key: cord-0870722-7lup2e5d
authors: Husnain, Muhammad Iftikhar ul; Syed, Qasim Raza; Bashir, Arooj; Khan, Muhammad Aamir
title: Do geopolitical risk and energy consumption contribute to environmental degradation? Evidence from E7 countries
date: 2022-01-30
journal: Environ Sci Pollut Res Int
DOI: 10.1007/s11356-021-17606-z
sha: 4d0e1d2db7e08d46233b1b5c87c62fe18a0b6757
doc_id: 870722
cord_uid: 7lup2e5d

Environmental degradation is frequently cited as one of the eminent issues in the modern era. To limit environmental degradation, prior literature discerns several macroeconomic, socio-economic, and institutional factors that affect environmental degradation. However, the relationship between geopolitical risk and environmental degradation is understudied in the previous literature. To fill this gap, the inquiry at hand aims to scrutinize the influence of geopolitical risk on environmental degradation for E7 countries while controlling the effect of renewable energy, non-renewable energy, and GDP. Further, we utilize both the ecological footprint and CO(2) emissions as proxies of environmental degradation and employ second-generation panel methods for robust findings. In addition to this, the present study uses augmented mean group (AMG) estimator to provide long-run relationship among the selected variables. The findings from the AMG estimator expound that there exists environmental Kuznets curve (EKC) for E7 countries. Moreover, renewable energy ameliorates environmental quality because it plunges both ecological footprint and CO(2) emissions. On the contrary, non-renewable energy consumption escalates both ecological footprint and CO(2) emissions. Finally, geopolitical risk tends to decrease CO(2) emissions as well as ecological footprint. Our findings deduce a few policy implications to replenish environmental quality. For instance, the share of renewables in the energy mix should be surged to ameliorate the environmental quality. Further, to control both the geopolitical risk and environmental degradation at the same time, policymakers should put forward reforms and initiatives (e.g., policies to escalate R&D, technological innovations, and tax exemptions on imports of renewables) that can help to improve environmental quality without affecting geopolitical risk. At times of low geopolitical risk, environmental degradation will surge; therefore, the rate of environmental control taxes should be increased by the policymakers.

The growing number of state and regional instability, energy crisis, terrorist attacks, political copes, and other unfavorable events worldwide has aggravated the issue of geopolitical risk. Geopolitical risk (GPR) is referred to tensions linked with terrorism, wars, and unfriendly relations among countries (Adams et al. 2020) and is important to the economies susceptible to wars or war-like tensions, terrorism, ethnicity, conflict, and political violence. Furthermore, major geopolitical events such as 9/11, London bombing, Madrid bombing, Bombay attacks, China-USA trade war, Korea's nuclear issues, and Iranian trade tensions all pose a serious threat to the economic stability of a country (Cai and Wu 2020) . Geopolitical risk can affect economic performance and investment decisions and trigger business cycles that impact natural resource rents and financial markets (Price-waterhouseCoopers 2018; Balcilar et al. 2018; Dogan et al. 2021) . Unfavorable geopolitical events change the direction of investment spending towards less productive uses like reconstruction and security (Olanipekun and Alola 2020) . Moreover, extreme geopolitical events will cause panic among investors and businesses that will create abnormal fluctuations in the market and eventually influence energy returns and volatility (Qin et al. 2020 ). Subsequently, GPR is considered as one of the top five business threats globally (Price Waterhouse Coopers 2018). Recently, highlight that geopolitical risk also exerts detrimental impacts on tourism.

Geopolitical events have a harmful consequence not only on social and economic life but also on the environment. Anser et al. (2021a) put forward two theoretical channels that link GPR and the environment. The first channel is called the "escalating effect" which describes that GPR mitigates renewable energy consumption (hereafter REC) which in turn leads to higher carbon emissions. Parallel to this, the "mitigating effect" expounds that GPR curtails non-renewable energy consumption (hereafter NREC) and economic growth leading to a reduction in CO 2 emissions. In another study, Anser et al. (2021b) pointed out that GPR affects economic growth, R&D investment, innovations, technological advancements, and investment in clean energy. These aforementioned indicators eventually escalate emissions. Therefore, GPR may either curb or surge carbon emissions.

