
<mml:math id="m90">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>p</mml:mi>
<mml:mi>o</mml:mi>
<mml:msub>
<mml:mi>s</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.516</td>
<td align="char" char=".">&#x2212;4.813&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.275</td>
<td align="char" char=".">&#x2212;4.809&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf81">
<mml:math id="m91">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>n</mml:mi>
<mml:mi>e</mml:mi>
<mml:msub>
<mml:mi>g</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.612</td>
<td align="char" char=".">&#x2212;6.401&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.642</td>
<td align="char" char=".">&#x2212;4.712&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="5" align="left">Critical values of ADF unit root test</td>
</tr>
<tr>
<td align="left">&#x2003;10%</td>
<td align="char" char=".">&#x2212;2.610</td>
<td align="char" char=".">&#x2212;3.200</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;5%</td>
<td align="char" char=".">&#x2212;2.943</td>
<td align="char" char=".">&#x2212;3.537</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;1%</td>
<td align="char" char=".">&#x2212;3.621</td>
<td align="char" char=".">&#x2212;4.227</td>
<td align="left"/>
<td align="left"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note:&#x2a;&#x2a;&#x2a; represents 1% level of significance.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The results of the CADF unit root test indicate three variables <inline-formula id="inf68">
<mml:math id="m78">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>O</mml:mi>
<mml:msub>
<mml:mn>2</mml:mn>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula id="inf69">
<mml:math id="m79">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, and <inline-formula id="inf70">
<mml:math id="m80">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> are stationary when only an intercept is included in the unit root test and when a linear trend is included in the unit root test, the null hypothesis of unit root is not rejected. In contrast, when the null hypothesis of unit root is tested for the first differenced variables, in both models with constant and constant and linear trends, the null hypothesis of unit root is rejected at 1% significant level. The CADF unit root test results for EU indicate that the variable is I(1) for the model with intercept.</p>
<p>The results of the univariate ADF unit root test in panel B indicate that all three variables <italic>oilP</italic>, <italic>oilP_pos</italic>, and <italic>oilP_neg</italic> are I(1) according to both models with only intercept and intercept and linear trend. With a little condescension, we conclude that all panel data variables and time series variables in the study are I(1). Thus, in the next step, we test the existing long-run relationship between variables in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> using <xref ref-type="bibr" rid="B89">Westerlund (2007)</xref>&#x2019; panel cointegration test.</p>
<p>The results of the null hypothesis test for the lack of cointegration between the variables in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> using the <xref ref-type="bibr" rid="B89">Westerlund (2007)</xref> co-integration panel test in panels A and B are presented in <xref ref-type="table" rid="T4">Table 4</xref> respectively. We offer the test statistics and related robust <italic>p</italic>-values, which are computed using bootstrapping process, for all four test statistics, including <inline-formula id="inf71">
<mml:math id="m81">
<mml:mrow>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula id="inf72">
<mml:math id="m82">
<mml:mrow>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>&#x3b1;</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula id="inf73">
<mml:math id="m83">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, and <inline-formula id="inf74">
<mml:math id="m84">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>&#x3b1;</mml:mi>
<mml:mo>&#xa0;</mml:mo>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>. All tests indicate the null hypothesis of no cointegration among variables in <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> are rejected at 1% statistically significant level. Next, we apply two first panel data estimators including panel dynamic OLS (panel DOLS) and panel fully modified OLS (panel FMOLS) and second-generation panel data estimator of panel DSUR to estimate the long-run relationship among variables in the <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref>.</p>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>The results of <xref ref-type="bibr" rid="B89">Westerlund (2007)</xref> panel cointegration test.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="2" align="left">Panel A: <xref ref-type="disp-formula" rid="e1">Eq. 1</xref>: <inline-formula id="inf84">
<mml:math id="m94">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mi>O</mml:mi>
<mml:msub>
<mml:mn>2</mml:mn>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:mi>f</mml:mi>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
<mml:mo>,</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mo>)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula>
</th>
</tr>
<tr>
<th align="left">Statistics</th>
<th align="center">Test statistics</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">
<inline-formula id="inf85">
<mml:math id="m95">
<mml:mrow>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;4.245&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf86">
<mml:math id="m96">
<mml:mrow>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>&#x3b1;</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;21.069&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf87">
<mml:math id="m97">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;10.710&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf88">
<mml:math id="m98">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>&#x3b1;</mml:mi>
<mml:mo>&#xa0;</mml:mo>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;22.173&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td colspan="2" align="left">
<xref ref-type="disp-formula" rid="e2">Eq. 2</xref>: <inline-formula id="inf89">
<mml:math id="m99">
<mml:mrow>
<mml:mi mathvariant="bold-italic">C</mml:mi>
<mml:mi mathvariant="bold-italic">O</mml:mi>
<mml:msub>
<mml:mn>2</mml:mn>
<mml:mrow>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:mi mathvariant="bold-italic">f</mml:mi>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
<mml:mi mathvariant="bold-italic">G</mml:mi>
<mml:mi mathvariant="bold-italic">D</mml:mi>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:mrow>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="bold-italic">G</mml:mi>
<mml:mi mathvariant="bold-italic">D</mml:mi>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:msubsup>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:mrow>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="bold-italic">E</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">U</mml:mi>
<mml:mrow>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="bold-italic">o</mml:mi>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">l</mml:mi>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi mathvariant="bold-italic">p</mml:mi>
<mml:mi mathvariant="bold-italic">o</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">s</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="bold-italic">o</mml:mi>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">l</mml:mi>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi mathvariant="bold-italic">n</mml:mi>
<mml:mi mathvariant="bold-italic">e</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">g</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mo>)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
</tr>
<tr>
<td align="left">
<bold>Statistics</bold>
</td>
<td align="center">
<bold>Test statistics</bold>
</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf90">
<mml:math id="m100">
<mml:mrow>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;3.844&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf91">
<mml:math id="m101">
<mml:mrow>
<mml:msub>
<mml:mi>G</mml:mi>
<mml:mi>&#x3b1;</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;18.22&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf92">
<mml:math id="m102">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;10.082&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">
<inline-formula id="inf93">
<mml:math id="m103">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>&#x3b1;</mml:mi>
<mml:mo>&#xa0;</mml:mo>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;20.492&#x2a;&#x2a;&#x2a;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: &#x2a;&#x2a;&#x2a; represents 1% level of significance.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>We present the estimation results of <xref ref-type="disp-formula" rid="e1">Eq. 1</xref> by panel DOLS and FMOLS in panels A and B of <xref ref-type="table" rid="T5">Table 5</xref>, respectively. The results of the panel DOLS estimator indicate 1) oil price has a statistically significant negative effect (at 5%) on CO<sub>2</sub> emission in the GCC countries. A 10 per cent increase in the oil price will decrease CO<sub>2</sub> emissions by about 0.06%. 2) The coefficients of <inline-formula id="inf82">
<mml:math id="m92">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf83">
<mml:math id="m93">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> are 0.467 and &#x2212;0.022, respectively and both of them are statistically significant at 1%. According to the results, the environmental Kuznets curve hypothesis is not rejected in the GCC countries. 3) The coefficient of EU is positive and statistically significant at 1%. The result indicates that if energy use increases 10%, the CO<sub>2</sub> emission will decrease by 8.8%.</p>
<table-wrap id="T5" position="float">
<label>TABLE 5</label>
<caption>
<p>Estimation results of <xref ref-type="disp-formula" rid="e1">Eq. 1</xref> by panel DOLS and panel FMOLS.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="4" align="left">Panel A: Results of panel DOLS</th>
</tr>
<tr>
<th align="left">Variable</th>
<th align="center">Coefficient</th>
<th align="center">t-Statistic</th>
<th align="left"/>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">
<inline-formula id="inf96">
<mml:math id="m106">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.467&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">7.014</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf97">
<mml:math id="m107">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.022&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;7.003</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf98">
<mml:math id="m108">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.822&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">131.809</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf99">
<mml:math id="m109">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.006&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;1.980</td>
<td align="left"/>
</tr>
<tr>
<td colspan="4" align="left">
<bold>Panel B: Results of panel FMOLS</bold>
</td>
</tr>
<tr>
<td align="left">
<bold>Variable</bold>
</td>
<td align="center">
<bold>Coefficient</bold>
</td>
<td align="center">
<bold>
<italic>t</italic>-Statistic</bold>
</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf100">
<mml:math id="m110">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.890</td>
<td align="char" char=".">&#x2212;1.145</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf101">
<mml:math id="m111">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.050</td>
<td align="char" char=".">1.401</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf102">
<mml:math id="m112">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.745&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">10.769</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf103">
<mml:math id="m113">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.087&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.164</td>
<td align="left"/>
</tr>
<tr>
<td colspan="4" align="left">Specification test</td>
</tr>
<tr>
<td align="left">R-squared</td>
<td align="char" char=".">0.936</td>
<td align="center">Adjusted R-squared</td>
<td align="char" char=".">0.933</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note:&#x2a;&#x2a; and &#x2a;&#x2a;&#x2a; represent 5% and 1% levels of significance.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The results of the panel FMOLS estimator indicate 1) oil price has a statistically significant negative effect (at 5%) on CO<sub>2</sub> emission in the GCC countries. A 10 per cent increase in the oil price will decrease CO<sub>2</sub> emission by about 0.87% (greater than estimated by the panel DOLS estimator). 2) The coefficients of <inline-formula id="inf94">
<mml:math id="m104">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf95">
<mml:math id="m105">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> are statistically insignificant at conventional cut-off points. In contrast with panel DOLS estimator results, according to panel FMOLS estimator results, the GCC countries&#x2019; environmental Kuznets curve does not exist. 3) The coefficient of EU is positive and statistically significant at 1%. The result indicates that if energy use increases 10%, the CO<sub>2</sub> emission will decrease by 7.45%.</p>
<p>We present <xref ref-type="disp-formula" rid="e4">Eq. 4</xref> estimation results by panel DOLS and panel FMOLS in panels A and B in <xref ref-type="table" rid="T6">Table 6</xref>. The estimated coefficient of positive oil price component by panel DOLS and panel FMOLS is negative, statistically significant at 5%. The results indicate that positive shocks to oil prices will decrease the CO<sub>2</sub> emission in the GCC countries. In contrast, the estimated coefficient of the negative oil price component by panel DOLS and FMOLS estimators is statistically insignificant. Thus, only positive shocks to oil prices have a statistically significant effect on CO<sub>2</sub> emission and help reduce air pollution. In contrast, negative shocks have neutral effects on CO<sub>2</sub> emission.</p>
<table-wrap id="T6" position="float">
<label>TABLE 6</label>
<caption>
<p>Estimation results of <xref ref-type="disp-formula" rid="e1">Eq. 1</xref> by panel DOLS and panel FMOLS.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="4" align="left">Panel A: Results of panel DOLS</th>
</tr>
<tr>
<th align="left">Variable</th>
<th align="center">Coefficient</th>
<th align="center">
<italic>t</italic>-Statistic</th>
<th align="left"/>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">
<inline-formula id="inf104">
<mml:math id="m114">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.920&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">4.967</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf105">
<mml:math id="m115">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.039&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;4.583</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf106">
