Oil rents, economic growth, and CO2 emissions in 13 OPEC member economies: Asymmetry analyses

Oil rents significantly contribute to income in OPEC member economies and could have environmental consequences. The present study explores the asymmetrical effects of oil rents on CO₂ emissions in 13 current OPEC economies using a period 1970–2019, and also tests the Environmental Kuznets Curve (EKC) hypothesis. Long-run results show that economic growth has a positive effect, and its square term has a negative effect on CO₂ emissions in Algeria, Congo, Gabon, Kuwait, and Saudi Arabia, which validate the EKC in these countries. However, a U-shaped effect of income growth on emissions is substantiated in Angola. Moreover, rising oil rents have positive effects on CO₂ emissions in Saudi Arabia, Angola, Congo, Equatorial Guinea, Iran, Iraq, Kuwait, and Libya, and have negative impacts in Algeria, Nigeria, and the UAE. Decreasing oil rents reduce CO₂ emissions in Angola, Equatorial Guinea, Libya, and Saudi Arabia, and increase emissions in Algeria. Moreover, asymmetrical effects of oil rents on emissions are found in Angola, Congo, Iran, Iraq, Kuwait, Nigeria, Equatorial Guinea, Saudi Arabia, and the UAE. The short-run results show that the EKC is validated in Algeria, Congo, and Libya. However, economic growth shows a monotonic positive impact on emissions in Nigeria, the UAE, and Venezuela. Increasing oil rents show a positive impact on emissions in Angola, Congo, Iran, and Kuwait and carry a negative impact in Algeria and the UAE. In addition, decreasing oil rents increase CO₂ emissions in Algeria, Gabon, Nigeria, and Saudi Arabia. We recommend Angola, Congo, Equatorial Guinea, Iran, Iraq, Kuwait, Libya, and Saudi Arabia to adopt tight environmental policies in times of increasing oil rents to avoid the negative environmental consequences of oil rents.

Introduction

Oil rents are the major source of income in oil-abundant OPEC economies and would have a scale effect in the oil-income-dependent OPEC economies. Consequently, oil rents would be responsible for greater energy consumption and pollution emissions. On the production side, oil production was responsible for 10.3 g of emissions on average from each megajoule of crude, which generated 1.7 gigatons of carbon dioxide in 2015 worldwide (Garthwaite, 2018). In 2020, on average, 13 OPEC economies emitted 2.73 oil emissions tCO₂ per person and 7.16 territorial emissions tCO₂ per person compared to the global average of 2.57 oil emissions tCO₂ per person and 5.18 territorial emissions tCO₂ per person, respectively. Thus, OPEC economies are emitting greater average CO₂ emissions per capita compared to the global average. In total emissions, OPEC economies are emitting 6.36% of global CO₂ emissions (Global Carbon Atlas, 2022). Globally, more than 50% of CO₂ emissions are from oil emissions and OPEC economies are highly dependent on the oil sector. For instance, as per data for 2021, the oil exports were 54.9% of total exports in OPEC. Moreover, OPEC carried 37.8% of world crude oil production and 33.2% of world petroleum exports (OPEC, 2021). Moreover, the oil rents were observed at 24.62% of Gross Domestic Product (GDP) on average in 13 OPEC economies during 1970–2019. However, the oil rents are not very smooth and have spikes due to the many international events.

Figure 1 reports the trends of oil rents percentage of GDP. A great fluctuation in oil rents was observed due to an oil price hike of 300% from October 1973 to March 1974 because of putting an embargo by OPEC on selected countries (Office of the Historian, 2022). After some declines, oil price got more than doubled in 1979. Later, oil prices and rents mostly declined till 1982 and fluctuated with ups and downs movements during 1982–1990. However, oil prices again got double in 1990 due to Iraq-Kuwait tension. The decade of the 2000s also faced a lot of fluctuations, and oil prices got their peak in July 2008. Afterward, oil prices declined sharply till December 2008 (Hamilton, 2009) and oil prices showed great fluctuations from 70$ to 120$ till November 2014. During 2014–2016, oil prices faced a deep decline due to a growing supply glut. During 2016–2019, oil prices started stabilizing but fetch up in a problem of COVID-19 due to a downturn in oil demand globally (OPEC, 2021). Figure 1 explains the story of the oil crisis and oil rents. All the OPEC economies have moved almost in the same directions and these fluctuations could have a deep impact on the economy and environment of the OPEC economies. For instance, the economic growth rate of OPEC economies was -5.2% in 2020 due to COVID-19 compared to the world’s average of -3.3% (OPEC, 2021).

FIGURE 1

FIGURE 1. Trends of oil rents percentage of GDP during 1970–2019.

Oil rents may support the economic growth of oil-abundant economies. However, overdependence on natural resources may obstruct the development of other sectors, which is called Dutch Disease (Corden and Neary, 1982). Dutch Disease explains that increasing exports of the natural resource sector would appreciate the currency and exports of other sectors will become expensive consequently, which may reduce exports from other sectors. Moreover, the growth of the oil sector would decrease the concentration of a nation on other sectors as well. In addition, the natural resource curse hypothesis explains that the presence of natural resources would have political problems in a country. Hence, excessive dependence on natural resources would obstruct the process of economic growth (Auty, 1993). The natural resource curse can be termed an oil curse in the oil-abundant economies of the OPEC cartel. Excessive dependence on oil sources would hinder many economic, social, and political indicators, which would reduce the process of development (Shao and Yang, 2014). On the other hand, Sachs (2007) claimed that the oil curse phenomenon is partially true, and it can happen in an economy if oil earnings are utilized for consumption purposes instead of investment purposes. It was suggested to invest the oil earnings in the growth of non-oil exports to avoid the Dutch Disease phenomenon. A vast literature has studied the impact of natural resources on economic growth and other macroeconomic indicators (Sachs and Warner, 1995; Dietz et al., 2007; Daniele, 2011; Bhattacharyya and Hodler, 2014; Cockx and Francken, 2016).