Based on the above milieu, this research contributes to the existing empirical literature by exploring the impact of GPR, economic growth, NREC, and REC on environmental degradation. To attain this, firstly, we use the recently introduced GPR index developed by Caldara and Iacoviello (2018) . Despite the significance of the prior studies and their results, the proxies of geopolitical events (e.g., terrorism/ terrorist attacks, war or militarization, and political instability) have some limitations of not in real-time, being discontinuous, and not covering the real geopolitical events. Moreover, these proxies do not accurately describe GPR as they do not account for all events, ranging from economic crisis to wars to climate change (Bouoiyour et al. 2019) . The GPR index captures the risk associated with terror attacks, military threats, war risk, political tensions, and geopolitical uncertainty. This index is superior to other indicators as it offers a time-consistent, holistic, and real-time approach to capture GPR. Moreover, the GPR index integrates both present and expected future risks (Muhammad and Long 2021) .

Secondly, many countries aim to achieve the goal of energy security for the smooth functioning of their economies and easy access of their people to modern and clean energy supplies (Ayoo 2020) . Economic, social, and human well-being depends on the production of goods which further depend on the availability of energy (Bompard et al. 2017) . It is a well-established fact that economic growth and well-being are closely correlated (Warr and Ayers 2010) . A plethora of energy challenges including high energy prices, uncertain energy supplies, environmental degradation, and inadequate supplies of energy sources are being faced by both developed and developing economies. Countries with high reliance on energy imports are vulnerable to risks and threats associated with energy supplies (Yergin 2006) . E7 countries, with their ever-increasing energy demand due to population growth and robust economic expansion, heavily depend on energy imports to reduce poverty and to uplift the well-being of their people. Therefore, economic security which is strongly correlated with energy security remains a challenge for E7 countries.

Thirdly, the study focuses on E7 countries (Brazil, China, Indonesia, India, Mexico, Turkey, and Russia), which according to Earth System Science Data (ESSD) (2020) emit approximately 45% of global CO 2 emissions. Four of the world's highest CO 2 emitter countries (China, India, Russia, and Indonesia) are part of this group. A high level of growth and the consequent high energy consumption in these economies cause a substantial increase in CO 2 emissions. Moreover, these countries are strong political powers, and they have political tensions as well. According to Global Risks Report (2021), E7 countries are among the most critical countries based on their socio-economic and geopolitical conditions. For instance, being the second largest economy and most populated country in the world, China has been an important political economy that might affect the whole world. Moreover, the China-USA trade war has been one of the prime reasons behind the geopolitical tensions between these countries that have led to global tensions worldwide. Further, border tensions between China and India exert pressure on both countries which in turn affect the social and economic life of consumers and producers of both countries. Brazil has disputes with Uruguay and Colombia on smuggling and immigration. Moreover, unstable governments and impeachments contribute to geopolitical instability in the case of Brazil. As mentioned earlier, India has a long history of border tensions with its neighbors such as China and Pakistan. Also, the world has witnessed several wars between India and its neighbors which have created spikes in geopolitical tensions. Further, following the USA and UK, India is the third country with the highest number of cyber-attacks in the last two decades. Likewise, Mexico, Turkey, and Russia have been facing several issues with the USA and a few other countries. E7 economies have border tensions with their neighbors, and they also have (geo)political instability that contributes to economic uncertainty. It is worth mentioning that, according to the Global Risks Report (2021), COVID-19 has been exerting a detrimental impact on the economies of E7 countries which have experienced even negative economic growth during the COVID-19 pandemic.

Moreover, due to lockdowns and other stringency measures, the energy sector has also witnessed a negative supply shock that has led to the high vulnerability of the energy sector.

Fourthly, we employ a comprehensive measure of environmental degradation, i.e., ecological footprint (hereafter EF) along with CO 2 emissions to have more robust and insightful conclusions. Fifthly, we have disaggregated energy consumption by source, NREC, and REC, to see their separate role in escalating environmental degradation in anticipation of GPR. Finally, to overcome the problem of heterogeneity and cross-sectional dependency, the present study uses the second generation of panel data methods. In addition to this, we also employ CIPS unit root tests, Westerlund cointegration test, and augmented mean group (AMG) estimator to render robust and consistent estimates in the existence of cross-sectional dependence and heterogeneity (Baloch and Wang 2019) .