<mml:math id="m116">
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.798&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">43.376</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf107">
<mml:math id="m117">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>p</mml:mi>
<mml:mi>o</mml:mi>
<mml:msub>
<mml:mi>s</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.029&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.164</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf108">
<mml:math id="m118">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>n</mml:mi>
<mml:mi>e</mml:mi>
<mml:msub>
<mml:mi>g</mml:mi>
<mml:mi>t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">0.025</td>
<td align="char" char=".">1.571</td>
<td align="left"/>
</tr>
<tr>
<td colspan="4" align="left">Specification test</td>
</tr>
<tr>
<td align="left">R-squared</td>
<td align="char" char=".">0.958</td>
<td align="center">Adjusted R-squared</td>
<td align="char" char=".">0.945</td>
</tr>
<tr>
<td colspan="4" align="left">
<bold>Panel B: Results of panel FMOLS</bold>
</td>
</tr>
<tr>
<td align="left">
<bold>Variable</bold>
</td>
<td align="center">
<bold>Coefficient</bold>
</td>
<td align="center">
<bold>
<italic>t</italic>-Statistic</bold>
</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf109">
<mml:math id="m119">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="char" char=".">&#x2212;0.334</td>
<td align="char" char=".">&#x2212;0.851</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf110">
<mml:math id="m120">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
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<td align="char" char=".">1.150</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
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<td align="char" char=".">0.854&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">22.785</td>
<td align="left"/>
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<tr>
<td align="left">
<inline-formula id="inf112">
<mml:math id="m122">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
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<td align="char" char=".">&#x2212;0.045&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;2.105</td>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf113">
<mml:math id="m123">
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi>n</mml:mi>
<mml:mi>e</mml:mi>
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<mml:mi>g</mml:mi>
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</mml:math>
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</td>
<td align="char" char=".">&#x2212;0.007</td>
<td align="char" char=".">&#x2212;0.238</td>
<td align="left"/>
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<tr>
<td colspan="4" align="left">Specification test</td>
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<tr>
<td align="left">R-squared</td>
<td align="char" char=".">0.940</td>
<td align="center">Adjusted R-squared</td>
<td align="char" char=".">0.937</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note:&#x2a;&#x2a; and &#x2a;&#x2a;&#x2a; represent 5% and 1% level of significance.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>One of the main shortcomings of panel DOLS and panel FMOLS estimators is that they cannot overcome the problem related to cross-section dependence. Hence in the final step, we re-estimate the <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> using panel DSUR. The results are prepared in <xref ref-type="table" rid="T7">Table 7</xref>.</p>
<table-wrap id="T7" position="float">
<label>TABLE 7</label>
<caption>
<p>Estimation results of <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> by panel DSUR estimator.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="11" align="left">Panel A: The estimation results of <xref ref-type="disp-formula" rid="e1">Eq. 1</xref>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="11" align="left">
<bold>A1: the results of the panel DSUR estimator</bold>
</td>
</tr>
<tr>
<td align="left">
<bold>Explanatory variables</bold>
</td>
<td align="center">
<bold>coefficient</bold>
</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf116">
<mml:math id="m126">
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<td align="char" char=".">2.401</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">2.882&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
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<tr>
<td align="left">
<inline-formula id="inf117">
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<td align="char" char=".">&#x2212;0.101</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">&#x2212;2.590&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
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<td align="left">
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</td>
<td align="char" char=".">0.648</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">9.257&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
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<tr>
<td align="left">
<inline-formula id="inf119">
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<mml:mrow>
<mml:mi>o</mml:mi>
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<mml:mi>P</mml:mi>
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<td align="char" char=".">&#x2212;0.104</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">&#x2212;3.250&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td colspan="11" align="left">
<bold>A2: The results of DSUR for Single Equation</bold>
</td>
</tr>
<tr>
<td align="left">
<bold>Countries</bold>
</td>
<td align="center">
<inline-formula id="inf120">
<mml:math id="m130">
<mml:mrow>
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<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
</td>
<td align="center">
<inline-formula id="inf121">
<mml:math id="m131">
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<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
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<td align="center">
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<bold>
<italic>t</italic>-statistics</bold>
</td>
<td align="center">
<inline-formula id="inf123">
<mml:math id="m133">
<mml:mrow>
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<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Bahrain</td>
<td align="char" char=".">&#x2212;10.914</td>
<td align="char" char=".">&#x2212;4.122&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">0.532</td>
<td align="char" char=".">3.941&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.340</td>
<td align="char" char=".">&#x2212;2.297&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.283</td>
<td align="char" char=".">&#x2212;3.216&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Kuwait</td>
<td align="char" char=".">4.157</td>
<td align="char" char=".">2.164&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.187</td>
<td align="char" char=".">&#x2212;2.078&#x2a;&#x2a;</td>
<td align="char" char=".">0.768</td>
<td align="char" char=".">5.606&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">0.075</td>
<td align="char" char=".">0.833</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Oman</td>
<td align="char" char=".">&#x2212;1.003</td>
<td align="char" char=".">&#x2212;1.038</td>
<td align="char" char=".">0.083</td>
<td align="char" char=".">1.694&#x2a;</td>
<td align="char" char=".">0.133</td>
<td align="char" char=".">1.343</td>
<td align="char" char=".">&#x2212;0.316</td>
<td align="char" char=".">&#x2212;3.718&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Qatar</td>
<td align="char" char=".">2.191</td>
<td align="char" char=".">1.379</td>
<td align="char" char=".">&#x2212;0.077</td>
<td align="char" char=".">&#x2212;0.963</td>
<td align="char" char=".">1.192</td>
<td align="char" char=".">9.933&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.375</td>
<td align="char" char=".">&#x2212;2.358&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Saudi Arabia</td>
<td align="char" char=".">13.402</td>
<td align="char" char=".">3.908&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.608</td>
<td align="char" char=".">&#x2212;3.663&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">1.957</td>
<td align="char" char=".">3.532&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.481</td>
<td align="char" char=".">&#x2212;3.064&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">United Arab Emirates</td>
<td align="char" char=".">13.525</td>
<td align="char" char=".">2.201&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.587</td>
<td align="char" char=".">&#x2212;2.182&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.193</td>
<td align="char" char=".">&#x2212;0.937</td>
<td align="char" char=".">&#x2212;0.252</td>
<td align="char" char=".">&#x2212;6.000&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td colspan="11" align="left">
<bold>Panel B: The estimation results of <xref ref-type="disp-formula" rid="e1">Eq. 1</xref>
</bold>
</td>
</tr>
<tr>
<td colspan="11" align="left">
<bold>B1: the results of the panel DSUR estimator</bold>
</td>
</tr>
<tr>
<td align="left">
<bold>Explanatory variables</bold>
</td>
<td align="center">
<bold>Coefficient</bold>
</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
<inline-formula id="inf124">
<mml:math id="m134">
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<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
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<mml:mi>i</mml:mi>
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</td>
<td align="char" char=".">2.416</td>
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<td align="left"/>
<td align="left"/>
<td align="char" char=".">2.800&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">
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</td>
<td align="char" char=".">&#x2212;0.109</td>
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<td align="left"/>
<td align="left"/>
<td align="char" char=".">&#x2212;2.659&#x2a;&#x2a;&#x2a;</td>
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<td align="left"/>
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<tr>
<td align="left">
<inline-formula id="inf126">
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</mml:msub>
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</inline-formula>
</td>
<td align="char" char=".">0.661</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">8.813&#x2a;&#x2a;&#x2a;</td>
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</td>
<td align="char" char=".">&#x2212;0.198</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="char" char=".">&#x2212;4.400&#x2a;&#x2a;&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
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<tr>
<td align="left">
<inline-formula id="inf128">
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<mml:mi>o</mml:mi>
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<td align="char" char=".">0.133</td>
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<td align="left"/>
<td align="left"/>
<td align="char" char=".">1.511</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td colspan="11" align="left">
<bold>B2: The results of DSUR for Single Equation</bold>
</td>
</tr>
<tr>
<td align="left">
<bold>Countries</bold>
</td>
<td align="center">
<inline-formula id="inf129">
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<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
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<td align="center">
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<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
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<td align="center">
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<bold>
<italic>t</italic>-statistics</bold>
</td>
<td align="center">
<inline-formula id="inf132">
<mml:math id="m142">
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<mml:mi mathvariant="bold-italic">o</mml:mi>
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<mml:mi mathvariant="bold-italic">l</mml:mi>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi mathvariant="bold-italic">p</mml:mi>
<mml:mi mathvariant="bold-italic">o</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">s</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
</td>
<td align="center">
<inline-formula id="inf133">
<mml:math id="m143">
<mml:mrow>
<mml:mi mathvariant="bold-italic">o</mml:mi>
<mml:mi mathvariant="bold-italic">i</mml:mi>
<mml:mi mathvariant="bold-italic">l</mml:mi>
<mml:mi mathvariant="bold-italic">P</mml:mi>
<mml:mo>_</mml:mo>
<mml:mi mathvariant="bold-italic">n</mml:mi>
<mml:mi mathvariant="bold-italic">e</mml:mi>
<mml:msub>
<mml:mi mathvariant="bold-italic">g</mml:mi>
<mml:mi mathvariant="bold-italic">t</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td align="center">
<bold>
<italic>t</italic>-statistics</bold>
</td>
</tr>
<tr>
<td align="left">Bahrain</td>
<td align="char" char=".">&#x2212;10.702</td>
<td align="char" char=".">&#x2212;4.633&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">0.517</td>
<td align="char" char=".">4.419&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.379</td>
<td align="char" char=".">&#x2212;2.746&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.407</td>
<td align="char" char=".">&#x2212;4.845&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">0.097</td>
<td align="char" char=".">0.581</td>
</tr>
<tr>
<td align="left">Kuwait</td>
<td align="char" char=".">2.023</td>
<td align="char" char=".">0.607</td>
<td align="char" char=".">&#x2212;0.098</td>
<td align="char" char=".">&#x2212;0.628</td>
<td align="char" char=".">1.057</td>
<td align="char" char=".">3.915&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">0.006</td>
<td align="char" char=".">0.030</td>
<td align="char" char=".">0.811</td>
<td align="char" char=".">1.616</td>
</tr>
<tr>
<td align="left">Oman</td>
<td align="char" char=".">&#x2212;0.370</td>
<td align="char" char=".">&#x2212;0.491</td>
<td align="char" char=".">0.054</td>
<td align="char" char=".">1.421</td>
<td align="char" char=".">0.039</td>
<td align="char" char=".">0.494</td>
<td align="char" char=".">&#x2212;0.164</td>
<td align="char" char=".">&#x2212;2.158&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.782</td>
<td align="char" char=".">&#x2212;6.410&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">Qatar</td>
<td align="char" char=".">2.188</td>
<td align="char" char=".">1.727&#x2a;</td>
<td align="char" char=".">&#x2212;0.067</td>
<td align="char" char=".">&#x2212;1.063</td>
<td align="char" char=".">1.039</td>
<td align="char" char=".">7.754&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.879</td>
<td align="char" char=".">&#x2212;5.140&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">0.065</td>
<td align="char" char=".">0.305</td>
</tr>
<tr>
<td align="left">Saudi Arabia</td>
<td align="char" char=".">19.516</td>
<td align="char" char=".">6.867</td>
<td align="char" char=".">&#x2212;0.919</td>
<td align="char" char=".">&#x2212;6.659</td>
<td align="char" char=".">3.625</td>