On the environmental side, many studies have investigated and corroborated the positive impact of natural resource rents on ecological or carbon footprint (Hassan et al., 2019; Nathaniel et al., 2021; Jahanger et al., 2022) and CO₂ emissions (Bekun et al., 2019; Adediyan et al., 2020; Joshua and Bekun, 2020; Khan et al., 2020; Nwani and Adams, 2021; Onifade et al., 2021; Shen et al., 2021; Huang and Guo, 2022). Alternatively, some studies also reported the negative effect of natural resource rents on the ecological footprint (Danish and Khan, 2020; Ulucak and Khan, 2020) and CO₂ emissions (Balsalobre-Lorente et al., 2018; Kongbuamai et al., 2020). Thus, resource rents do not have the same effect on the environment in different economies. In the same way, the exact effect of oil rents on emissions is an empirical question, which is a target of this present study to investigate in OPEC economies. Mogaddam (2022) argued that the oil sector from well to tank is highly responsible for CO₂ emissions. However, the test of oil rents on pollution emissions is scant in the present state of literature. Doing spatial analysis, Mahmood and Furqan (2021) explored the role of oil rents on GHGs emissions in six GCC countries. Still, comprehensive research is missing in the maximum sample of OPEC economies. Thus, the present study contributes to OPEC environmental literature by investigating the effects of oil rents on CO₂ emissions in all current OPEC members. In addition, this relationship is tested in an asymmetry setting to enhance the contribution of this study, as the literature suggested investigating this issue in asymmetrical analyses (Mahmood et al., 2020; Alvarado et al., 2021).

Literature review

Resource rents could play a significant role in resource-abundant OPEC economies and may support the economic growth of economies through generating income and employment (Sinha and Sengupta, 2019). Moreover, resource rents may also improve environmental quality if they could reduce the reliance on fossil fuel consumption (Balsalobre-Lorente et al., 2018). In oil-abundant economies, oil rents may generate the technique effect, if oil rents could invest in producing energy-efficient and clean energy technologies. Consequently, energy efficiency could help in the promotion of environmental sustainability (Alam M. S. et al., 2022a; Murshed et al., 2022a; Khan et al., 2022). Moreover, oil rents may also be utilized for economic diversification from the oil sector, which may generate a composition effect. Thus, oil rents would help in shaping the EKC hypothesis by promoting technique and/or composition effects in oil-abundant economies. There is limited empirical environmental literature on oil rents. However, a vast literature has examined the relationship between natural resource rents and pollution emissions.

At first, we discuss the literature corroborating the pleasant environmental effects of natural resource rents. For instance, Balsalobre-Lorente et al. (2018) confirmed a negative relationship between natural resources and CO₂ emissions in 5 EU economies from 1995 to 2016. In the same way, Kongbuamai et al. (2020) confirmed this relationship in the case of ASEAN from 1995 to 2016. Moreover, Shittu et al. (2021) corroborated a negative effect of resource rents on the ecological footprint in forty-five Asian economies from 1990 to 2018 and also confirmed a U-shaped relationship between ecological footprint and growth. In addition, a negative impact of resource rents on ecological footprint was confirmed by Danish and Khan. (2020) and Ulucak and Khan (2020) in BRICS economies and by Zafar et al. (2019) in the case of the United States. On the other hand, some studies explored the coal rents and pollution emissions nexus in BRICS countries. For instance, Adedoyin et al. (2020) explored the BRICS economies from 1990 to 2014 and found that coal rents and renewable energy reduced carbon emissions. However, carbon damage costs had a positive effect on CO₂ emissions.

Natural resource rents may also have environmental damages. For instance, Harbaugh et al. (2002) argued in the EKC theory that natural resources could be exploited in the early stage of growth and could pollute the economy. For instance, economic growth might accelerate industrialization, which could be responsible for natural resource exploitation and ecological problems (Kwakwa et al., 2020). Moreover, Badeeb et al. (2020) argued that natural resource abundance might promote a positive association between emissions and growth in the first stage of the EKC. In addition, it would reduce the strength of the negative relationship in the second stage of the EKC in resource-abundant economies. Thus, the natural resource abundance economies have a lesser chance to achieve the second phase of the EKC with increasing economic growth. Furthermore, using old technology in natural resource extraction might damage the environment (Shuai and Zhongying, 2009). In another argument, the natural resource would restrict human capital development and could reduce the chance of progress in technology (Gylfason, 2001). However, good-quality institutions might reduce the bad environmental consequences of natural resources (Tiba and Frikha, 2019).

In the empirical work, Jahanger et al. (2022) investigated 73 developing countries from 1990 to 2016. Natural resources and financial development raised, and innovation reduced the ecological footprint. Ulucak et al. (2020) explored the OECD countries from 1980 to 2016. Natural resources rents increased both carbon footprint and CO₂ emissions. Thus, natural resource extraction might be a threat to environmental sustainability. Moreover, renewable energy reduced and non-renewable increased ecological and carbon footprint. In the same way, Murshed et al. (2022b) corroborated the negative effect of renewable energy on carbon and ecological footprint in South Asia. Onifade et al. (2021) investigated the E7 economies from 1990 to 2016 and found that resource rents, income, and urbanization accelerated CO₂ emissions and ecological footprint. However, globalization reduced environmental degradation. Hussain et al. (2020) investigated 56 Belt and Road Initiative (BRI) economies from 1990 to 2014 and found that natural resource depletion accelerated energy usage and CO₂ emissions. Moreover, they found the feedback effects in the causality analyses of all investigated variables. In the same way, Khan et al. (2020) investigated 51 BRI countries from 1990 to 2016 and found that natural resources had positive effects on CO₂ emissions and energy consumption.

Baloch et al. (2019) investigated BRICS economies from 1990 to 2015 and found a positive impact of natural resources in South Africa, a negative effect in Russia, and insignificant effects on the ecological footprint in the rest of the 3 BRICS economies. The EKC hypothesis was also validated. Nathaniel et al. (2021) investigated BRICS economies and found that natural resources and income growth enhanced the ecological footprint. Ibrahim and Ajide (2021) explored BRICS economies from 1996 to 2018. Coal and fuel production and consumption and gas production increased carbon emissions. However, gas consumption reduced emissions. Moreover, resource rents, financial markets, and regulatory quality increased emissions. In the same way, Alam N. et al. (2022b) found that financial development increased carbon footprint and low-carbon energy resources reduced the carbon footprint. Moreover, Murshed et al. (2022c) found that financial inclusion reduced carbon productivity.