Environmental pollution has been the core of empirical as well as theoretical discussion for many years until now. (Dahish and Recep 2020) .

Based on the GPR index presented by Caldara and Iacoviello (2018) , the role of GPR on energy consumption and environmental degradation has been explored by a few studies in recent years. In the case of Russia, Rasoulinezhad et al. (2020) tested the relationship between energy transition and GPR from 1993 to 2018. They detected a positive influence of GPR, CO 2 emissions, financial openness, and exchange rate on energy transition, whereas the economic growth, inflation rate, and population growth negatively affect the energy transition. Moreover, the relationship between economic growth, energy transition, CO 2 emissions, inflation rate, and population growth is negative in the short run. On the contrary, financial openness, GPR, and exchange rate accelerate the energy transition. Their results further revealed that in the short run, GPR is the main contributor to the energy transition. Recently, Alsagr and Hemmen (2021) explored the dynamic impact of GPR and financial development on REC during 1996-2015 in 19 emerging economies. The results of GMM revealed a positively significant influence of financial development on energy consumption. Similarly, in the case of the USA, Sweidan (2021) concluded that GPR has a statistically significant and positive effect on energy diffusion. It implies that GPR drives energy rather than depressing it. Adams et al. (2020) investigated the relationship between economic policy uncertainty and NREC for 10 resourcerich economies with a high level of GPR from 1996 to 2017 in the long run. The findings of Kao's test reveal a cointegration association among GPR, NREC, economic policy uncertainty, economic growth, and CO 2 emissions. Moreover, the PMG-ARDL results show that uncertainty, economic growth, and NREC contribute to CO2 emissions. This indicates that economic policy uncertainty has a detrimental impact on the environment. They found a significant relationship between uncertainty and emissions in the long run. Lastly, the results of the DH causality test show a oneway causal relationship running from CO 2 emissions to GPR and a two-way causal relationship among CO 2 emissions and NREC, economic growth and CO 2 emissions, and economic policy uncertainty and CO 2 emissions.

Likewise, Anser et al. (2021a) probe the effect of GPR on the EF in the case of BRMCC (Brazil, Russia, Mexico, China, Colombia) using AMG estimators. The study concludes that GPR mitigates environmental degradation. Zhao et al. (2021) examined the asymmetric impact of GPR on carbon emissions in the case of BRICS countries using the NARDL approach. The findings from the study reveal that the impact of GPR on carbon emissions is asymmetric, and it is heterogeneous across the BRICS countries. Anser et al. (2021b) estimated the impact of GPR, REC, NREC, economic growth, population, and economic growth on CO 2 emissions in BRICS countries. They employed the second-generation analysis and AMG estimator. The results indicate that GPR, GDP, population, and NREC escalate CO 2 emissions and REC reduces emissions in BRICS. It is worth mentioning that prior studies on the GPR-environment nexus either use CO 2 emissions or EF as a proxy for environmental degradation. Next, no study expounds on the renewable energy-environment and non-renewable energy-environment nexus amidst GPR. However, we employ both CO 2 emissions and EF as a proxy for the environment. Recently, Hashmi et al. (2021) use global emissions and GPR to explore the worldwide nexus between GPR and emissions. They note that GPR is a key determinants of global carbon emissions.

It is important to know that risk due to the COVID-19 pandemic has also affected both energy and the environment. For instance, Iqbal et al. (2021) revealed that the COVID-19 outbreak mitigates both NREC and carbon emissions. In the case of India, Aruga et al. (2020) conclude that lockdown amid the COVID-19 outbreak plunges NREC. Algamdi et al. (2021) find that the COVID-19 outbreak impedes oil prices. Additionally, Wang and Su (2020) reported that the COVID-19 outbreak decreases NREC and hence improved the environmental quality in China. In the case of India, Lokhandwala and Gautam (2020) conclude that the COVID-19 outbreak improved both air and water quality. So, it could be perceived that the risk associated with COVID-19 has a positive effect on energy security and environmental quality (Table 1) . 