<td align="char" char=".">5.800</td>
<td align="char" char=".">&#x2212;0.452</td>
<td align="char" char=".">&#x2212;2.568&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.582</td>
<td align="char" char=".">&#x2212;2.541&#x2a;&#x2a;&#x2a;</td>
</tr>
<tr>
<td align="left">United Arab Emirates</td>
<td align="char" char=".">&#x2212;16.721</td>
<td align="char" char=".">&#x2212;1.697</td>
<td align="char" char=".">0.744</td>
<td align="char" char=".">1.722</td>
<td align="char" char=".">0.700</td>
<td align="char" char=".">2.128</td>
<td align="char" char=".">&#x2212;0.226</td>
<td align="char" char=".">&#x2212;3.831&#x2a;&#x2a;&#x2a;</td>
<td align="char" char=".">&#x2212;0.106</td>
<td align="char" char=".">&#x2212;0.586</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note:&#x2a;, &#x2a;&#x2a; and &#x2a;&#x2a;&#x2a; represent 10%, 5% and 1% level of significance.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>We present the estimation results of <xref ref-type="disp-formula" rid="e1">Eqs 1</xref>, <xref ref-type="disp-formula" rid="e4">4</xref> by panel DSUR estimator in panels A and B, respectively. Panel A1 reports the panel DSUR estimator and panel A2 reports a single country DSUR estimator of <xref ref-type="disp-formula" rid="e1">Eq. 1</xref>. The results of the panel DSUR estimator indicate 1) oil price has a statistically significant negative effect (at 1%) on CO<sub>2</sub> emission in the GCC countries. Its coefficient equals &#x2212;0.104 (greater than panel DOLS and FMOLS) and indicates a 10 per cent increase in the oil price will decrease CO<sub>2</sub> emission by about 1.04%. 2) The coefficients of <inline-formula id="inf114">
<mml:math id="m124">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf115">
<mml:math id="m125">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> are 2.401 and &#x2212;0.101, respectively and both of them are statistically significant at 5%. According to the results, the environmental Kuznets curve exists in the GCC countries. 3) The coefficient of the EU is positive and statistically significant at 1%. The result indicates that if energy use increases 10%, the CO<sub>2</sub> emission will decrease by 6.48%. <xref ref-type="table" rid="T7">Table 7</xref>
</p>
<p>The results of a single DSUR estimator for each country indicate 1) except Kuwait. For other GCC countries, the oil prices negatively affect the CO<sub>2</sub> emission, and the most negative effect is related to Saudi Arabia (equals -0.481). For Kuwait, the null hypothesis of the neutral effect of oil price on CO<sub>2</sub> emission is not rejected at conventional cut-off points. 2) The sign and statistically significance of <inline-formula id="inf134">
<mml:math id="m144">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf135">
<mml:math id="m145">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> indicate the environmental Kuznets curve hypothesis is not rejected in Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates contrast, the hypothesis is rejected in Bahrain and Oman. 3) The EU has a statistically positive significant effect in Kuwait, Qatar, and Saudi Arabia.</p>
<p>The estimation results of <xref ref-type="disp-formula" rid="e4">Eq. 4</xref> by panel DSUR estimator in panel B1 indicate 1) positive shocks of oil price have a statistically significant negative effect (at 1%) on CO<sub>2</sub> emission in the GCC countries. Ten points of positive shock of oil prices will decrease CO<sub>2</sub> emission by about 1.98%. In contrast, the negative shocks of oil prices do not have statistically significant effects on CO<sub>2</sub> emission. The results are in line with our previous results using panel FMOLS and panel DOLS estimators. 2) The sign and statistical significance of other explanatory variables are the same as our results for <xref ref-type="disp-formula" rid="e1">Eq. 1</xref>.</p>
<p>The results of a single DSUR estimator for each country indicate 1) except Kuwait. For other GCC countries, the positive shocks to oil prices have a statistically significant negative effect on the CO<sub>2</sub> emission and the most negative effect on Qatar and Saudi Arabia. The negative shocks of oil prices have statistically significant effects on the CO<sub>2</sub> emission of Oman and Saudi Arabia. 2) The sign and statistically significant of <inline-formula id="inf136">
<mml:math id="m146">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula id="inf137">
<mml:math id="m147">
<mml:mrow>
<mml:mi>G</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> indicate environmental Kuznets curve hypothesis is not rejected in Qatar and Saudi Arabia. 3) The EU has a statistically positive significant effect on Kuwait, Qatar, Saudi Arabia, and the United Arab Emirates.</p>
<p>For robustness checking, Brent crude oil price substitutes the WTI oil price in our estimations. We encounter that the results are consistent and robust with the main findings.</p>
</sec>
<sec id="s6">
<title>6 Discussion</title>
<p>The primary goal of this study is to see how positive and negative oil price shocks affect environmental degradation. The findings suggest that the GCC countries under investigation are cross-sectionally dependent. According to long-run DSUR estimates, positive oil price shocks have a statistically significant negative influence on CO<sub>2</sub> emissions. Our findings are in line with the previous work of <xref ref-type="bibr" rid="B59">Malik et al. (2020)</xref> for Pakistan, <xref ref-type="bibr" rid="B79">Shahbaz et al. (2017)</xref> for Australia, <xref ref-type="bibr" rid="B83">Umar et al. (2020)</xref> for African countries, <xref ref-type="bibr" rid="B82">Ullah et al. (2020)</xref> for the top ten carbon emitters, and <xref ref-type="bibr" rid="B2">Abumunshar et al. (2020)</xref> for Turkey. This result is in line with <xref ref-type="bibr" rid="B22">Bilgili et al. (2020)</xref> for United States and China, which also found that the increase in oil prices in the US is a negative effect on CO<sub>2</sub> emissions. These findings support the findings of <xref ref-type="bibr" rid="B42">Haque (2020)</xref>, who discovered that an increase in oil prices reduced energy consumption by 0.22 per cent while higher energy consumption increases CO<sub>2</sub> emissions in the GCC. This result is also consistent with <xref ref-type="bibr" rid="B59">Malik et al. (2020)</xref>, who found that in the long-run relationship between oil price and carbon emission, an increase in the oil price (positive shock in the partial sum of oil price) reduces carbon emission while a decrease in the oil price (negative shocks in the partial sum of oil price) increases carbon emission.</p>
<p>Oil price shocks, on the other hand, have had a negative impact on CO<sub>2</sub> emissions in Oman, Bahrain, Saudi Arabia, Qatar, and the United Arab Emirates. Qatar has the largest detrimental impact, followed by Saudi Arabia. Oil price negative shocks have statistically significant effects on CO<sub>2</sub> emissions in Oman and Saudi Arabia, but not in other nations. These findings confirm the work of <xref ref-type="bibr" rid="B9">Aljadani et al. (2021)</xref>, who find that there is a long-term negative and significant association between oil rent (OILRENT) and CO<sub>2</sub> emissions, and a rise of 1% in oil rent (OILRENT) will result in a 0.25 per cent reduction in environmental deterioration in Saudi Arabia. The outcome of this study is similar to (<xref ref-type="bibr" rid="B86">Wang and Li, 2016</xref>; <xref ref-type="bibr" rid="B58">Maji et al., 2017</xref>; <xref ref-type="bibr" rid="B3">Agbanike et al., 2019</xref>; <xref ref-type="bibr" rid="B32">Constantinos et al., 2019</xref>), which supports the significant negative impact of oil price on CO<sub>2</sub> emissions. To be more precise, the energy prices exert a negative effect on CO<sub>2</sub> emissions in line with some previous empirical literature (<xref ref-type="bibr" rid="B53">Li et al., 2020</xref>). The results are in line with results using panel FMOLS and panel DOLS estimators showing that oil price has a significant negative effect on CO<sub>2</sub> emissions.</p>
<p>In the meanwhile, the EKC theory is not rejected in Kuwait, Oman, Qatar, Saudi Arabia, or the UAE; nevertheless, it is rejected in Bahrain and Oman. This means that an increase in oil prices will decrease the carbon emissions in the selected countries. However, this research found that both positive and negative oil price shocks have little effect on pollution. The Fully Modified OLS was used to achieve this outcome. The DSUR approach was also used to elucidate the influence of oil price shocks and other explanatory variables on CO<sub>2</sub> emissions in GCC nations for the robustness assessment. The results of the long-run estimation show that positive oil price shocks have a negative but insignificant effect on pollution. This conclusion is consistent with <xref ref-type="bibr" rid="B29">Chang et al. (2009)</xref> and Sadorsky&#x2019;s reasoning (<xref ref-type="bibr" rid="B76">2009a</xref> and <xref ref-type="bibr" rid="B75">2009b</xref>). They found that the impact of oil prices on environmental deterioration is inversely proportional to the country&#x2019;s economic development rate. They also pointed out that nations with greater economic growth transition to clean energy sources (renewable energy) faster than countries with lower economic growth to reduce pollution caused by oil price shocks.</p>
<p>The effect of negative oil price shocks on CO<sub>2</sub> emissions in GCC nations, on the other hand, demonstrates that negative oil price shocks have statistically significant effects on CO<sub>2</sub> emissions. This means that a decline in oil prices has a greater impact on pollution than an increase in oil prices. This is in line with <xref ref-type="bibr" rid="B61">Marques and Fuinhas&#x2019;s (2011)</xref> findings, who argued that prices of fossil-based fuels are not significant tools for mitigating carbon emissions. Similar findings reported by <xref ref-type="bibr" rid="B80">Sun et al. (2019)</xref> reveal that energy price does not matter in predicting changes in CO<sub>2</sub> emission in China. They suggested that oil prices are not suitable tools to encourage the consumption of renewable energy sources.</p>
<p>The short-run results of the current analysis revealed that both positive and negative oil price shocks have no statistically significant influence on pollution. In other words, the effect of total energy consumption is statistically significant and positive in all of the estimated models. This is consistent with prior research that found that energy usage has a favourable impact on carbon emissions in GCC countries (<xref ref-type="bibr" rid="B77">Salahuddin and Gow, 2014</xref>; <xref ref-type="bibr" rid="B78">Salahuddin et al., 2015</xref>; <xref ref-type="bibr" rid="B5">Al-mulali and Che Sab, 2018</xref>; <xref ref-type="bibr" rid="B7">Al-Saidi and Elagib, 2018</xref>).</p>
<p>Moreover, the statistically significant positive and negative coefficients of GDP and square of GDP, respectively, support the EKC hypothesis in the selected GCC countries. This finding is in line with the result of several studies such as <xref ref-type="bibr" rid="B39">Hamdi and Sbia (2013)</xref> for the panel of GCC; <xref ref-type="bibr" rid="B48">Jaunky (2011)</xref> for Bahrain, Oman, and UAE; <xref ref-type="bibr" rid="B16">Arouri et al. (2012)</xref> for Egypt, Lebanon, Bahrain, Saudi Arabia, and Oman; and Ozcan (2013) for UAE, Egypt, and Lebanon.</p>
<p>The GCC countries have observed the benefits of renewables as a cost-effective and reliable power source. This may be attributed to initiatives and favourable policies adopted by these countries and programs towards developing renewable energy sources in these countries. All GCC countries have also targeted that 10% of the power production come from renewable energy sources by 2020 and are rapidly moving towards realizing this target.</p>
<p>The key to renewable energy development in the GCC region is solar power, as it is the single most abundant renewable energy source available. The region&#x2019;s topography gives it immense solar energy potential throughout the year. It benefits the space to develop large solar power plants&#x2014;almost 85&#x2013;90% of the money spent on renewable energy. For example, Saudi Arabia has announced plans to invest more than $ 100 billion to generate 41&#xa0;gigawatts of electricity using solar power. Dubai has also unveiled plans to invest about $ 4 billion to generate 1&#xa0;gigawatt of electricity using solar energy. The six Gulf countries have begun construction of solar power plants with investments of over $ 155 billion to create more than 84&#xa0;gigawatts of power and are scheduled to be completed by 2017, Other examples of these policies include renewable energy initiatives, such as Saudi Arabia&#x2019;s six greenfield economic cities (combined with efforts to elevate cities like Mecca to Smart City status). Lusail&#x2019;s Smart and Sustainable City, Pearl-Qatar Island, and Energy City Qatar are three projects in Qatar. Two projects in the United Arab Emirates (Masdar City in Abu Dhabi and Smart City Dubai).</p>
</sec>
<sec id="s7">
<title>7 Conclusion and Policy Implications</title>
<p>Oil price shocks have become a major decisive factor in environmental degradation, thus calling policymakers and researchers to investigate its causes. In this study, we explored the short- and long-run effects of oil price shocks on the CO<sub>2</sub> emissions for a panel of six GCC countries from 1996 to 2016. Although various studies have been conducted on this topic for countries in Western Europe, America, Asia, and Africa, the studies that have been undertaken on the GCC countries are very limited. Therefore, the present study&#x2019;s findings can positively impact both the literature and future decisions of policymakers.</p>
<p>The long-run interactions between oil price shocks and CO<sub>2</sub> emissions were investigated using the DSUR technique in our study. In the long run, the estimates revealed no significant relationship between negative oil price shocks and CO<sub>2</sub> emissions. Nonetheless, a strong negative relationship was discovered between positive oil price shocks and CO<sub>2</sub> emissions. Also, a single DSUR estimate shows that positive oil price shocks have had a negative impact on CO<sub>2</sub> emissions in Oman, Bahrain, Saudi Arabia, Qatar, and the United Arab Emirates. At the same time, the findings revealed that Qatar had the largest detrimental impact, followed by Saudi Arabia.</p>
<p>Meanwhile, the negative shocks of oil prices have statistically significant effects on the CO<sub>2</sub> emission of Oman and Saudi Arabia, and for other countries, it does not have a significant effect. Moreover, the results also support the existence of the EKC in Kuwait, Oman, Qatar, Saudi Arabia, and the UAE. In contrast, the hypothesis is rejected in Bahrain and Oman.</p>