Nwani and Adams (2021) investigated 93 countries from 1995 to 2017. Natural resource rents, economic growth, and imports increased consumption and production-based carbon emissions in countries with low-quality governance and decreased production-based emissions in countries with high-quality governance. Tiba and Frikha (2019) investigated 26 African economies from 1990 to 2016 and corroborated the EKC hypothesis and resource curve hypothesis. Thus, natural resources degraded the environment. Moreover, Byakagaba et al. (2019) found that the exploration of oil and gas in Uganda developed social ills and environmental degradation. Adediyan et al. (2020) investigated Nigeria from 1986 to 2018 and found that resource rents had a positive effect on CO₂ emissions. Kwakwa et al. (2020) investigated Ghana from 1971 to 2013 and found that growth, urbanization, and natural resource extraction had positive effects on carbon emissions. However, trade openness and foreign aid helped to reduce emissions. Alam (2022) investigated and also found that trade helped reduce CO₂ emissions in Oman during 1980–2020. Moreover, Joshua and Bekun (2020) investigated South Africa from 1970 to 2017 and found that total natural resources rents showed a significant contribution to pollutant emissions.

Shen et al. (2021) examined 30 provinces of China from 1995 to 2017. Energy consumption, natural resources rents, and financial development increased emissions, while green investment reduced CO₂ emissions. In the same sample of provinces in China, Huang and Guo (2022) shared the same findings. Bekun et al. (2019) probed 16 EU countries from 1996 to 2014. Natural resource rents, nonrenewable, and income increased, and renewable energy reduced emissions. Wang et al. (2020) investigated G7 from 1996 to 2017 and found a positive effect of natural resources on CO₂ emissions. Nevertheless, the agriculture sector reduced emissions. Alvarado et al. (2021) suggested applying asymmetrical analyses to 17 Latin American economies and corroborated the asymmetrical effect of resource rents on the ecological footprint in quantile regression analyses using a period 1980–2016.

In the single country analysis, Shahbaz et al. (2020) investigated the United States from 1976 to 2016 and found that natural resources degraded the environment. However, education reduced carbon emissions. Hassan et al. (2019) examined Pakistan from 1970 to 2014 and found that resource rents increased the ecological footprint. Besides, the EKC hypothesis was validated. However, biocapacity and human capital could not affect the environment. Loganathan et al. (2020) investigated Malaysia from 1970 to 2018 and found a mix of the increasing and decreasing impact of natural resources on CO₂ emissions in different quantile of regression analyses and could not validate the EKC.

Some studies are conducted specifically for the OPEC economies. For instance, Liski and Tahvonen (2004) argued that due to the cartel of OPEC, pollution tax generated greater rents than the damage cost of pollution. Hence, the net welfare effect was positive for OPEC economies. Agboola et al. (2021) investigated Saudi Arabia from 1971 to 2016 and found that energy usage, resource rents, and income increased CO₂ emissions. However, oil rents reduced CO₂ emissions. Alfalih and Hadj (2022) investigated Saudi Arabia from 1985 to 2017 and found that financialization and natural resources rents improved environmental sustainability. Shehzad et al. (2022) corroborated that resource rents improved the environment and globalization degraded the environment in Algeria. Moreover, an N-shaped EKC was found between economic growth and ecological footprint. Ignoring resource rents, Saboori et al. (2016) investigated OPEC from 1977 to 2008 and corroborated the EKC hypothesis in 6 out of 10 investigated OPEC economies.

Benchekroun et al. (2020) investigated the cartel-fringe model and found that OPEC market power was a source of welfare loss net to climate change. Moreover, rising non-OPEC oil reserves decreased global welfare. Mahmood (2022) investigated the GCC countries from 1975 to 2019 and found that increasing oil and gas consumption increased emissions in the GCC region. However, declining oil consumption showed positive environmental effects in 4 out of 6 GCC economies, and decreasing gas consumption had similar effects in 3 out of 6 GCC countries. Interestingly, oil showed a larger effect than gas consumption. Moreover, the EKC was confirmed in two economies. Dong and Whalley (2012) investigated and found that the carbon taxes by large importers of oil, i.e., the US, the EU, and China, reduced the welfare of OPEC and increased the welfare of non-OPEC economies. However, these taxes reduced global emissions marginally. Moutinho et al. (2020) examined the 12 OPEC nations from 1992 to 2015 and found a U-shaped relationship between income and emissions. Moreover, energy usage increased, and trade decreased emissions. Moutinho and Madaleno (2022) tested the EKC in sectoral analyses of 9 OPEC economies from 1974 to 2016. The EKC was validated in extractive and manufacturing industries and commerce-related activities. Moreover, a U-shaped relationship was found in other analyzed sectors.

Some literature specifically investigated the relationships between the oil sector and the environment. For instance, Merrill and Orlando (2020) found that increasing political violence increased oil production, which accelerated carbon emissions in the MENA region. Ouédraogo et al. (2021) investigated African countries from 1980 to 2014. Oil resources increased CO₂ emissions in Angola and decreased CO₂ emissions in 4 African economies. Moreover, they found the EKC in Cameroon, Côte d’Ivoire, and Nigeria. However, a U-shaped relationship was found in Algeria and Morocco. Ozturk (2017) investigated Latin America from 1975 to 2013 and verified the negative effect of oil rents on emissions. Badeeb et al. (2016) found a positive effect of oil rents on commercial activity, which would increase energy demand and pollution. Liu et al. (2022) examined the role of resources’ commodity price volatility in G7 economies from 1990 to 2020 and found that price volatility and economic growth accelerated carbon emissions. However, oil rents helped to reduce emissions. Mahmood and Furqan (2021) investigated oil rents and GHGs emissions relationship in GCC economies from 1980 to 2014 and confirmed the EKC. Moreover, oil rents had a positive impact on CO₂ emissions and a U-shaped effect on N₂O emissions. He et al. (2022) investigated China from 1971 to 2018 and found that oil rents and renewable energy reduced GHGs emissions. However, economic growth and natural resources increased GHGs emissions. Zhang et al. (2021) investigated 41 African countries from 1996 to 2018 and found that oil, gas, and coal consumption and their rents deteriorated the environmental quality. Moreover, technology through imports of goods and services helped to support environmental quality.

The reviewed literature discusses the relationship between natural resource rents and emissions. However, the studies on the oil rents and pollution emissions are limited and no study has conducted this analysis on all current members of OPEC. Hence, the present study contributes to this literature gap by inquiring about the oil rents-emissions nexus in asymmetrical analyses.