In the literature of environmental economics, several empirical models have been developed to link the environment with the economy. It is worth noting that the EKC hypothesis has been regarded as the most critical theory of environmental economics that has been extensively tested in empirical studies. The EKC is an inverted U-shaped relationship between environment and income, and, in this analysis, we extend the EKC framework by including GPR and energy consumption:

In Eqs. (1) and (2), GDP and GDP 2 denote real GDP per capita and square of real GDP per capita, respectively. NREC and REC represent non-renewable energy consumption and renewable energy consumption, respectively. Further, GPRI is the geopolitical risk index. CO 2 is carbon dioxide emissions, whereas EF is the ecological footprint. These aforementioned variables (CO 2 and EF) are employed as an environmental degradation proxy. It is hypothesized that the magnitude of the coefficient of GDP and GDP 2 is > 0 and < 0, respectively. This means that EKC does exist, implying that, at the initial stages of economic growth, environmental degradation also increases and decreases as economic growth exceeds a certain point. Several recent studies use the EKC framework to explore the determinants of environmental degradation (see, for example, Destek and Sarkodie 2019; Haider et al. 2020 ). In addition to this, we further hypothesized that the coefficient of NREC and REC is > 0 and < 0, respectively. This indicates that non-renewable energy escalates environmental degradation, while renewable energy impedes it (see, for example, Anser el al. 2021c; Bhowmik et al. 2021; Ali et al. 2020; Gardiner and Hajek 2020). Next, it is hypothesized that the coefficient of GPRI is < 0, depicting that GPR plunges the environmental degradation (see, for example, Adams et al. 2020) . It is stated that this outcome is possible if the mitigating effect exceeds escalating effect.

The present study utilizes an annual panel dataset for E7 economies (Brazil, China, India, Indonesia, Mexico, Russia, and Turkey) over the period 1990-2015. The dependent variables are CO 2 emissions (measured in metric tons per capita) and ecological footprint (measured in Gha per person). On the other hand, independent variables are real GDP per capita (GDP), NREC, REC, and GPR index (GPRI). GPRI is established by Caldara and Iacoviello (2018) , which is calculated based on the frequency of the newspaper articles containing the words, for example, "geopolitics," "geopolitical risk," and "geopolitical (1) CO 2 = f (GDP, GDP 2 , NREC, REC, GPRI)

(2) EF = f (GDP, GDP 2 , NREC, REC, GPRI) tension. The summary of data is given in Table 10 in the Appendix. In addition, we employ several cross-sectional dependence tests, second-generation unit root tests, second-generation cointegration tests, and augmented mean group (AMG) estimator for robust analysis. Table 2 exhibits the descriptive statistics of study variables. The mean value of GDP is the highest, whereas it is the lowest for CO 2 emissions. Also, the standard deviation is the highest for EF, while it is the minimum for GPRI. Moreover, GPRI is positively skewed. while all other variables are negatively skewed. In addition to this, Jarque-Bera test statistics highlight that the selected dataset follows the non-normal distribution.

All variables are transformed into logarithmic form. (.) denotes P value. Further, ***, **, and * represent 1%, 5%, and 10% levels of significance, respectively.

To achieve its objective (i.e., probing the impact of GPR, NRE, and REN on the environment), in this section, the current study reports the results from second-generation panel data methods and AMG estimators coupled with the panel causality test. First, we report the results of the Breusch-Pagan LM test, the Pesaran LM test, and the Pesaran CD test in Table 3 .

The null hypothesis of all CD tests describes that there is no cross-sectional dependence (CD). The findings from CD tests reveal that at 1% level of significant, null hypothesis could be rejected, indicating that there exists CD in our case. This implies that shocks in one country can transmit to another country. Next, we test unit root in all selected variables to identify the order of integration. The results from the CIPS unit root test of Pesaran (2007) are given in Table 4 .