<p>Positive oil price shocks have no significant effect on CO<sub>2</sub> emissions, but negative shocks have a considerable impact on CO<sub>2</sub> emissions in the GCC countries. This is understandable, given that the UAE liberalized energy pricing following the negative impact of oil prices in 2014, resulting in lower domestic consumption. Saudi Arabia and Kuwait, which have been reclaimed, have also increased domestic energy prices by roughly 50%, but they still retain support. Overall, such a reduction, combined with the start-up of solar power plants via the big projects outlined above, reduces dependency on fossil fuels for energy generation. However, there is a positive effect of economic growth on the CO<sub>2</sub>, on the level of the economic situation of the country, where the countries have positive GDP effect with CO<sub>2</sub>, but Oman and Bahrain have less economic growth compared with other four countries like Kuwait, Qatar, KSA, and UAE. These countries are on top of the largest energy reserve in the world&#x2014;also, a significant positive effect between energy consumption and CO<sub>2</sub> in GCC countries.</p>
<p>The data presented here concerning causal relationships between oil price shocks and CO<sub>2</sub> emissions has policy implications for GCC countries. According to the findings, GCC governments may prioritize clean and green economic growth by maintaining oil prices as low as feasible, which would be more effective in terms of environmental sustainability. The environmental degradation problem in these countries cannot be solved systematically and solely by economic growth. The efforts should focus on non-oil sectors, focusing more on diversifying its energy mix, with a higher percentage of renewable (clean) energy production, adopting new policies regarding the development of efficient projects, and employing green finance tools to achieve sustainable economic growth. Economic policy which is supposed to be followed by GCC governments implies investment in renewable energy and smart energy, rather than fossil fuel energy to achieve their sustainable development goals and shed light on urgent global issues. These economies could invest primarily in low-carbon renewable energy resources and aim to outperform key acts where the green economy looks to be a top government goal. To achieve long-term economic development goals, policymakers must concentrate on new energy sources. To attain a digital economy, GCC countries must modify their economic growth patterns and promote economic diversification activities, as well as improve the efficiency of the energy sector. The government and policymakers should push for a more thorough reform of oil price shocks, paying special attention to the indirect risk of price shocks and their leveraging consequences. Furthermore, changes in oil prices and CO<sub>3</sub> emissions result in GCC nations needing authorities and policymakers to approach diesel and gasoline policies independently.</p>
</sec>
</body>
<back>
<sec id="s8">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s9">
<title>Author Contributions</title>
<p>AE: Conceptualization, Methodology, Data Curation, Formal analysis, Writing-Original draft HHL: Supervision, Conceptualization, Methodology, Writing-Reviewing and Editing, Resources UA-M: Validation, Writing-Reviewing and Editing.</p>
</sec>
<sec sec-type="COI-statement" id="s11">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s12">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<ref-list>
<title>References</title>
<ref id="B1">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Abokyi</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>Appiah-Konadu</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Abokyi</surname>
<given-names>F.</given-names>
</name>
<name>
<surname>Oteng-Abayie</surname>
<given-names>E. F.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Industrial Growth and Emissions of CO2 in Ghana: The Role of Financial Development and Fossil Fuel Consumption</article-title>. <source>Energy Rep.</source> <volume>5</volume>, <fpage>1339</fpage>&#x2013;<lpage>1353</lpage>. <pub-id pub-id-type="doi">10.1016/j.egyr.2019.09.002</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.egyr.2019.09.002">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Industrial+Growth+and+Emissions+of+CO2+in+Ghana:+The+Role+of+Financial+Development+and+Fossil+Fuel+Consumption&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B2">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Abumunshar</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Aga</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Samour</surname>
<given-names>A.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Oil Price, Energy Consumption, and CO2 Emissions in Turkey. New Evidence from a Bootstrap ARDL Test</article-title>. <source>Energies</source> <volume>13</volume>, <fpage>5588</fpage>. <pub-id pub-id-type="doi">10.3390/en13215588</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3390/en13215588">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Oil+Price,+Energy+Consumption,+and+CO2+Emissions+in+Turkey.+New+Evidence+from+a+Bootstrap+ARDL+Test&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B3">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Agbanike</surname>
<given-names>T. F.</given-names>
</name>
<name>
<surname>Nwani</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Uwazie</surname>
<given-names>U. I.</given-names>
</name>
<name>
<surname>Anochiwa</surname>
<given-names>L. I.</given-names>
</name>
<name>
<surname>Onoja</surname>
<given-names>T. G. C.</given-names>
</name>
<name>
<surname>Ogbonnaya</surname>
<given-names>I. O.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Oil Price, Energy Consumption and Carbon Dioxide (CO 2) Emissions: Insight into Sustainability Challenges in Venezuela</article-title>. <source>Lat. Am. Econ. Rev.</source> <volume>28</volume> (<issue>1</issue>), <fpage>1</fpage>&#x2013;<lpage>26</lpage>. <pub-id pub-id-type="doi">10.1186/s40503-019-0070-8</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1186/s40503-019-0070-8">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Oil+Price,+Energy+Consumption+and+Carbon+Dioxide+(CO+2)+Emissions:+Insight+into+Sustainability+Challenges+in+Venezuela&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B4">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ahmed</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Ahmed</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Ismail</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Predictive Analysis of CO2 Emissions and the Role of Environmental Technology, Energy Use and Economic Output: Evidence from Emerging Economies</article-title>. <source>Air Qual. Atmos. Health</source> <volume>13</volume>. <pub-id pub-id-type="doi">10.1007/s11869-020-00855-1</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11869-020-00855-1">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Predictive+Analysis+of+CO2+Emissions+and+the+Role+of+Environmental+Technology,+Energy+Use+and+Economic+Output:+Evidence+from+Emerging+Economies&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B5">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Al-Mulali</surname>
<given-names>U.</given-names>
</name>
<name>
<surname>Che Sab</surname>
<given-names>C. N. B.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>Electricity Consumption, CO2 Emission, and Economic Growth in the Middle East</article-title>. <source>Energy Sources, Part B Econ. Plan. Policy</source> <volume>13</volume> (<issue>5</issue>), <fpage>257</fpage>&#x2013;<lpage>263</lpage>. <pub-id pub-id-type="doi">10.1080/15567249.2012.658958</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1080/15567249.2012.658958">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Electricity+Consumption,+CO2+Emission,+and+Economic+Growth+in+the+Middle+East&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B6">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Al-Mulali</surname>
<given-names>U.</given-names>
</name>
<name>
<surname>Ozturk</surname>
<given-names>I.</given-names>
</name>
</person-group> (<year>2016</year>). <article-title>The Investigation of Environmental Kuznets Curve Hypothesis in the Advanced Economies: the Role of Energy Prices</article-title>. <source>Renew. Sustain. Energy Rev.</source> <volume>54</volume>, <fpage>1622</fpage>&#x2013;<lpage>1631</lpage>. <pub-id pub-id-type="doi">10.1016/j.rser.2015.10.131</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.rser.2015.10.131">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Investigation+of+Environmental+Kuznets+Curve+Hypothesis+in+the+Advanced+Economies:+the+Role+of+Energy+Prices&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B7">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Al-Saidi</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Elagib</surname>
<given-names>N. A.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>Ecological Modernization and Responses for a Low-Carbon Future in the Gulf Cooperation Council Countries</article-title>. <source>Wiley Interdiscip. Rev. Clim. Change</source> <volume>9</volume> (<issue>4</issue>), <fpage>e528</fpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Ecological+Modernization+and+Responses+for+a+Low-Carbon+Future+in+the+Gulf+Cooperation+Council+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B8">
<citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname>Ali</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Ejaz</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Anjum</surname>
<given-names>M. A.</given-names>
</name>
<name>
<surname>Nawaz</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Ahmad</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2020</year>). &#x201c;<article-title>Impact of Climate Change on Postharvest Physiology of Edible Plant Products</article-title>,&#x201d; in <source>Plant Ecophysiology and Adaptation under Climate Change: Mechanisms and Perspectives I</source> (<publisher-loc>Singapore</publisher-loc>: <publisher-name>Springer</publisher-name>), <fpage>87</fpage>&#x2013;<lpage>115</lpage>. <pub-id pub-id-type="doi">10.1007/978-981-15-2156-0_4</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/978-981-15-2156-0_4">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Impact+of+Climate+Change+on+Postharvest+Physiology+of+Edible+Plant+Products&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B9">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Aljadani</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Toumi</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Toumi</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Hsini</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Jallali</surname>
<given-names>B.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Investigation of the N-Shaped Environmental Kuznets Curve for COVID-19 Mitigation in the KSA</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>28</volume>, <fpage>29681</fpage>&#x2013;<lpage>29700</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-021-12713-3</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11356-021-12713-3">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Investigation+of+the+N-Shaped+Environmental+Kuznets+Curve+for+COVID-19+Mitigation+in+the+KSA&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B10">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Alshehry</surname>
<given-names>A. S.</given-names>
</name>
<name>
<surname>Belloumi</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>Energy Consumption, Carbon Dioxide Emissions and Economic Growth: The Case of Saudi Arabia</article-title>. <source>Renew. Sustain. Energy Rev.</source> <volume>41</volume>, <fpage>237</fpage>&#x2013;<lpage>247</lpage>. <pub-id pub-id-type="doi">10.1016/j.rser.2014.08.004</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.rser.2014.08.004">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Energy+Consumption,+Carbon+Dioxide+Emissions+and+Economic+Growth:+The+Case+of+Saudi+Arabia&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B12">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Anser</surname>
<given-names>M. K.</given-names>
</name>
<name>
<surname>Syed</surname>
<given-names>Q. R.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
<name>
<surname>Alola</surname>
<given-names>A. A.</given-names>
</name>
<name>
<surname>Ahmad</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Do Economic Policy Uncertainty and Geopolitical Risk Lead to Environmental Degradation? Evidence from Emerging Economies</article-title>. <source>Sustainability</source> <volume>13</volume> (<issue>11</issue>), <fpage>5866</fpage>. <pub-id pub-id-type="doi">10.3390/su13115866</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3390/su13115866">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Do+Economic+Policy+Uncertainty+and+Geopolitical+Risk+Lead+to+Environmental+Degradation?+Evidence+from+Emerging+Economies&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B13">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Apergis</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Gangopadhyay</surname>
<given-names>P.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>The Asymmetric Relationships between Pollution, Energy Use and Oil Prices in Vietnam: Some Behavioural Implications for Energy Policy-Making</article-title>. <source>Energy Policy</source> <volume>140</volume>, <fpage>111,430</fpage>&#x2013;<lpage>111,442</lpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2020.111430</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.enpol.2020.111430">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Asymmetric+Relationships+between+Pollution,+Energy+Use+and+Oil+Prices+in+Vietnam:+Some+Behavioural+Implications+for+Energy+Policy-Making&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B14">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Apergis</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Payne</surname>
<given-names>J. E.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>Renewable Energy, Output, Carbon Dioxide Emissions, and Oil Prices: Evidence from South America</article-title>. <source>Energy Sources, Part B Econ. Plan. Policy</source> <volume>10</volume> (<issue>3</issue>), <fpage>281</fpage>&#x2013;<lpage>287</lpage>. <pub-id pub-id-type="doi">10.1080/15567249.2013.853713</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1080/15567249.2013.853713">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Renewable+Energy,+Output,+Carbon+Dioxide+Emissions,+and+Oil+Prices:+Evidence+from+South+America&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B15">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ari</surname>
<given-names>I.</given-names>
</name>
<name>
<surname>&#x15e;ent&#xfc;rk</surname>
<given-names>H.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>The Relationship between GDP and Methane Emissions from Solid Waste: A Panel Data Analysis for the G7</article-title>. <source>Sustain. Prod. Consum.</source> <volume>23</volume>, <fpage>282</fpage>&#x2013;<lpage>290</lpage>. <pub-id pub-id-type="doi">10.1016/j.spc.2020.06.004</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.spc.2020.06.004">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Relationship+between+GDP+and+Methane+Emissions+from+Solid+Waste:+A+Panel+Data+Analysis+for+the+G7&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B16">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Arouri</surname>