Methodology

Economic growth may be considered a major determinant of pollution emissions. Grossman and Krueger (1991) did a pioneer study finding a nonlinear impact of economic growth on pollution emissions, which is called the EKC hypothesis. In its first phase, a scale effect of economic growth demands more energy and is responsible for environmental degradation. Later, economic growth would create pleasant environmental effects through technique and/or composition effects by demanding a better environment to improve the standard of living (Grossman and Krueger, 1995). Resource rents would shape the EKC in natural resource-abundant economies (Harbaugh et al., 2002; Baloch et al., 2019; Tiba and Frikha, 2019; Badeeb et al., 2020). Particularly, oil rents carry a significant share in the GDP of each OPEC economy and would play a significant role in shaping the EKC. For instance, oil rents can be utilized for diversification policy from the oil sector and may also be utilized to develop clean technologies and energy sources. Hence, these both efforts would generate the technique and composition effects in the economy and may shift the economy from the first stage to the second stage of the EKC. Thus, the present study hypothesizes the effect of oil rents on CO₂ emissions, while testing the EKC hypothesis in OPEC economies, in the following way:

${\mathrm{C}\mathrm{O}}_t=f\left({\mathrm{Y}}_t,Y_t^2,{\mathrm{O}\mathrm{R}}_t\right)(1)$

CO_t represents the natural log of tCO₂ emissions per person, which is taken from the Global Carbon Atlas (2022). Y_t is the natural log of per head GDP in constant USD and Y_t² is a square of Y_t. OR_t is the natural log of oil rents percentage of GDP. The annual series of Y_t and OR_t are sourced from World Bank (2022). Data is taken for the UAE and Congo from 1975 to 2019, Angola and Equatorial Guinea from 1980 to 2019, Libya from 1990 to 2019, Venezuela from 1970 to 2014, and Algeria, Gabon, Iran, Iraq, Kuwait, Nigeria, and Saudi Arabia from 1970 to 2019, as the availability of data for targeted variables. Alvarado et al. (2021) suggested applying asymmetrical analyses to the relationship between resource rents and ecological footprint. In the same way, oil rents could have asymmetrical effects on CO₂ emissions. Because increasing oil rents may increase income and pollution emissions through the consumption of pollution-oriented products for a demand for a higher standard of living. However, it is not necessary that consumption of such products will decrease emissions with a decrease in income. For instance, the Ratchet effect theory explains that to sustain such a standard of living of consumption patterns (Duesenberry, 1951), the demand for such products might not decrease with decreasing income. Hence, it is not necessary to have an equal impact of both rising and falling oil rents on emissions. Therefore, we split OR_t into positive and negative series using Shin et al. (2014):

${\mathrm{O}\mathrm{R}\mathrm{P}}_t={\sum }_{j=1}^t{OR}_j^{+}={\sum }_{j=1}^t\max \left(∆{OR}_j,0\right)(2)$

${\mathrm{O}\mathrm{R}\mathrm{N}}_t={\sum }_{j=1}^t{OR}_j^{-}={\sum }_{j=1}^t\min \left(∆{OR}_j,0\right)(3)$

ORP_t is a partial sum of positive change in OR_t in Eq. 2 and ORN_t is a partial sum of negative change in OR_t in Eq. 3. Now, the nonlinear model is as follows:

${\mathrm{C}\mathrm{O}}_t=f\left({\mathrm{Y}}_t,Y_t^2,{\mathrm{O}\mathrm{R}\mathrm{P}}_t,{\mathrm{O}\mathrm{R}\mathrm{N}}_t\right)(4)$

Our purpose is to apply Eq. 4 to all targeted OPEC economies to verify an asymmetrical effect of oil rents on emissions and to verify the existence of the EKC hypothesis in each individual country. Before moving towards long-run analyses, we apply Ng and Perron’s (2001) methodology checking an order of integration in a model of each country. We use only MZa statistics out of 4 statistics of Ng and Perron (2001), because of the large number of series in the models of 13 countries. The test statistic is as follows:

${MZ}_a=\raisebox{1ex}{$\left[\raisebox{1ex}{${\left(y_T^d\right)}^2$}\!\left/ \!\raisebox{-1ex}{$T$}\right.-{\sum }_{j=-T+1}^{T-1}\varnothing \left(j\right).k\left(\frac{j}{l}\right)\right]$}\!\left/ \!\raisebox{-1ex}{$2\left[\raisebox{1ex}{${\left(y_T^d\right)}^2$}\!\left/ \!\raisebox{-1ex}{${\left(T\right)}^2$}\right.\right]$}\right.(5)$

After checking the unit root, we will apply the Autoregressive Distributive Lag (ARDL) of Pesaran et al. (2001) to Eq. 4:

$\begin{array}{ll}\hfill {∆\mathrm{C}\mathrm{O}}_t& =a_0+a_1{CO}_{t-1}+a_2{Y}_{t-1}+a_3{Y}_{t-1}^2+a_4{ORP}_{t-1}+a_5{ORN}_{t-1}\hfill \\ \hfill & +{\sum }_{i=1}^{l-1}{b}_{1i}{\Delta CO}_{t-i}+{\sum }_{i=0}^{m-1}{b}_{2i}{\Delta Y}_{t-i}+{\sum }_{i=0}^{m-1}{b}_{3i}{\Delta Y}_{t-1}^2+{\sum }_{i=0}^{n-1}\left(b_{4i}{\Delta ORP}_{t-i}+b_{5i}\Delta {ORN}_{t-i}\right)+U_t\hfill \end{array}(6)$

${∆\mathrm{C}\mathrm{O}}_t=\partial {ECT}_{t-1}+{\sum }_{i=1}^{l-1}{b}_{1i}\Delta {CO}_{t-i}+{\sum }_{i=0}^{m-1}{b}_{2i}{\Delta Y}_{t-i}+{\sum }_{i=0}^{m-1}{b}_{3i}\Delta Y_{t-1}^2+{\sum }_{i=0}^{n-1}\left(b_{4i}{\Delta ORP}_{t-i}+b_{5i}{\Delta ORN}_{t-i}\right)+V_t(7)$

Eqs 6, 7 will be employed in each OPEC member’s model. At first, a cointegration will be tested on a null hypothesis (H₀: a₁ = a₂ = a₃ = a₄ = a₅ = 0) through a bound testing approach after selecting the optimal lag length of lagged difference variables in Eq. 6, using Kripfganz and Schneider’s (2019) critical values. After bound testing, long-run effects will be calculated by normalizing lag-level variables in Eq. 6, normalized by estimated a₁. Moreover, the short-run relationships will be corroborated in Eq. 7, if we can get a negative and statistically significant coefficient $\partial$. Then, short-run effects will be captured by coefficients of lagged difference variables in Eq. 7. At last, the asymmetries will be tested by applying the Wald test with H₀: equal coefficients of ORP_t and ORN_t.