We fail to reject the null hypothesis of "there is no unit root at I (0)." However, at a 1% level of significance, we could reject the null hypothesis at I (1). This specifies that We employ ecological footprint (EF) and carbon dioxide emissions (CO 2 ) as a proxy for environmental degradation, hence applying Westerlund (2007) test two times. We do not fail to reject the null hypothesis, which indicates that there is no cointegration among the selected variables. Hence, we can conclude that there is an existence of cointegration among the selected variables used in the model.

Further, Westerlund (2007) test does not render long-run estimates (elasticities); therefore, we apply the AMG estimator to avail long-run estimates. The findings of the AMG estimator using CO 2 emissions as environmental degradations' proxy are reported in Table 6 .

In Table 6 , all reported variables are statistically significant. Further, the sign of GDP and GDP 2 is positive and negative, respectively. Therefore, we note the validity of EKC for E7 countries. This outcome is in line with the conclusion of Anser et al. (2021b) . Next, the value of NREC is 0.17, indicating that a 0.17% upsurge in carbon emissions is fostered by a 1% raise in NREC. Therefore, we conclude that NREC escalates emissions. This finding conforms with the results reached by Gardiner and Hajek (2020) . Additionally, the value of REC is − 0.09, implying that a 1% rise in REC plunges CO 2 emissions by 0.09%. This means that REC reduces CO 2 emissions in E7 countries (Alola et al. 2019 ). The coefficient of GPRI is − 0.08, indicating that a 0.08% decrease in CO 2 emissions is fostered by a 1% surge in GPRI. There are a few possible reasons behind the negative impact of GPRI on CO 2 emissions. First, high GPRI may discourage consumption and production, which sequentially impedes CO 2 emissions. Second, GPRI could affect energy prices, international trade, and tourism activities. These factors may constraint CO 2 emissions. Our findings are also backed by the study of Adams et al. (2020) and Anser et al. (2021a) who noted that GPR impedes environmental degradation. However, our findings are inconsistent with the conclusion of Anser et al. (2021b) who reported that GPR leads to higher carbon emissions.

Likewise, we use EF as a proxy for environmental degradation and scrutinize the impact of REC, NREC, and GPRI employing an AMG estimator. The estimates are reported in Table 7 . Table 7 depicts that all coefficients are statistically significant. Next, the GDP and GDP 2 coefficients are positive and negative, respectively. Thus, we validate the presence of EKC which is an inverse U-shaped relationship between income and environment. This outcome is supported by the conclusion of Destek et al. (2018) . Additionally, the value of NREC is 0.13, explaining that a 1% rise in NREC surges EF by 0.13%. This conclusion is in line with the conclusion reached by Destek and Sinha (2020) . On the contrary, the coefficient of REC is − 0.02 implying that a 0.02% decrease in EF is fostered by a 1% increase in REC. Additionally, the value of GPRI is − 0.10 inferring that a 1% upsurge in GPR impedes EF by 0.10%. As mentioned earlier, a decrease in production and consumption activities due to high GPR could be the possible reason behind low levels of EF. This result is supported by Adams et al. (2020) who argue that GPR plunges environmental degradation.

Finally, we employ the DH causality test to examine the direction of causality. The findings of the DH test are reported in Tables 8-9 .

As can be seen from Table 8 , there exists one-way causality running from GDP to carbon emissions. Next, one-way causality is also running from GPRI to CO 2 emissions. Likewise, one-way causality is running from CO 2 emissions to NREC, from GDP to NREC, from REC to GDP, from REC to GPRI, and from NREC energy to REC.

According to Table 9 , there exists unidirectional causality running from NREC to GDP, from REC to GDP, from NREC to GPRI, from GPRI to EF, from NREC to EF, and 