<given-names>M. E. H.</given-names>
</name>
<name>
<surname>Ben Youssef</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>M&#x27;Henni</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Rault</surname>
<given-names>C.</given-names>
</name>
</person-group> (<year>2012</year>). <article-title>Energy Consumption, Economic Growth and CO2 Emissions in Middle East and North African Countries</article-title>. <source>Energy Policy</source> <volume>45</volume>, <fpage>342</fpage>&#x2013;<lpage>349</lpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2012.02.042</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.enpol.2012.02.042">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Energy+Consumption,+Economic+Growth+and+CO2+Emissions+in+Middle+East+and+North+African+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B117">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Badeeb</surname>
<given-names>R. A.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>Asymmetric impact of oil price on Islamic sectoral stocks</article-title>. <source>Energy Economics,</source> <volume>71</volume>, <fpage>128</fpage>&#x2013;<lpage>139</lpage>. <pub-id pub-id-type="doi">10.1016/j.resourpol.2021.102326</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.resourpol.2021.102326">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Asymmetric+impact+of+oil+price+on+Islamic+sectoral+stocks&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B17">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Badeeb</surname>
<given-names>R. A.</given-names>
</name>
<name>
<surname>Szulczyk</surname>
<given-names>K. R.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Asymmetries in the Effect of Oil Rent Shocks on Economic Growth: A Sectoral Analysis from the Perspective of the Oil Curse</article-title>. <source>Resour. Policy</source> <volume>74</volume>, <fpage>102326</fpage>. <pub-id pub-id-type="doi">10.1016/j.resourpol.2021.102326</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.resourpol.2021.102326">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Asymmetries+in+the+Effect+of+Oil+Rent+Shocks+on+Economic+Growth:+A+Sectoral+Analysis+from+the+Perspective+of+the+Oil+Curse&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B18">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Balaguer</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Cantavella</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>Estimating the Environmental Kuznets Curve for Spain by Considering Fuel Oil Prices</article-title>. <source>Ecol. Indic.</source> <volume>60</volume>, <fpage>853</fpage>&#x2013;<lpage>859</lpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Estimating+the+Environmental+Kuznets+Curve+for+Spain+by+Considering+Fuel+Oil+Prices&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B19">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Baltagi</surname>
<given-names>B. H.</given-names>
</name>
<name>
<surname>Feng</surname>
<given-names>Q.</given-names>
</name>
<name>
<surname>Kao</surname>
<given-names>C.</given-names>
</name>
</person-group> (<year>2012</year>). <article-title>A Lagrange Multiplier Test for Cross-Sectional Dependence in a Fixed Effects Panel Data Model</article-title>. <source>J. Econ.</source> <volume>170</volume> (<issue>1</issue>), <fpage>164</fpage>&#x2013;<lpage>177</lpage>. <pub-id pub-id-type="doi">10.1016/j.jeconom.2012.04.004</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.jeconom.2012.04.004">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=A+Lagrange+Multiplier+Test+for+Cross-Sectional+Dependence+in+a+Fixed+Effects+Panel+Data+Model&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B21">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bayomi</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>E. Fernandez</surname>
<given-names>J.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Towards Sustainable Energy Trends in the Middle East: A Study of Four Major Emitters</article-title>. <source>Energies</source> <volume>12</volume> (<issue>9</issue>), <fpage>1615</fpage>. <pub-id pub-id-type="doi">10.3390/en12091615</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3390/en12091615">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Towards+Sustainable+Energy+Trends+in+the+Middle+East:+A+Study+of+Four+Major+Emitters&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B22">
<citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname>Bilgili</surname>
<given-names>F.</given-names>
</name>
<name>
<surname>Mugaloglu</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>Ko&#xe7;ak</surname>
<given-names>E.</given-names>
</name>
</person-group> (<year>2020</year>). &#x201c;<article-title>The Impact of Oil Prices on CO2 Emissions in China: a Wavelet Coherence Approach</article-title>,&#x201d; in <source>Econometrics of Green Energy Handbook</source>, <fpage>31</fpage>&#x2013;<lpage>57</lpage>. <pub-id pub-id-type="doi">10.1007/978-3-030-46847-7_2</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/978-3-030-46847-7_2">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Impact+of+Oil+Prices+on+CO2+Emissions+in+China:+a+Wavelet+Coherence+Approach&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B23">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Boufateh</surname>
<given-names>T.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>The Environmental Kuznets Curve by Considering Asymmetric Oil Price Shocks: Evidence from the Top Two</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>26</volume> (<issue>1</issue>), <fpage>706</fpage>&#x2013;<lpage>720</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-018-3641-3</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11356-018-3641-3">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Environmental+Kuznets+Curve+by+Considering+Asymmetric+Oil+Price+Shocks:+Evidence+from+the+Top+Two&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B24">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Breusch</surname>
<given-names>T. S.</given-names>
</name>
<name>
<surname>Pagan</surname>
<given-names>A. R.</given-names>
</name>
</person-group> (<year>1980</year>). <article-title>The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics</article-title>. <source>Rev. Econ. Stud.</source> <volume>47</volume>, <fpage>239</fpage>&#x2013;<lpage>253</lpage>. <pub-id pub-id-type="doi">10.2307/2297111</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.2307/2297111">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Lagrange+Multiplier+Test+and+its+Applications+to+Model+Specification+in+Econometrics&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B25">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bergmann</surname>
<given-names>P.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Oil Price Shocks and GDP Growth: Do Energy Shares Amplify Causal Effects?</article-title> <source>Energy Econ.</source> <volume>80</volume>, <fpage>1010</fpage>&#x2013;<lpage>1040</lpage>. <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.eneco.2019.01.031">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Oil+Price+Shocks+and+GDP+Growth:+Do+Energy+Shares+Amplify+Causal+Effects?&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B26">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bruvoll</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Medin</surname>
<given-names>H.</given-names>
</name>
</person-group> (<year>2003</year>). <article-title>Factors behind the Environmental Kuznets Curve. A Decomposition of the Changes in Air Pollution</article-title>. <source>Environ. Resour. Econ.</source> <volume>24</volume> (<issue>1</issue>), <fpage>27</fpage>&#x2013;<lpage>48</lpage>. <pub-id pub-id-type="doi">10.1023/a:1022881928158</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1023/a:1022881928158">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Factors+behind+the+Environmental+Kuznets+Curve.+A+Decomposition+of+the+Changes+in+Air+Pollution&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B27">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Cashin</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Mohaddes</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Raissi</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>The Differential Effects of Oil Demand and Supply Shocks on the Global Economy</article-title>. <source>Energy Econ.</source> <volume>44</volume>, <fpage>113</fpage>&#x2013;<lpage>134</lpage>. <pub-id pub-id-type="doi">10.1016/j.eneco.2014.03.014</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.eneco.2014.03.014">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Differential+Effects+of+Oil+Demand+and+Supply+Shocks+on+the+Global+Economy&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B28">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chai</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Zhou</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Liang</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Xing</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Lai</surname>
<given-names>K.</given-names>
</name>
</person-group> (<year>2016</year>). <article-title>Impact of International Oil Price on Energy Conservation and Emission Reduction in China</article-title>. <source>Sustainability</source> <volume>8</volume> (<issue>6</issue>), <fpage>508</fpage>. <pub-id pub-id-type="doi">10.3390/su8060508</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3390/su8060508">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Impact+of+International+Oil+Price+on+Energy+Conservation+and+Emission+Reduction+in+China&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B29">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chang</surname>
<given-names>T.-H.</given-names>
</name>
<name>
<surname>Huang</surname>
<given-names>C.-M.</given-names>
</name>
<name>
<surname>Lee</surname>
<given-names>M.-C.</given-names>
</name>
</person-group> (<year>2009</year>). <article-title>Threshold Effect of the Economic Growth Rate on the Renewable Energy Development from a Change in Energy Price: Evidence from OECD Countries</article-title>. <source>Energy Policy</source> <volume>37</volume>, <fpage>5796</fpage>&#x2013;<lpage>5802</lpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2009.08.049</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.enpol.2009.08.049">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Threshold+Effect+of+the+Economic+Growth+Rate+on+the+Renewable+Energy+Development+from+a+Change+in+Energy+Price:+Evidence+from+OECD+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B30">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Charfeddine</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Kahia</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Impact of Renewable Energy Consumption and Financial Development on CO2 Emissions and Economic Growth in the MENA Region: A Panel Vector Autoregressive (PVAR) Analysis</article-title>. <source>Renew. Energy</source> <volume>139</volume>, <fpage>199</fpage>&#x2013;<lpage>213</lpage>. <pub-id pub-id-type="doi">10.1016/j.renene.2019.01.010</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.renene.2019.01.010">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Impact+of+Renewable+Energy+Consumption+and+Financial+Development+on+CO2+Emissions+and+Economic+Growth+in+the+MENA+Region:+A+Panel+Vector+Autoregressive+(PVAR)+Analysis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B31">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chaudhry</surname>
<given-names>I. S.</given-names>
</name>
<name>
<surname>Azali</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Faheem</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Ali</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Asymmetric Dynamics of Oil Price and Environmental Degradation: Evidence from Pakistan</article-title>. <source>Reads</source> <volume>6</volume> (<issue>1</issue>), <fpage>1</fpage>&#x2013;<lpage>12</lpage>. <pub-id pub-id-type="doi">10.47067/reads.v6i1.179</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.47067/reads.v6i1.179">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Asymmetric+Dynamics+of+Oil+Price+and+Environmental+Degradation:+Evidence+from+Pakistan&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B95">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Chen</surname>
<given-names>L. J.</given-names>
</name>
<name>
<surname>Lin</surname>
<given-names>Y. L.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>Does Air Pollution Respond to Petroleum Price</article-title>. <source>Int. J. Appl. Econ</source> <volume>12</volume>, <fpage>104</fpage>&#x2013;<lpage>125</lpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Does+Air+Pollution+Respond+to+Petroleum+Price&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B32">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Constantinos</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Eleni</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Nikolaos</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Bantis</surname>
<given-names>D.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Greenhouse Gas Emissions-Crude Oil Prices: an Empirical Investigation in a Nonlinear Framework</article-title>. <source>Environ. Dev. Sustain</source> <volume>21</volume> (<issue>6</issue>), <fpage>2835</fpage>&#x2013;<lpage>2856</lpage>. <pub-id pub-id-type="doi">10.1007/s10668-018-0163-6</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s10668-018-0163-6">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Greenhouse+Gas+Emissions-Crude+Oil+Prices:+an+Empirical+Investigation+in+a+Nonlinear+Framework&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B33">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Dong</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Sun</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Hochman</surname>
<given-names>G.</given-names>
</name>
<name>
<surname>Zeng</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Jiang</surname>
<given-names>H.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>Impact of Natural Gas Consumption on CO2 Emissions: Panel Data Evidence from China&#x27;s Provinces</article-title>. <source>J. Clean. Prod.</source> <volume>162</volume>, <fpage>400</fpage>&#x2013;<lpage>410</lpage>. <pub-id pub-id-type="doi">10.1016/j.jclepro.2017.06.100</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.jclepro.2017.06.100">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Impact+of+Natural+Gas+Consumption+on+CO2+Emissions:+Panel+Data+Evidence+from+China&#x27;s+Provinces&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B34">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ehigiamusoe</surname>