Data analyses

Before moving to cointegration analyses, Ng and Perron unit root test is applied and the results are presented in Table 1. For conciseness, we report only MZa statistics. Results show that all variables, except Y_t and Y_t² with constant specification in Libya, are nonstationary at the level. Moreover, all series in all OPEC economies are stationary after the first difference. Hence, the order of integration is mixed in the Libya model, and it is one in the rest countries’ models. Later, we apply ARDL cointegration, which is efficient in both cases of the mixed order and order one integration level.

TABLE 1

TABLE 1. Ng and Perron Test with MZa statistic.

After confirming the integration level, the cointegration test is applied to all countries’ models in Table 2. The estimated F-value is higher than the critical value at 1% significance level in models of Algeria, Angola, Congo, Gabon, Libya, and Venezuela, and at 5% significance level in models of Equatorial Guinea and Iran, and at 10% in the UAE. Thus, the cointegration is verified in all the above-mentioned countries’ models by the bound testing procedure. Moreover, the cointegration is alternatively verified in models of Saudi Arabia, Iraq, Kuwait, and Nigeria with the negative coefficient of ECT_t-1, which reflects the long-run converging equilibrium from any short-run fluctuations (Pesaran et al., 2001). In addition, the results of the diagnostic tests reflect the robustness of all estimated models. Therefore, we may proceed with long and short coefficients estimations.

TABLE 2

TABLE 2. Cointegration analyses.

In Table 3, we display the long-run coefficients from the selected ARDL models of all OPEC members. The EKC is corroborated with a positive coefficient of Y_t and a negative coefficient of Y_t² in models of Algeria, Congo, Gabon, Kuwait, and Saudi Arabia. Thus, the increasing income of these economies would increase emissions in the first phase of the EKC and might decrease emissions in the second phase of the EKC. Inquiring the natural resource rents and environmental quality, literature corroborated the EKC in resource-abundant economies (Baloch et al., 2019; Hassan et al., 2019; Tiba and Frikha, 2019; Shehzad et al., 2022). Likewise, Mahmood and Furqan (2021) have also validated this EKC in the spatial analysis of the GCC panel while investigating the connection between oil rents and emissions. Moreover, a U-shaped effect of income on CO₂ emissions is found in the model of Angola. So, the economic growth of Angola has a positive environmental effect with increasing economic growth in the first phase of the EKC. However, economic growth can have environmental consequences in the second phase of the EKC. This U-shaped relationship is also evident by Moutinho et al. (2020). For the rest of the OPEC economies, our results show that economic growth did not have any effect on CO₂ emissions.

TABLE 3

TABLE 3. The long run results.

In the oil rents and CO₂ emissions relationship, increasing oil rents (ORP_t) show a positive effect on emissions in the models of Equatorial Guinea, Iran, Iraq, Angola, Congo, Kuwait, Libya, and Saudi Arabia. It means that increasing oil rents are increasing economic activities, which need energy and pollute the environment of these countries. Thus, the scale effect of oil rents is dominant in these countries and increasing oil rents have environmental consequences in 8 out of 13 analyzed OPEC members. Many past studies have confirmed that natural resource rents accelerated carbon emissions (Bekun et al., 2019; Adediyan et al., 2020; Hussain et al., 2020; Ulucak and Khan, 2020; Wang et al., 2020; Agboola et al., 2021; Nwani and Adams, 2021; Onifade et al., 2021; Huang and Guo, 2022). Moreover, the literature has corroborated the positive effect of resource rents on the ecological footprint (Baloch et al., 2019; Hassan et al., 2019; Jahanger et al., 2022). Mahmood and Furqan (2021) corroborated a positive connection between oil rents and emissions in the GCC panel’s spatial analysis. On the other hand, our results also show that increasing oil rents decrease emissions in Algeria, the UAE, and Nigeria. Thus, the technique and composition effects of oil rents are dominant over the scale effect in these three countries, which may help to reduce the CO₂ emissions in these economies. Some studies have also corroborated the negative impact of resource rents on emissions (Balsalobre-Lorente et al., 2018; Liu et al., 2022) and on the ecological footprint (Zafar et al., 2019; Danish and Khan, 2020; Danish and Khan, 2020; Kongbuamai et al., 2020; Ulucak and Khan, 2020). Moreover, Ozturk (2017) corroborated the negative impact of oil rents on emissions in Latin America. Furthermore, decreasing oil rents (ORN_t) reduce emissions in models of Saudi Arabia, Angola, Equatorial Guinea, and Libya. So, the decreasing oil rents are decreasing economic activities in these four economies, which would reduce CO₂ emissions. Hence, decreasing oil rents would reduce environmental consequences in 4 out of 13 OPEC economies and lesser dependence on oil rents has pleasant environmental effects in these economies. However, decreasing oil rents have a negative effect on CO₂ emissions in Algeria.

In the long-run asymmetry analyses, the asymmetry in the relationship between oil rents and CO₂ emissions is substantiated by the statistically significant effect of ORP_t and statistically insignificant effect of ORN_t in the models of Angola, Congo, Iran, Iraq, Kuwait, Nigeria, and the UAE. Besides, the impacts of ORP_t and ORN_t are insignificant in Gabon and Venezuela. For the rest cases, the Wald test is employed, and F-stat (p-value) is found as 0.2861(0.4451), 3.2145(0.0841), 0.4263(0.2764), and 4.1257 (0.0461) in Algeria, Equatorial Guinea, Libya, and Saudi Arabia, respectively. Thus, the symmetrical impact of oil rents is corroborated in Algeria and Libya. However, asymmetry is validated in Equatorial Guinea and Saudi Arabia.

Table 4 shows that the short-run relationships have been validated by a negative coefficient of ECT_t-1 in all estimated models with different speeds of adjustments. Moreover, the EKC is corroborated with a positive parameter of ΔY_t and negative coefficient of ΔY_t² in the models of Algeria and Congo, and with a positive parameter of ΔY_t-1 and negative coefficient of ΔY_t-1² in a model of Libya with 1 year lag. A U-shaped impact of growth on emissions is substantiated in the model of Angola and a positive monotonic impact of growth on emissions is observed in Nigeria, the UAE, and Venezuela. Increasing oil rents (ΔORP_t) carry a positive impact on emissions in the models of Angola, Congo, Iran, and Kuwait and have a negative effect in the case of Algeria and the UAE. Thus, increasing oil rents are increasing economic activities and CO₂ emissions in Angola, Congo, Iran, and Kuwait in the short run, and have environmental consequences in 4 out of 13 analyzed OPEC economies. However, increasing oil rents reduce CO₂ emissions in 2 out of 13 analyzed countries. Moreover, decreasing oil rents (ΔORN_t) carry a negative impact on emissions in Algeria, Gabon, Nigeria, and Saudi Arabia.