We first scrutinize the CD in the selected set of panel data, since it is essential for reliable results. The outcomes from these approaches confirm the null hypothesis rejection at a 1% significance level; therefore, variables endure CD. That means EF, CO 2 , GDP, NREC, REC, and GPRI shocks in one country are also correlated with other countries. In this way, due to interdependency between countries, economic shocks have spillover effects via trade channels (Bello et al. 2018 Westerlund (2007) cointegration test illustrates that all variables in the current study are cointegrated (which proposes that there is an effective long-term connection among EF, CO 2 , GDP, NREC, REC, GPRI in E7 countries). The findings are in line with the results of Sharma et al. (2021) for eight developing countries of Asia, Sharif et al. (2019) for 74 nations, Le and Bao (2020) for 16 developing economies, Shafiei and Salim (2014) for OECD economies, and Zafar et al. (2019) for emerging economies. The longrun estimates from AMG show that NREC significantly promotes environmental degradation in E7 countries. The use of NREC exerts pressure on natural resources exploitations, and NREC emits higher carbon gas. As a result, environmental degradation occurs at a higher pace. The use of NREC still dominates in E7 countries; therefore, environmental degradation has been increasing over time. The results expound that a 1% raise in NREC fostered the emissions by 17%. In the empirical literature, there is a predictable consent on the adverse environmental effect of NREC based on fossil fuel. Some respective studies including Gorus and Aydin (2019) for MENA countries; Nathaniel and Khan (2020) On the other hand, results depict that REC contributes significantly to environmental improvements in E7 countries. That is, a 1% rise in REC tends to reduce CO 2 emissions by 9%. Renewables in the form of wind energy, hydropower energy, and solar energy, etc. do not emit greenhouse gases (e.g., CO2). Further, renewables do not exploit and deplete the natural resources and hence environmental degradation plunges. Since E7 countries are among the top countries that are shifting from NREC to REC, hence, they are at the right part by escalating the REC to achieve sustainable development. These findings are parallel with the conclusions attained by Al-Mulali and Ozturk (2015) for 23 selected European countries, Nathaniel and Khan (2020) for ASEAN countries, Sharif et al. (2019) for 74 nations, and Dogan and Aslan (2017) for EU countries. In contrast, our findings are inconsistent with the conclusions of Mehdi and Slim (2017) who report findings opposite to our conclusion for North African countries.

Furthermore, the results also indicate that a 1% hike in GPRI tends to reduce CO 2 emissions by 8%. GPRI adversely affects NREC and economic growth, which results in a decline in CO 2 emissions. Also, GPRI affects economies through international trade, equity market, production and consumption, energy prices, military tensions, and war and terrorism. Further, GPRI is the main determinant of AMG estimator indicates that a 1% rise in NREC will escalate EF by 13%, whereas a 1% rise in REC will lessen the EF by 2%. This argument is compatible with the conclusions reached by Destek and Sinha (2020) in the case of 24 OECD nations and Sharif et al. (2020) for Turkey. The impact of REC is significant and negative on the EF. This describes the clean role of REC in depleting the EF. The findings also expound that E7 economies are on the right track towards achieving the goal of development through the incorporation and progression of environmentally friendly advances. This is equivalent to the conclusion of Danish et al. (2020) for BRICS economies, Destek and Sinha (2020) for 24 OECD nations, Wang and Dong (2019) for 14 SSA countries, and Destek et al. (2018) for EU economies. A 1% rise in GPRI hinders EF by 10%. As mentioned above, it is because of a decrease in production and consumption activities due to high GPRI. Also, GPRI creates uncertainty, which drives firms to put their tentative plans on hold and decrease current production to their limited capacity in anticipation to lower consumption. As GPRI has become the main indicator in economic and business cycles, significant players of economic activities including bankers, industrialists, and market traders accept that GPRI changes the element of the capital market and impedes the dynamics of investment (Caldara and Iacoviello 2018) . Moreover, due to the negative and positive signs of GDP and GDP 2 , the current study validates the EKC for E7 countries. The other studies that confirm the existence of EKC include Al-Mulali and Ozturk (2016) for 27 advanced economies, Bilgili et al. (2016) for OECD nations, and Bölük and Mert (2015) for Turkey. In contrast, Al-Mulali and Ozturk (2015) in the case of 23 European economies do not support the presence of EKC.