<given-names>K. U.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Effects of Energy Consumption, Economic Growth, and Financial Development on Carbon Emissions: Evidence from Heterogeneous Income Groups</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>26</volume> (<issue>22</issue>), <fpage>22611</fpage>&#x2013;<lpage>22624</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-019-05309-5</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11356-019-05309-5">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Effects+of+Energy+Consumption,+Economic+Growth,+and+Financial+Development+on+Carbon+Emissions:+Evidence+from+Heterogeneous+Income+Groups&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B35">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ehigiamusoe</surname>
<given-names>K. U.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
<name>
<surname>Smyth</surname>
<given-names>R.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>The Moderating Role of Energy Consumption in the Carbon Emissions-Income Nexus in Middle-Income Countries</article-title>. <source>Appl. Energy</source> <volume>261</volume>, <fpage>114215</fpage>. <pub-id pub-id-type="doi">10.1016/j.apenergy.2019.114215</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.apenergy.2019.114215">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Moderating+Role+of+Energy+Consumption+in+the+Carbon+Emissions-Income+Nexus+in+Middle-Income+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B36">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Fern&#xe1;ndez-V&#xe1;zquez</surname>
<given-names>J.-S.</given-names>
</name>
<name>
<surname>Sancho-Rodr&#xed;guez</surname>
<given-names>&#xc1;.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Critical Discourse Analysis of Climate Change in IBEX 35 Companies</article-title>. <source>Technol. Forecast. Soc. Change</source> <volume>157</volume>, <fpage>120063</fpage>. <pub-id pub-id-type="doi">10.1016/j.techfore.2020.120063</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.techfore.2020.120063">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Critical+Discourse+Analysis+of+Climate+Change+in+IBEX+35+Companies&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B37">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Gbatu</surname>
<given-names>A. P.</given-names>
</name>
<name>
<surname>Wang</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Junior</surname>
<given-names>P. K. W.</given-names>
</name>
<name>
<surname>Sesay</surname>
<given-names>V. A.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>How Do Energy Consumption, Output, Energy Price, and Population Growth Correlate with CO2 Emissions in Liberia</article-title>. <source>Ijgenvi</source> <volume>18</volume>, <fpage>209</fpage>&#x2013;<lpage>235</lpage>. <pub-id pub-id-type="doi">10.1504/ijgenvi.2019.102776</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1504/ijgenvi.2019.102776">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=How+Do+Energy+Consumption,+Output,+Energy+Price,+and+Population+Growth+Correlate+with+CO2+Emissions+in+Liberia&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B38">
<citation citation-type="book">
<collab>Gulf Cooperation Council</collab> (<year>2017</year>). <source>The Economic Outlook and Policy Challenges in the GCC Countries</source>. <comment>Available at: <ext-link ext-link-type="uri" xlink:href="https://www.imf.org/en/Publications/Policy-Papers/Issues/2017/12/14/pp121417gcc-economic-outlook-and-policy-challenges">https://www.imf.org/en/Publications/Policy-Papers/Issues/2017/12/14/pp121417gcc-economic-outlook-and-policy-challenges</ext-link>
</comment>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Economic+Outlook+and+Policy+Challenges+in+the+GCC+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B39">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Hamdi</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Sbia</surname>
<given-names>R.</given-names>
</name>
</person-group> (<year>2013</year>). <article-title>Dynamic Relationships between Oil Revenues, Government Spending and Economic Growth in an Oil-dependent Economy</article-title>. <source>Econ. Model.</source> <volume>35</volume>, <fpage>118</fpage>&#x2013;<lpage>125</lpage>. <pub-id pub-id-type="doi">10.1016/j.econmod.2013.06.043</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.econmod.2013.06.043">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Dynamic+Relationships+between+Oil+Revenues,+Government+Spending+and+Economic+Growth+in+an+Oil-dependent+Economy&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B40">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Hammoudeh</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Mensi</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>Reboredo</surname>
<given-names>J. C.</given-names>
</name>
<name>
<surname>Nguyen</surname>
<given-names>D. K.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>Dynamic Dependence of the Global Islamic Equity Index with Global Conventional Equity Market Indices and Risk Factors</article-title>. <source>Pacific-Basin Finance J.</source> <volume>30</volume>, <fpage>189</fpage>&#x2013;<lpage>206</lpage>. <pub-id pub-id-type="doi">10.1016/j.pacfin.2014.10.001</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.pacfin.2014.10.001">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Dynamic+Dependence+of+the+Global+Islamic+Equity+Index+with+Global+Conventional+Equity+Market+Indices+and+Risk+Factors&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B41">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Hammoudeh</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Nguyen</surname>
<given-names>D. K.</given-names>
</name>
<name>
<surname>Sousa</surname>
<given-names>R. M.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>US Monetary Policy and Sectoral Commodity Prices</article-title>. <source>J. Int. Money Finance</source> <volume>57</volume>, <fpage>61</fpage>&#x2013;<lpage>85</lpage>. <pub-id pub-id-type="doi">10.1016/j.jimonfin.2015.06.003</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.jimonfin.2015.06.003">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=US+Monetary+Policy+and+Sectoral+Commodity+Prices&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B42">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Haque</surname>
<given-names>M. I.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Negating the Role of Institutions in the Long Run Growth of an Oil Producing Country</article-title>. <source>Ijeep</source> <volume>10</volume> (<issue>5</issue>), <fpage>503</fpage>&#x2013;<lpage>509</lpage>. <pub-id pub-id-type="doi">10.32479/ijeep.9870</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.32479/ijeep.9870">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Negating+the+Role+of+Institutions+in+the+Long+Run+Growth+of+an+Oil+Producing+Country&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B43">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>He</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Richard</surname>
<given-names>P.</given-names>
</name>
</person-group> (<year>2010</year>). <article-title>Environmental Kuznets Curve for CO2 in Canada</article-title>. <source>Ecol. Econ.</source> <volume>69</volume> (<issue>5</issue>), <fpage>1083</fpage>&#x2013;<lpage>1093</lpage>. <pub-id pub-id-type="doi">10.1016/j.ecolecon.2009.11.030</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.ecolecon.2009.11.030">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Environmental+Kuznets+Curve+for+CO2+in+Canada&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B44">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Husaini</surname>
<given-names>D. H.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
<name>
<surname>Ab. Rahim</surname>
<given-names>R.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>The Relationship between Energy Subsidies, Oil Prices, and CO2 Emissions in Selected Asian Countries: a Panel Threshold Analysis</article-title>. <source>Australas. J. Environ. Manag.</source> <volume>28</volume> (<issue>4</issue>), <fpage>1</fpage>&#x2013;<lpage>16</lpage>. <pub-id pub-id-type="doi">10.1080/14486563.2021.1961620</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1080/14486563.2021.1961620">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Relationship+between+Energy+Subsidies,+Oil+Prices,+and+CO2+Emissions+in+Selected+Asian+Countries:+a+Panel+Threshold+Analysis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B45">
<citation citation-type="book">
<collab>IEA</collab> (<year>2019</year>). <source>World Energy Outlook</source>. <publisher-loc>Paris</publisher-loc>: <publisher-name>IEA</publisher-name>. <comment>Available at: <ext-link ext-link-type="uri" xlink:href="https://wwwieaorg/reports/world-energy-outlook-2019">https://wwwieaorg/reports/world-energy-outlook-2019</ext-link>
</comment>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=World+Energy+Outlook&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B46">
<citation citation-type="book">
<collab>International Energy Agency (IEA)</collab> (<year>2005</year>). <source>Middle East and North Africa Insights</source>. <publisher-loc>Paris, France</publisher-loc>: <publisher-name>IEA</publisher-name>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Middle+East+and+North+Africa+Insights&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B47">
<citation citation-type="web">
<collab>International Monetary Fund (IMF)</collab> (<year>2016</year>). <article-title>Annual Meeting of Arab Ministers of Finance: A Economic Diversification in Oil-Exporting Arab Countries</article-title>. <comment>Prepared by Staff of the International Monetary Fund. Available at: <ext-link ext-link-type="uri" xlink:href="https://www.imf.org/external/np/pp/eng/2016/042916.pdf">https://www.imf.org/external/np/pp/eng/2016/042916.pdf</ext-link>
</comment>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Annual+Meeting+of+Arab+Ministers+of+Finance:+A+Economic+Diversification+in+Oil-Exporting+Arab+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B48">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Jaunky</surname>
<given-names>V. C.</given-names>
</name>
</person-group> (<year>2011</year>). <article-title>The CO 2 Emissions-Income Nexus: Evidence from Rich Countries</article-title>. <source>Energy Policy</source> <volume>39</volume>, <fpage>1228</fpage>&#x2013;<lpage>1240</lpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2010.11.050</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.enpol.2010.11.050">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+CO+2+Emissions-Income+Nexus:+Evidence+from+Rich+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B49">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Jiao</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Sharma</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Kautish</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Hussain</surname>
<given-names>H.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>Unveiling the Asymmetric Impact of Exports, Oil Prices, Technological Innovations, and Income Inequality on Carbon Emissions in India</article-title>. <source>Resour. Policy</source> <volume>74</volume>. <pub-id pub-id-type="doi">10.1016/j.resourpol.2021.102408</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.resourpol.2021.102408">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Unveiling+the+Asymmetric+Impact+of+Exports,+Oil+Prices,+Technological+Innovations,+and+Income+Inequality+on+Carbon+Emissions+in+India&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B50">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Kilian</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Stock</surname>
<given-names>J. H.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand John Coglianese Lucas W. Davis</article-title>. <source>Ann Arbor</source> <volume>1001</volume>, <fpage>48109</fpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Anticipation,+Tax+Avoidance,+and+the+Price+Elasticity+of+Gasoline+Demand+John+Coglianese+Lucas+W.+Davis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B51">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Kuznets</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>1955</year>). <article-title>Economic Growth and Income Inequality</article-title>. <source>Am. Econ. Rev.</source> <volume>45</volume>, <fpage>1</fpage>&#x2013;<lpage>28</lpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Economic+Growth+and+Income+Inequality&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B52">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
<name>
<surname>McAleer</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Wong</surname>
<given-names>W.-K.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>Preferences of Risk-Averse and Risk-Seeking Investors for Oil Spot and Futures before, during and after the Global Financial Crisis</article-title>. <source>Int. Rev. Econ. Finance</source> <volume>40</volume>, <fpage>204</fpage>&#x2013;<lpage>216</lpage>. <pub-id pub-id-type="doi">10.1016/j.iref.2015.02.019</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.iref.2015.02.019">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Preferences+of+Risk-Averse+and+Risk-Seeking+Investors+for+Oil+Spot+and+Futures+before,+during+and+after+the+Global+Financial+Crisis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B53">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Li</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Fang</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>He</surname>
<given-names>L.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>The Impact of Energy Price on CO2 Emissions in China: a Spatial Econometric Analysis</article-title>. <source>Sci. Total Environ.</source> <volume>706</volume>, <fpage>135942</fpage>. <pub-id pub-id-type="doi">10.1016/j.scitotenv.2019.135942</pub-id> <ext-link ext-link-type="uri" xlink:href="https://pubmed.ncbi.nlm.nih.gov/31846876/">PubMed Abstract</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.scitotenv.2019.135942">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Impact+of+Energy+Price+on+CO2+Emissions+in+China:+a+Spatial+Econometric+Analysis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B54">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lin</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Jia</surname>
<given-names>Z.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Impacts of Carbon Price Level in Carbon Emission Trading Market</article-title>. <source>Appl. Energy</source> <volume>239</volume>, <fpage>157</fpage>&#x2013;<lpage>170</lpage>. <pub-id pub-id-type="doi">10.1016/j.apenergy.2019.01.194</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.apenergy.2019.01.194">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Impacts+of+Carbon+Price+Level+in+Carbon+Emission+Trading+Market&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B55">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Mahmood</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Adow</surname>
<given-names>A. H.</given-names>
</name>
<name>