TABLE 4

TABLE 4. The short run results.

In the short-run asymmetry analyses, asymmetry is substantiated by the statistically significant effect of ΔORP_t and the statistically insignificant effect of ΔORN_t in the models of Kuwait, the UAE, Angola, Congo, and Iran. Moreover, asymmetry is substantiated by the statistically significant effect of ΔORN_t and the statistically insignificant effect of ΔORP_t in the models of Gabon, Nigeria, and Saudi Arabia. In addition, the effects of both ΔORP_t and ΔORN_t are found statistically insignificant in Equatorial Guinea, Iraq, Libya, and Venezuela. Furthermore, the Wald test is applied, and F-stat (p-value) is found 0.1648 (0.7025) in Algeria. Hence, symmetry is corroborated.

Conclusion

Oil rents might be responsible for pollution emissions in oil-abundant economies. The present study probes the asymmetrical impact of oil rents on CO₂ emissions in 13 OPEC economies and also tests the EKC hypothesis using the period 1970–2019. The EKC is proven in 5 out of 13 economies in long run, i.e., Algeria, Congo, Gabon, Kuwait, and Saudi Arabia. Thus, the technique and composition effects of economic growth may outweigh the scale effects in the long run after a threshold point in these economies. However, a U-shaped relationship is found in Angola in both the long and short run. In the short run, the EKC is corroborated in Algeria, Congo, and Libya and economic growth carries a monotonic positive impact on emissions in Nigeria, the UAE, and Venezuela. Increasing oil rents raise CO₂ emissions in 8 out of 13 OPEC economies in the long run, i.e., Equatorial Guinea, Iran, Iraq, Angola, Congo, Kuwait, Libya, and Saudi Arabia. Hence, the scale effects of increasing oil rents are dominant over the technique and composition effects and increasing oil rents has environmental consequences in these economies. In contrast, increasing oil rents reduce emissions in the UAE, Algeria, and Nigeria. Thus, increasing oil rents have pleasant long-run environmental effects in reducing CO₂ emissions in 3 out of 13 analyzed countries, which reflects that technique and composition effects are dominant over scale effects in these economies. Decreasing oil rents help to reduce CO₂ emissions in Angola, Equatorial Guinea, Libya, and Saudi Arabia and increase emissions in Algeria. Moreover, asymmetrical long-run effects of oil rents on CO₂ emissions are found in Saudi Arabia, the UAE, Angola, Congo, Iran, Iraq, Kuwait, Nigeria, and Equatorial Guinea. Increasing oil rents have a positive effect on emissions in Angola, Congo, Iran, and Kuwait and carry a negative impact in Algeria and the UAE in the short run. Besides, falling oil rents increase emissions in Algeria, Gabon, Nigeria, and Saudi Arabia. Moreover, asymmetrical short-run impacts of oil rents are validated in Angola, Congo, Iran, Kuwait, the UAE, Gabon, Nigeria, and Saudi Arabia.

Based on long-run results, we recommend Equatorial Guinea, Angola, Congo, Saudi Arabia, Iran, Iraq, Kuwait, and Libya to invest their oil rents in the development of green and renewable energy projects, avoiding the negative ecological effects of oil rents. Moreover, the over-dependence of these economies on the oil sector may also be one of the reasons for environmental problems. Thus, the economies should diversify from the oil sector by investing the oil rents in the non-oil sector of the economies to avoid the Dutch Disease phenomenon in OPEC economies. Now-a-day, oil prices and rents are booming in OPEC economies, and it is the right time to invest the excessive oil rents to condemn pollution by using these rents in renewable and green projects and by investing in diversification policy. Moreover, increasing oil rents helped reduce emissions in the UAE, Algeria, and Nigeria and these countries should further focus on renewable projects to support a sustainable environment to a greater extent.

Data availability statement

Publicly available datasets were analyzed in this study. This data can be found here: https://databank.worldbank.org/reports.aspx?source=world-development-indicators.

Author contributions

HM: Writing Original Draft preparation, Methodology, Software, Literature Review. NS: Data Curation, Writing, Reviewing and Editing.

Acknowledgments

The authors would like to acknowledge the support of Prince Sultan University for paying the Article Processing Charges (APC) of this publication.

Conflict of interest

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.

Publisher’s note

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.

References

Adediyan, A. R., Chigozie, U. K., and Ehisuoria, O. T. (2020). The empirics of per capita income growth, resources rents and environmental quality in Nigeria. Acad. J. Econom. Stud. 6 (3), 72.

Google Scholar

Adedoyin, F. F., Gumede, M. I., Bekun, F. V., Etokakpan, M. U., and Balsalobre-Lorente, D. (2020). Modelling coal rent, economic growth and CO₂ emissions: Does regulatory quality matter in BRICS economies? Sci. Total Environ. 710, 136284. doi:10.1016/j.scitotenv.2019.136284

PubMed Abstract | CrossRef Full Text | Google Scholar

Agboola, M. O., Bekun, F. V., and Joshua, U. (2021). Pathway to environmental sustainability: Nexus between economic growth, energy consumption, CO₂ emission, oil rent and total natural resources rent in Saudi Arabia. Resour. Policy 74, 102380. doi:10.1016/j.resourpol.2021.102380

CrossRef Full Text | Google Scholar

Alam, M. S., Alam, M. N., Murshed, M., Mahmood, H., and Alam, R. (2022a). Pathways to securing environmentally sustainable economic growth through efficient use of energy: A bootstrapped ARDL analysis. Environ. Sci. Pollut. Res. 29, 50025–50039. doi:10.1007/s11356-022-19410-9

CrossRef Full Text | Google Scholar

Alam, M. S. (2022). Is trade, energy consumption and economic growth threat to environmental quality in Bahrain–evidence from VECM and ARDL bound test approach? Int. J. Emerg. Serv. 11, 396–408. doi:10.1108/IJES-12-2021-0084