The findings from the DH causality test highlight that there exists one-way causality running from GPRI to EF and from GPRI to CO 2 emissions. This implies that GPR affects environmental degradation, but environmental degradation does not affect GPR in the selected countries. That is, environmental degradation is not one of the reasons behind geopolitical tensions, but GPR alters environmental degradation. Next, there exists one-way causality running from NREC to economic growth, indicating that non-renewables contribute to economic growth. However, economic growth does not affect NREC. Thus, the current study validates the growth hypothesis. Likewise, regarding the nexus between REC and economic growth, we also find the existence of a growth hypothesis. Hence, it could be concluded that E7 countries depend on energy consumption, and any action to conserve energy will affect economic growth.

The threat due to global warming and environmental degradation calls for investigating the socio-economic factors that drive these critical issues (i.e., global warming and environmental degradation). In the prior literature, economic growth and NREC have widely been probed as drivers of environmental degradation; however, there is a dearth of literature on the geopolitical risk-environment nexus. In addition, the limited literature on geopolitical risk-environment nexus has a contrasting conclusion that calls for further exploration of this line of research. Hence, this study probes the impact of GPR on environmental degradation, controlling the effects of economic growth, NREC, and REC in the case of E7 countries. This study contributes to the existing literature by using carbon emissions and EF as proxies for the environment in the case of E7 countries that provide robust findings. In addition, this study employs several second-generation panel data methods, AMG estimators, and DH causality tests for robust and reliable findings.

The empirical evidence shows that the data set has crosssectional dependence revealing spillover effects of macroeconomic shocks occurring in any of the countries. All variables are cointegrated which suggests that there exists an effective long-term connection among all the considered variables in the case of E7 countries. The long-run empirical estimates from AMG estimator show that there is a significant impact of NREC on environmental degradation; however, REC contributes to environmental improvements. This provides a solid argument that escalating REC helps decrease CO 2 emissions. Secondly, results also depict that if GPR increases, it will reduce CO 2 emissions. On the contrary, using EF as a proxy for environmental degradation, we report that NREC escalates EF and REC lessens the EF. Furthermore, results also depict that rise in GPR will tend to impede EF. The present study also confirms the presence of EKC for E7 countries. Findings from the causality test imply that GPR affects environmental degradation, but environmental degradation does not lead to geopolitical risk.

Moreover, we report the validity of the growth hypothesis (in the case of both renewable and non-renewable energy consumption) which is one-way causality running from NREC to economic growth.

The results suggest that to guarantee sustainable growth, E7 countries should invest in clean energies since global warming is becoming a more serious problem worldwide. Next, investment in REC is more proficient to limit CO 2 emissions. Different sectors must be urged to adopt innovation that limits contaminations, and it will also help them to lessen their dependency on energy as well as to stimulate the energy security of countries that import energy. Furthermore, governments should provide subsidies on the import of renewable energy productions, as they ameliorate the environmental quality. There should be special research grants for renewable energy development. On the contrary, the government should impose high trade barriers on the import of non-renewable energy. Also, programs and schemes should be initiated to make people aware of the adverse effects of non-renewable energy use. Moreover, E7 countries are on the right track, as the findings from the EKC hypothesis suggest that high real income (above a threshold) leads to improved environmental quality. Further, we report that if governments try to reduce GPR, environmental degradation increases. Therefore, policymakers should keep in mind the environmental impacts of reducing GPR. In addition to this, if policymakers aim to reduce GPR and environmental degradation simultaneously, they should explore the other factors (e.g., renewables) that impede environmental degradation without affecting GPR. Moreover, policymakers should devise policies to encourage R&D investment, technological advancement, and green energy investment because these factors might curb environmental degradation without causing a surge in GPR. Additionally, at the time of low GPR, government officials and/or policymakers should divert their attention towards environmental degradation because low GPR leads to higher energy consumption and economic growth, which in turn deteriorate the environment. Apart from this, keeping in view the inverse relationship between GPR and the environment, higher environmental taxes should be imposed at times of high GPR and vice versa.

Regarding the limitations of this study, we analyze the emerging countries; so, this study does not propose any policy suggestions for developed countries. Next, the present study does not explain the country-wise findings on the relationship between GPRI and the environment. Regarding future research directions, researchers can explore the nexus between GPR and the environment in the case of developed countries. In terms of methodology, the non-linear or asymmetric impact of GPR on the environment could be examined. The direct and indirect impact of GPR on the environment can also be probed. Furthermore, structured machine learning panel data regression models can be used for future prediction to test the hypothesis related to GPR, carbon emissions, and environmental degradation. 