<surname>Abbas</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Iqbal</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Murshed</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Furqan</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2022</year>). <article-title>The Fiscal and Monetary Policies and Environment in GCC Countries: Analysis of Territory and Consumption-Based CO2 Emissions</article-title>. <source>Sustainability</source> <volume>14</volume> (<issue>3</issue>), <fpage>1225</fpage>. <pub-id pub-id-type="doi">10.3390/su14031225</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3390/su14031225">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Fiscal+and+Monetary+Policies+and+Environment+in+GCC+Countries:+Analysis+of+Territory+and+Consumption-Based+CO2+Emissions&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B56">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Mahmood</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Alkhateeb</surname>
<given-names>T. T. Y.</given-names>
</name>
<name>
<surname>Furqan</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Oil Sector and CO2 Emissions in Saudi Arabia: Asymmetry Analysis</article-title>. <source>Palgrave Commun.</source> <volume>6</volume>, <fpage>88</fpage>. <pub-id pub-id-type="doi">10.1057/s41599-020-0470-z</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1057/s41599-020-0470-z">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Oil+Sector+and+CO2+Emissions+in+Saudi+Arabia:+Asymmetry+Analysis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B58">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Maji</surname>
<given-names>I. K.</given-names>
</name>
<name>
<surname>Habibullah</surname>
<given-names>M. S.</given-names>
</name>
<name>
<surname>Saari</surname>
<given-names>M. Y.</given-names>
</name>
<name>
<surname>Abdul-Rahim</surname>
<given-names>A. S.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>The Nexus between Energy Price Changes and Environmental Quality in Malaysia</article-title>. <source>Energy Sources, Part B Econ. Plan. Policy</source> <volume>12</volume> (<issue>10</issue>), <fpage>903</fpage>&#x2013;<lpage>909</lpage>. <pub-id pub-id-type="doi">10.1080/15567249.2017.1323052</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1080/15567249.2017.1323052">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Nexus+between+Energy+Price+Changes+and+Environmental+Quality+in+Malaysia&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B59">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Malik</surname>
<given-names>M. Y.</given-names>
</name>
<name>
<surname>Latif</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Khan</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Butt</surname>
<given-names>H. D.</given-names>
</name>
<name>
<surname>Hussain</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Nadeem</surname>
<given-names>M. A.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Symmetric and Asymmetric Impact of Oil Price, FDI and Economic Growth on Carbon Emission in Pakistan: Evidence from ARDL and Non-linear ARDL Approach</article-title>. <source>Sci. Total Environ.</source> <volume>726</volume>, <fpage>138421</fpage>. <pub-id pub-id-type="doi">10.1016/j.scitotenv.2020.138421</pub-id> <ext-link ext-link-type="uri" xlink:href="https://pubmed.ncbi.nlm.nih.gov/32481222/">PubMed Abstract</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.scitotenv.2020.138421">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Symmetric+and+Asymmetric+Impact+of+Oil+Price,+FDI+and+Economic+Growth+on+Carbon+Emission+in+Pakistan:+Evidence+from+ARDL+and+Non-linear+ARDL+Approach&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B60">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Mark</surname>
<given-names>N. C.</given-names>
</name>
<name>
<surname>OgakiSul</surname>
<given-names>M. D.</given-names>
</name>
<name>
<surname>Sul</surname>
<given-names>D.</given-names>
</name>
</person-group> (<year>2005</year>). <article-title>Dynamic Seemingly Unrelated Cointegrating Regressions</article-title>. <source>Rev. Econ. Stud.</source> <volume>72</volume>, <fpage>797</fpage>&#x2013;<lpage>820</lpage>. <pub-id pub-id-type="doi">10.1111/j.1467-937x.2005.00352.x</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1111/j.1467-937x.2005.00352.x">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Dynamic+Seemingly+Unrelated+Cointegrating+Regressions&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B61">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Marques</surname>
<given-names>A. C.</given-names>
</name>
<name>
<surname>Fuinhas</surname>
<given-names>J. A.</given-names>
</name>
</person-group> (<year>2011</year>). <article-title>Drivers Promoting Renewable Energy: A Dynamic Panel Approach</article-title>. <source>Renew. Sustain. Energy Rev.</source> <volume>15</volume> (<issue>3</issue>), <fpage>1601</fpage>&#x2013;<lpage>1608</lpage>. <pub-id pub-id-type="doi">10.1016/j.rser.2010.11.048</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.rser.2010.11.048">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Drivers+Promoting+Renewable+Energy:+A+Dynamic+Panel+Approach&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B62">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Mensah</surname>
<given-names>I. A.</given-names>
</name>
<name>
<surname>Sun</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Gao</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Omari-Sasu</surname>
<given-names>A. Y.</given-names>
</name>
<name>
<surname>Zhu</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Ampimah</surname>
<given-names>B. C.</given-names>
</name>
<etal/>
</person-group> (<year>2019</year>). <article-title>Analysis on the Nexus of Economic Growth, Fossil Fuel Energy Consumption, CO2 Emissions and Oil Price in Africa Based on a PMG Panel ARDL Approach</article-title>. <source>J. Clean. Prod.</source> <volume>228</volume>, <fpage>161</fpage>&#x2013;<lpage>174</lpage>. <pub-id pub-id-type="doi">10.1016/j.jclepro.2019.04.281</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.jclepro.2019.04.281">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Analysis+on+the+Nexus+of+Economic+Growth,+Fossil+Fuel+Energy+Consumption,+CO2+Emissions+and+Oil+Price+in+Africa+Based+on+a+PMG+Panel+ARDL+Approach&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B63">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Munir</surname>
<given-names>Q.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
<name>
<surname>Smyth</surname>
<given-names>R.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>CO2 Emissions, Energy Consumption and Economic Growth in the ASEAN-5 Countries: A Cross-Sectional Dependence Approach</article-title>. <source>Energy Econ.</source> <volume>2019</volume>, <fpage>104571</fpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=CO2+Emissions,+Energy+Consumption+and+Economic+Growth+in+the+ASEAN-5+Countries:+A+Cross-Sectional+Dependence+Approach&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B64">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Murshed</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>An Empirical Analysis of the Non-linear Impacts of ICT-Trade Openness on Renewable Energy Transition, Energy Efficiency, Clean Cooking Fuel Access and Environmental Sustainability in South Asia</article-title>. <source>Environ. Sci. Pollut. Res.</source> <pub-id pub-id-type="doi">10.1007/s11356-020-09497-3</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11356-020-09497-3">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=An+Empirical+Analysis+of+the+Non-linear+Impacts+of+ICT-Trade+Openness+on+Renewable+Energy+Transition,+Energy+Efficiency,+Clean+Cooking+Fuel+Access+and+Environmental+Sustainability+in+South+Asia&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B65">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Murshed</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>LPG Consumption and Environmental Kuznets Curve Hypothesis in South Asia: a Time-Series ARDL Analysis with Multiple Structural Breaks</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>28</volume>, <fpage>8337</fpage>&#x2013;<lpage>8372</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-020-10701-7</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11356-020-10701-7">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=LPG+Consumption+and+Environmental+Kuznets+Curve+Hypothesis+in+South+Asia:+a+Time-Series+ARDL+Analysis+with+Multiple+Structural+Breaks&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B66">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Murshed</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Tanha</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Oil Price Shocks and Renewable Energy Transition: Empirical Evidence from Net Oil-Importing South Asian Economies</article-title>. <source>Energy Ecol. Environ.</source>, <fpage>183</fpage>&#x2013;<lpage>203</lpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Oil+Price+Shocks+and+Renewable+Energy+Transition:+Empirical+Evidence+from+Net+Oil-Importing+South+Asian+Economies&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B67">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Nasir</surname>
<given-names>M. A.</given-names>
</name>
<name>
<surname>Al-Emadi</surname>
<given-names>A. A.</given-names>
</name>
<name>
<surname>Shahbaz</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Hammoudeh</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Importance of Oil Shocks and the GCC Macroeconomy: A Structural VAR Analysis</article-title>. <source>Resour. Policy</source> <volume>61</volume>, <fpage>166</fpage>&#x2013;<lpage>179</lpage>. <pub-id pub-id-type="doi">10.1016/j.resourpol.2019.01.019</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.resourpol.2019.01.019">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Importance+of+Oil+Shocks+and+the+GCC+Macroeconomy:+A+Structural+VAR+Analysis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B68">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Nasser</surname>
<given-names>A. M.</given-names>
</name>
<name>
<surname>Hasim</surname>
<given-names>H. M.</given-names>
</name>
<name>
<surname>Al-Busaidi</surname>
<given-names>K.</given-names>
</name>
</person-group> (<year>2016</year>). <article-title>Modeling the Impact of the Oil Sector on the Economy of Sultanate of Oman</article-title>. <source>Int. J. Energy Econ. Policy</source> <volume>6</volume> (<issue>1</issue>), <fpage>120</fpage>&#x2013;<lpage>127</lpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Modeling+the+Impact+of+the+Oil+Sector+on+the+Economy+of+Sultanate+of+Oman&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B69">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Nusair</surname>
<given-names>S. A.</given-names>
</name>
</person-group> (<year>2016</year>). <article-title>The Effects of Oil Price Shocks on the Economies of the Gulf Co-operation Council Countries: Nonlinear Analysis</article-title>. <source>Energy Policy</source> <volume>91</volume>, <fpage>256</fpage>&#x2013;<lpage>267</lpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2016.01.013</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.enpol.2016.01.013">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Effects+of+Oil+Price+Shocks+on+the+Economies+of+the+Gulf+Co-operation+Council+Countries:+Nonlinear+Analysis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B70">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Nwani</surname>
<given-names>C.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>Causal Relationship between Crude Oil Price, Energy Consumption and Carbon Dioxide (CO2) Emissions in Ecuador</article-title>. <source>OPEC Energy Rev.</source> <volume>41</volume> (<issue>3</issue>), <fpage>201</fpage>&#x2013;<lpage>225</lpage>. <pub-id pub-id-type="doi">10.1111/opec.12102</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1111/opec.12102">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Causal+Relationship+between+Crude+Oil+Price,+Energy+Consumption+and+Carbon+Dioxide+(CO2)+Emissions+in+Ecuador&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B71">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Payne</surname>
<given-names>J. E.</given-names>
</name>
</person-group> (<year>2012</year>). <article-title>The Causal Dynamics between US Renewable Energy Consumption, Output, Emissions, and Oil Prices</article-title>. <source>Energy Sources, Part B Econ. Plan. Policy</source> <volume>7</volume> (<issue>4</issue>), <fpage>323</fpage>&#x2013;<lpage>330</lpage>. <pub-id pub-id-type="doi">10.1080/15567249.2011.595248</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1080/15567249.2011.595248">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Causal+Dynamics+between+US+Renewable+Energy+Consumption,+Output,+Emissions,+and+Oil+Prices&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B72">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Pesaran</surname>
<given-names>M. H.</given-names>
</name>
</person-group> (<year>2007</year>). <article-title>A Simple Panel Unit Root Test in the Presence of Cross-Section Dependence</article-title>. <source>J. Appl. Econ.</source> <volume>22</volume> (<issue>2</issue>), <fpage>265</fpage>&#x2013;<lpage>312</lpage>. <pub-id pub-id-type="doi">10.1002/jae.951</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1002/jae.951">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=A+Simple+Panel+Unit+Root+Test+in+the+Presence+of+Cross-Section+Dependence&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B73">
<citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname>Pesaran</surname>
<given-names>M. H.</given-names>
</name>
</person-group> (<year>2004</year>). &#x201c;<article-title>General Diagnostic Tests for Cross Section Dependence in Panels</article-title>,&#x201d; in <source>University of Cambridge, Working Paper, CWPE 0435</source> (<publisher-loc>Cambridge, UK</publisher-loc>: <publisher-name>Institute for the Study of Labor</publisher-name>). <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=General+Diagnostic+Tests+for+Cross+Section+Dependence+in+Panels&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B74">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Saboori</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Al-mulali</surname>
<given-names>U.</given-names>
</name>
<name>
<surname>Bin Baba</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Mohammed</surname>
<given-names>A. H.</given-names>
</name>
</person-group> (<year>2016</year>). <article-title>Oil-induced Environmental Kuznets Curve in Organization of Petroleum Exporting Countries (OPEC)</article-title>. <source>Int. J. Green Energy</source> <volume>13</volume> (<issue>4</issue>), <fpage>408</fpage>&#x2013;<lpage>416</lpage>. <pub-id pub-id-type="doi">10.1080/15435075.2014.961468</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1080/15435075.2014.961468">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Oil-induced+Environmental+Kuznets+Curve+in+Organization+of+Petroleum+Exporting+Countries+(OPEC)&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B75">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Sadorsky</surname>
<given-names>P.</given-names>
</name>
</person-group> (<year>2009b</year>). <article-title>Renewable Energy Consumption and Income in Emerging Economies</article-title>. <source>Energy Policy</source> <volume>37</volume> (<issue>10</issue>), <fpage>4021</fpage>&#x2013;<lpage>4028</lpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2009.05.003</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.enpol.2009.05.003">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Renewable+Energy+Consumption+and+Income+in+Emerging+Economies&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B76">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Sadorsky</surname>