CrossRef Full Text | Google Scholar

Alam, N., Hashmi, N. I., Jamil, S. A., Murshed, M., Mahmood, H., and Alam, S. (2022b). The marginal effects of economic growth, financial development, and low-carbon energy use on carbon footprints in Oman: Fresh evidence from autoregressive distributed lag model analysis. Environ. Sci. Pollut. Res. 29, 76432–76445. doi:10.1007/s11356-022-21211-z

CrossRef Full Text | Google Scholar

Alfalih, A. A., and Hadj, T. B. (2022). Financialization, natural resources rents and environmental sustainability dynamics in Saudi Arabia under high and low regimes. Resour. Policy 76, 102593. doi:10.1016/j.resourpol.2022.102593

CrossRef Full Text | Google Scholar

Alvarado, R., Tillaguango, B., Dagar, V., Ahmad, M., Isık, C., Mendez, P., et al. (2021). Ecological footprint, economic complexity and natural resources rents in Latin America: Empirical evidence using quantile regressions. J. Clean. Prod. 318, 128585. doi:10.1016/j.jclepro.2021.128585

CrossRef Full Text | Google Scholar

Auty, R. M. (1993). Sustaining development in mineral economies: The resource curse thesis. London: Routledge. doi:10.4324/9780203422595

CrossRef Full Text | Google Scholar

Badeeb, R. A., Lean, H. H., and Shahbaz, M. (2020). Are too many natural resources to blame for the shape of the Environmental Kuznets Curve in resource-based economies? Resour. Policy 68, 101694. doi:10.1016/j.resourpol.2020.101694

CrossRef Full Text | Google Scholar

Badeeb, R. A., Lean, H. H., and Smyth, R. (2016). Oil curse and finance–growth nexus in Malaysia: The role of investment. Energy Econ. 57, 154–165. doi:10.1016/j.eneco.2016.04.020

CrossRef Full Text | Google Scholar

Baloch, M. A., Mahmood, N., and Zhang, J. W. (2019). Effect of natural resources, renewable energy and economic development on CO₂ emissions in BRICS countries. Sci. Total Environ. 678, 632–638. doi:10.1016/j.scitotenv.2019.05.028

PubMed Abstract | CrossRef Full Text | Google Scholar

Balsalobre-Lorente, D., Shahbaz, M., Roubaud, D., and Farhani, S. (2018). How economic growth, renewable electricity and natural resources contribute to CO₂ emissions? Energy Policy 113, 356–367. doi:10.1016/j.enpol.2017.10.050

CrossRef Full Text | Google Scholar

Bekun, F. V., Alola, A. A., and Sarkodie, S. A. (2019). Toward a sustainable environment: Nexus between CO₂ emissions, resource rent, renewable and nonrenewable energy in 16-EU countries. Sci. Total Environ. 657, 1023–1029. doi:10.1016/j.scitotenv.2018.12.104

PubMed Abstract | CrossRef Full Text | Google Scholar

Benchekroun, H., van der Meijden, G., and Withagen, C. (2020). OPEC, unconventional oil and climate change-On the importance of the order of extraction. J. Environ. Econ. Manage. 104, 102384. doi:10.1016/j.jeem.2020.102384

CrossRef Full Text | Google Scholar

Bhattacharyya, S., and Hodler, R. (2014). Do natural resource revenues hinder financial development? The role of political institutions. World Dev. 57, 101–113. doi:10.1016/j.worlddev.2013.12.003

CrossRef Full Text | Google Scholar

Byakagaba, P., Mugagga, F., and Nnakayima, D. (2019). The socio-economic and environmental implications of oil and gas exploration: Perspectives at the micro level in the Albertine region of Uganda. Extr. Ind. Soc. 6 (2), 358–366. doi:10.1016/j.exis.2019.01.006

CrossRef Full Text | Google Scholar

Cockx, L., and Francken, N. (2016). Natural resources: A curse on education spending? Energy Policy 92, 394–408. doi:10.1016/j.enpol.2016.02.027

CrossRef Full Text | Google Scholar

Corden, W. M., and Neary, J. P. (1982). Booming sector and de-industrialisation in a small open economy. Econ. J. 92, 825–848. doi:10.2307/2232670

CrossRef Full Text | Google Scholar

Daniele, V. (2011). Natural resources and the ‘quality’ of economic development. J. Dev. Stud. 47 (4), 545–573. doi:10.1080/00220388.2010.506915

CrossRef Full Text | Google Scholar

Danish, R., and Khan, S. U. D. (2020). Determinants of the ecological footprint: Role of renewable energy, natural resources rents, and urbanization. Sustain. Cities Soc. 54, 101996. doi:10.1016/j.scs.2019.101996

CrossRef Full Text | Google Scholar

Dietz, S., Neumayer, E., and De Soysa, I. (2007). Corruption, the resource curse and genuine saving. Environ. Dev. Econ. 12 (01), 33–53. doi:10.1017/S1355770X06003378

CrossRef Full Text | Google Scholar

Dong, Y., and Whalley, J. (2012). Joint non-OPEC carbon taxes and the transfer of OPEC monopoly rents. J. Policy Model. 34 (1), 49–63. doi:10.1016/j.jpolmod.2011.08.001

CrossRef Full Text | Google Scholar

Duesenberry, J. S. (1951). Income, saving and the theory of consumer behaviour. Econ. J. 61, 131–134. doi:10.2307/2226615

CrossRef Full Text | Google Scholar

Garthwaite, J. (2018). Stanford study finds Stark differences in the carbon-intensity of global oil fields. Available at: https://news.stanford.edu/2018/08/30/measuring-crude-oils-carbon-footprint/ (accessed March 13, 2022).

Google Scholar

Global Carbon Atlas (2022). Globaal Carbon Atlas. Available at: http://www.globalcarbonatlas.org/en/CO2-emissions (accessed on January 15, 2022).