Ethics approval Not applicable.

Consent for publication Not applicable.

The authors declare no competing interests. 

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Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: evidence from panel models robust to heterogeneity and cross-sectional dependence

Analyzing the impacts of geopolitical risk and economic uncertainty on natural resources rents

The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries

Interactions among energy consumption, CO2, and economic development in European Union countries

The relationship between energy consumption, economic growth, and CO2 emission in MENA countries: causality analysis in the frequency domain

The effect of renewable energy consumption on economic stability: panel data analysis on selected countries

Impact of agricultural land use and economic growth on nitrous oxide emissions: evidence from developed and developing countries

Carbon emissions across the spectrum of renewable and nonrenewable energy use in developing economies of

Investigating the Environmental Kuznets Curve hypothesis amidst geopolitical risk: Global evidence using bootstrap ARDL approach

The role of renewable versus nonrenewable energy to the level of CO2 emissions a panel analysis of sub-Saharan Africa's Βig 10 electricity generators

It is time to control the worst: testing COVID-19 outbreak, energy consumption and CO 2 emission

Do Asian emerging stock markets react to international economic policy uncertainty and geopolitical risk alike? A quantile regression approach

Renewable and nonrenewable energy consumption, government expenditure, institution quality, financial development, trade openness, and sustainable development in Latin America and Caribbean emerging market and developing economies

Indirect impact of COVID-19 on environment: a brief study in Indian context

The role of renewable energy and agriculture in reducing CO2 emissions: evidence for North Africa countries

Rule of law and CO2 emissions: a comparative analysis across 65 belt and road initiative (BRI) countries

Carbon dioxide abatement in Africa: the role of renewable and non-renewable energy consumption

The nexus between urbanization, renewable energy, trade, and ecological footprint in ASEAN countries

Crude oil production in the Persian Gulf amidst geopolitical risk, cost of damage and resources rents: is there asymmetric inference?

A simple panel unit root test in the presence of cross-section dependence

Asymmetric effects of geopolitical risks on energy returns and volatility under different market conditions

Geopolitical risk and energy transition in Russia: evidence from ARDL bounds testing method

Renewable energy, nuclear energy, and environmental pollution: accounting for political institutional quality in South Africa

Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: a comparative analysis

Economic growth and environmental degradation in Vietnam: is the environmental Kuznets curve a complete picture?

The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: a global study with the application of heterogeneous panel estimations

Revisiting the role of renewable and non-renewable energy consumption on Turkey's ecological footprint: evidence from quantile ARDL approach. Sustainable Cities and Society, 102138. Renewable energy consumption reduce ecological footprint? Evidence from eight developing countries of Asia

Does renewable energy consumption reduce ecological footprint? Evidence from eight developing countries of Asia

Impact of corruption in public sector on environmental quality: implications for sustainability in BRICS and next 11 countries

Exploring the relationship between energy usage segregation and environmental degradation in N-11 countries

The geopolitical risk effect on the US renewable energy deployment

Impact of economic policy uncertainty on CO2 emissions in the US: evidence from bootstrap ARDL approach

Does geopolitical risk mitigate inbound tourism? Evidence from panel quantile regression

The asymmetric causal relationship between renewable and non-renewable energy consumption and economic growth in the ASEAN-5 countries

What drives environmental degradation? Evidence from 14 Sub-Saharan African countries

A preliminary assessment of the impact of COVID-19 on environment-a case study of China

Evidence of causality between the quantity and quality of energy consumption and economic growth

Testing for error correction in panel data

Ensuring energy security

The nexus of renewable and nonrenewable energy consumption, trade openness, and CO2 emissions in the framework of EKC: evidence from emerging economies

Energy, CO2 emissions, and value added flows embodied in the international trade of the BRICS group: a comprehensive assessment

Geopolitical risks, energy consumption, and CO 2 emissions in BRICS: an asymmetric analysis