<given-names>P.</given-names>
</name>
</person-group> (<year>2009a</year>). <article-title>Renewable Energy Consumption, CO2 Emissions and Oil Prices in the G7 Countries</article-title>. <source>Energy Econ.</source> <volume>31</volume> (<issue>3</issue>), <fpage>456</fpage>&#x2013;<lpage>462</lpage>. <pub-id pub-id-type="doi">10.1016/j.eneco.2008.12.010</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.eneco.2008.12.010">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Renewable+Energy+Consumption,+CO2+Emissions+and+Oil+Prices+in+the+G7+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B77">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Salahuddin</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Gow</surname>
<given-names>J.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>Economic Growth, Energy Consumption and CO2 Emissions in Gulf Cooperation Council Countries</article-title>. <source>Energy</source> <volume>73</volume>, <fpage>44</fpage>&#x2013;<lpage>58</lpage>. <pub-id pub-id-type="doi">10.1016/j.energy.2014.05.054</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.energy.2014.05.054">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Economic+Growth,+Energy+Consumption+and+CO2+Emissions+in+Gulf+Cooperation+Council+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B78">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Salahuddin</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Gow</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Ozturk</surname>
<given-names>I.</given-names>
</name>
</person-group> (<year>2015</year>). <article-title>Is the Long-Run Relationship between Economic Growth, Electricity Consumption, Carbon Dioxide Emissions and Financial Development in Gulf Cooperation Council Countries Robust?</article-title> <source>Renew. Sustain. Energy Rev.</source> <volume>51</volume>, <fpage>317</fpage>&#x2013;<lpage>326</lpage>. <pub-id pub-id-type="doi">10.1016/j.rser.2015.06.005</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.rser.2015.06.005">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Is+the+Long-Run+Relationship+between+Economic+Growth,+Electricity+Consumption,+Carbon+Dioxide+Emissions+and+Financial+Development+in+Gulf+Cooperation+Council+Countries+Robust?&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B79">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Shahbaz</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Bhattacharya</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Ahmed</surname>
<given-names>K.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>CO2emissions in Australia: Economic and Non-economic Drivers in the Long-Run</article-title>. <source>Appl. Econ.</source> <volume>49</volume> (<issue>13</issue>), <fpage>1273</fpage>&#x2013;<lpage>1286</lpage>. <pub-id pub-id-type="doi">10.1080/00036846.2016.1217306</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1080/00036846.2016.1217306">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=CO2emissions+in+Australia:+Economic+and+Non-economic+Drivers+in+the+Long-Run&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B96">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Shin</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Yu</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Greenwood-Nimmo</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework</article-title>. In <source>Festschrift in honor of Peter Schmidt</source>, <fpage>281</fpage>&#x2013;<lpage>314</lpage>. <publisher-loc>New York</publisher-loc>: <publisher-name>Springer</publisher-name> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/978-1-4899-8008-3_9">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Modelling+asymmetric+cointegration+and+dynamic+multipliers+in+a+nonlinear+ARDL+framework&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B80">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Sun</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Ding</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Fang</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>J.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>How Do Fossil Energy Prices Affect the Stock Prices of New Energy Companies? Evidence from Divisia Energy Price Index in China&#x27;s Market</article-title>. <source>Energy</source> <volume>169</volume>, <fpage>637</fpage>&#x2013;<lpage>645</lpage>. <pub-id pub-id-type="doi">10.1016/j.energy.2018.12.032</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.energy.2018.12.032">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=How+Do+Fossil+Energy+Prices+Affect+the+Stock+Prices+of+New+Energy+Companies?+Evidence+from+Divisia+Energy+Price+Index+in+China&#x27;s+Market&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B81">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tan</surname>
<given-names>F.</given-names>
</name>
<name>
<surname>Lean</surname>
<given-names>H. H.</given-names>
</name>
<name>
<surname>Khan</surname>
<given-names>H.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>Growth and Environmental Quality in Singapore: Is There Any Trade-Off?</article-title> <source>Ecol. Indic.</source> <volume>47</volume>, <fpage>149</fpage>&#x2013;<lpage>155</lpage>. <pub-id pub-id-type="doi">10.1016/j.ecolind.2014.04.035</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.ecolind.2014.04.035">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Growth+and+Environmental+Quality+in+Singapore:+Is+There+Any+Trade-Off?&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B82">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ullah</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Chishti</surname>
<given-names>M. Z.</given-names>
</name>
<name>
<surname>Majeed</surname>
<given-names>M. T.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>The Asymmetric Effects of Oil Price Changes on Environmental Pollution: Evidence from the Top Ten Carbon Emitters</article-title>. <source>Environ. Sci. Pollut. Res.</source> <volume>27</volume>, <fpage>29623</fpage>&#x2013;<lpage>29635</lpage>. <pub-id pub-id-type="doi">10.1007/s11356-020-09264-4</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11356-020-09264-4">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Asymmetric+Effects+of+Oil+Price+Changes+on+Environmental+Pollution:+Evidence+from+the+Top+Ten+Carbon+Emitters&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B83">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Umar</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Alam</surname>
<given-names>M. M.</given-names>
</name>
<name>
<surname>Al-Amin</surname>
<given-names>A. Q.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>Exploring the Contribution of Energy Price to Carbon Emissions in African Countries</article-title>. <source>Environ. Sci. Pollut. Res. Int.</source> <volume>28</volume> (<issue>63</issue>). <pub-id pub-id-type="doi">10.1007/s11356-020-10641-2</pub-id> <ext-link ext-link-type="uri" xlink:href="https://pubmed.ncbi.nlm.nih.gov/33090344/">PubMed Abstract</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11356-020-10641-2">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Exploring+the+Contribution+of+Energy+Price+to+Carbon+Emissions+in+African+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B84">
<citation citation-type="book">
<collab>Union of Concerned Scientists</collab> (<year>2018</year>). <source>Each Country&#x27;s Share of CO2 Emissions</source>. <comment>Available at: <ext-link ext-link-type="uri" xlink:href="https://www.ucsusa.org/resources/each-countrys-share-co2-emissions">https://www.ucsusa.org/resources/each-countrys-share-co2-emissions</ext-link>
</comment>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Each+Country&#x27;s+Share+of+CO2+Emissions&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B85">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Usman</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Hayat</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Bhutta</surname>
<given-names>M. M. A.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>SI Engine Fueled with Gasoline, CNG and CNG-HHO Blend: Comparative Evaluation of Performance, Emission and Lubrication Oil Deterioration</article-title>. <source>J. Therm. Sci.</source>, <fpage>1</fpage>&#x2013;<lpage>13</lpage>. <pub-id pub-id-type="doi">10.1007/s11630-020-1268-4</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1007/s11630-020-1268-4">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=SI+Engine+Fueled+with+Gasoline,+CNG+and+CNG-HHO+Blend:+Comparative+Evaluation+of+Performance,+Emission+and+Lubrication+Oil+Deterioration&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B86">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Wang</surname>
<given-names>Q.</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>R.</given-names>
</name>
</person-group> (<year>2016</year>). <article-title>Impact of Cheaper Oil on Economic System and Climate Change: A SWOT Analysis</article-title>. <source>Renew. Sustain. Energy Rev.</source> <volume>54</volume>, <fpage>925</fpage>&#x2013;<lpage>931</lpage>. <pub-id pub-id-type="doi">10.1016/j.rser.2015.10.087</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.rser.2015.10.087">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Impact+of+Cheaper+Oil+on+Economic+System+and+Climate+Change:+A+SWOT+Analysis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B87">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Wang</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Bai</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Xie</surname>
<given-names>C.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Investigating CO2 Mitigation Potentials and the Impact of Oil Price Distortion in China&#x27;s Transport Sector</article-title>. <source>Energy Policy</source> <volume>130</volume>, <fpage>320</fpage>&#x2013;<lpage>327</lpage>. <pub-id pub-id-type="doi">10.1016/j.enpol.2019.04.003</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.enpol.2019.04.003">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Investigating+CO2+Mitigation+Potentials+and+the+Impact+of+Oil+Price+Distortion+in+China&#x27;s+Transport+Sector&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B88">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Waqih</surname>
<given-names>M. A. U.</given-names>
</name>
<name>
<surname>Bhutto</surname>
<given-names>N. A.</given-names>
</name>
<name>
<surname>Ghumro</surname>
<given-names>N. H.</given-names>
</name>
<name>
<surname>Kumar</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Salam</surname>
<given-names>M. A.</given-names>
</name>
</person-group> (<year>2019</year>). <article-title>Rising Environmental Degradation and Impact of Foreign Direct Investment: an Empirical Evidence from SAARC Region</article-title>. <source>J. Environ. Manag.</source> <volume>243</volume>, <fpage>472</fpage>&#x2013;<lpage>480</lpage>. <pub-id pub-id-type="doi">10.1016/j.jenvman.2019.05.001</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.jenvman.2019.05.001">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Rising+Environmental+Degradation+and+Impact+of+Foreign+Direct+Investment:+an+Empirical+Evidence+from+SAARC+Region&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B89">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Westerlund</surname>
<given-names>J.</given-names>
</name>
</person-group> (<year>2007</year>). <article-title>Panel Cointegration Tests of the Fisher Hypothesis</article-title>. <source>J. Appl. Econ. Forthcom.</source> <volume>23</volume> (<issue>2</issue>), <fpage>193</fpage>&#x2013;<lpage>233</lpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Panel+Cointegration+Tests+of+the+Fisher+Hypothesis&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B90">
<citation citation-type="book">
<collab>World Bank</collab> (<year>2018</year>). <source>CO2 Emissions (Metric Tons Per Capita) - Kuwait</source>. <comment>Available at: <ext-link ext-link-type="uri" xlink:href="https://data.worldbank.org/indicator/EN.ATM.CO2E.PC?locations=KW">https://data.worldbank.org/indicator/EN.ATM.CO2E.PC?locations&#x3d;KW</ext-link>
</comment>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=CO2+Emissions+(Metric+Tons+Per+Capita)+-+Kuwait&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B91">
<citation citation-type="book">
<collab>World Bank</collab> (<year>2016</year>). <source>World Bank Annual Report</source>. <comment>Available at: <ext-link ext-link-type="uri" xlink:href="http://worldbank.org/annualreport">http://worldbank.org/annualreport</ext-link>
</comment>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=World+Bank+Annual+Report&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B92">
<citation citation-type="book">
<collab>Worldometers</collab> (<year>2016</year>). <source>Worldometers</source>. <comment>Available at: <ext-link ext-link-type="uri" xlink:href="https://www.worldometers.info/co2-emissions/united-arab-emirates-co2-emissions/">https://www.worldometers.info/co2-emissions/united-arab-emirates-co2-emissions/</ext-link>
</comment>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Worldometers&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B93">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zaghdoudi</surname>
<given-names>T.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>Internet Usage, Renewable Energy, Electricity Consumption and Economic Growth: Evidence from Developed Countries</article-title>. <source>Econ. Bull. Access Econ.</source> <volume>37</volume> (<issue>3</issue>), <fpage>1612</fpage>&#x2013;<lpage>1619</lpage>. <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=Internet+Usage,+Renewable+Energy,+Electricity+Consumption+and+Economic+Growth:+Evidence+from+Developed+Countries&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
<ref id="B94">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zhang</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Hu</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Cheng</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Song</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Xu</surname>
<given-names>B.</given-names>
</name>
<etal/>
</person-group> (<year>2019</year>). <article-title>The Effects of Energy Price, Technology, and Disaster Shocks on China&#x27;s Energy-Environment-Economy System</article-title>. <source>J. Clean. Prod.</source> <volume>207</volume>, <fpage>204</fpage>&#x2013;<lpage>213</lpage>. <pub-id pub-id-type="doi">10.1016/j.jclepro.2018.09.256</pub-id> <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.jclepro.2018.09.256">CrossRef Full Text</ext-link> &#x7c; <ext-link ext-link-type="uri" xlink:href="https://scholar.google.com/scholar?hl=en&#x0026;as_sdt=0%2C5&#x0026;q=The+Effects+of+Energy+Price,+Technology,+and+Disaster+Shocks+on+China&#x27;s+Energy-Environment-Economy+System&#x0026;btnG=">Google Scholar</ext-link>
</citation>
</ref>
</ref-list>
</back>
</article>