Google Scholar

Grossman, G. M., and Krueger, A. B. (1995). Economic growth and the environment. Q. J. Econ. 110 (2), 353–377. doi:10.2307/2118443

CrossRef Full Text | Google Scholar

Grossman, G. M., and Krueger, A. B. (1991). Environmental impacts of the North American free trade agreement. Cambridge, MA: National Bureau of Economic Research. NBER Working paper 3914. doi:10.3386/w3914

CrossRef Full Text | Google Scholar

Gylfason, T. (2001). Natural resources, education, and economic development. Eur. Econ. Rev. 45 (4–6), 847–859. doi:10.1016/S0014-2921(01)00127-1

CrossRef Full Text | Google Scholar

Hamilton, J. (2009). Causes and consequences of the oil shock of 2007–2008. Cambridge, MA: National Bureau of Economic Research. NBER working paper 15002. doi:10.3386/w15002

CrossRef Full Text | Google Scholar

Harbaugh, W. T., Levinson, A., and Wilson, D. M. (2002). Reexamining the empirical evidence for an environmental Kuznets curve. Rev. Econ. Stat. 84 (3), 541–551. doi:10.3386/w7711

CrossRef Full Text | Google Scholar

Hassan, S. T., Xia, E., Khan, N. H., and Shah, S. M. A. (2019). Economic growth, natural resources, and ecological footprints: Evidence from Pakistan. Environ. Sci. Pollut. Res. 26 (3), 2929–2938. doi:10.1007/s11356-018-3803-3

PubMed Abstract | CrossRef Full Text | Google Scholar

He, Y., Li, X., Huang, P., and Wang, J. (2022). Exploring the Road toward environmental sustainability: Natural resources, renewable energy consumption, economic growth, and greenhouse gas emissions. Sustainability 14 (3), 1579. doi:10.3390/su14031579

CrossRef Full Text | Google Scholar

Huang, J., and Guo, L. (2022). Analysis of the impact of natural resource rent, transportation infrastructure, innovation and financial development on China's carbon emission. Energy & Environ., 0958305X2211005. doi:10.1177/0958305X221100526

CrossRef Full Text | Google Scholar

Hussain, J., Khan, A., and Zhou, K. (2020). The impact of natural resource depletion on energy use and CO₂ emission in Belt & Road initiative countries: A cross-country analysis. Energy 199, 117409. doi:10.1016/j.energy.2020.117409

CrossRef Full Text | Google Scholar

Ibrahim, R. L., and Ajide, K. B. (2021). The dynamic heterogeneous impacts of nonrenewable energy, trade openness, total natural resource rents, financial development and regulatory quality on environmental quality: Evidence from BRICS economies. Resour. Policy 74, 102251. doi:10.1016/j.resourpol.2021.102251

CrossRef Full Text | Google Scholar

Jahanger, A., Usman, M., Murshed, M., Mahmood, H., and Balsalobre-Lorente, D. (2022). The linkages between natural resources, human capital, globalization, economic growth, financial development, and ecological footprint: The moderating role of technological innovations. Resour. Policy 76, 102569. doi:10.1016/j.resourpol.2022.102569

CrossRef Full Text | Google Scholar

Joshua, U., and Bekun, F. V. (2020). The path to achieving environmental sustainability in South Africa: The role of coal consumption, economic expansion, pollutant emission, and total natural resources rent. Environ. Sci. Pollut. Res. 27 (9), 9435–9443. doi:10.1007/s11356-019-07546-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Khan, A., Chenggang, Y., Hussain, J., Bano, S., and Nawaz, A. (2020). Natural resources, tourism development, and energy-growth-CO₂ emission nexus: A simultaneity modeling analysis of BRI countries. Resour. Policy 68, 101751. doi:10.1016/j.resourpol.2020.101751

CrossRef Full Text | Google Scholar

Khan, S., Murshed, M., Ozturk, I., and Khudoykulov, K. (2022). The roles of energy efficiency improvement, renewable electricity production, and financial inclusion in stimulating environmental sustainability in the Next Eleven countries. Renew. Energy 193, 1164–1176. doi:10.1016/j.renene.2022.05.065

CrossRef Full Text | Google Scholar

Kongbuamai, N., Bui, Q., Yousaf, H. M. A. U., and Liu, Y. (2020). The impact of tourism and natural resources on the ecological footprint: A case study of ASEAN countries. Environ. Sci. Pollut. Res. 27 (16), 19251–19264. doi:10.1007/s11356-020-08582-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Kripfganz, S., and Schneider, D. C. (2019). Response surface regressions for critical value bounds and approximate p-values in equilibrium correction models. Exeter, UK: University of Exeter. Economics Department Discussion Papers Series, Paper number 19/01Available from: http://www.people.exeter.ac.uk/RePEc/dpapers/DP1901.pdf (accessed March 17, 2022).

Google Scholar

Kwakwa, P. A., Alhassan, H., and Adu, G. (2020). Effect of natural resources extraction on energy consumption and carbon dioxide emission in Ghana. Int. J. Energy Sect. Manag. 14 (1), 20–39. doi:10.1108/IJESM-09-2018-0003

CrossRef Full Text | Google Scholar

Liski, M., and Tahvonen, O. (2004). Can carbon tax eat OPEC's rents? J. Environ. Econ. Manage. 47 (1), 1–12. doi:10.1016/S0095-0696(03)00052-4

CrossRef Full Text | Google Scholar

Liu, Q., Zhao, Z., Liu, Y., and He, Y. (2022). Natural resources commodity prices volatility, economic performance and environment: Evaluating the role of oil rents. Resour. Policy 76, 102548. doi:10.1016/j.resourpol.2022.102548

CrossRef Full Text | Google Scholar

Loganathan, N., Mursitama, T. N., Pillai, L. L. K., Khan, A., and Taha, R. (2020). The effects of total factor of productivity, natural resources and green taxation on CO₂ emissions in Malaysia. Environ. Sci. Pollut. Res. 27 (36), 45121–45132. doi:10.1007/s11356-020-10291-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Mahmood, H., Alkhateeb, T. T. Y., and Furqan, M. (2020). Oil sector and CO₂ emissions in Saudi Arabia: Asymmetry analysis. Palgrave Commun. 6 (1), 88. doi:10.1057/s41599-020-0470-z

CrossRef Full Text | Google Scholar

Mahmood, H., and Furqan, M. (2021). Oil rents and greenhouse gas emissions: Spatial analysis of gulf cooperation council countries. Environ. Dev. Sustain. 23 (4), 6215–6233. doi:10.1007/s10668-020-00869-w

CrossRef Full Text | Google Scholar

Mahmood, H. (2022). The effects of natural gas and oil consumption on CO₂ emissions in GCC countries: Asymmetry analysis. Environ. Sci. Pollut. Res. 29, 57980–57996. doi:10.1007/s11356-022-19851-2

CrossRef Full Text | Google Scholar

Merrill, R. K., and Orlando, A. W. (2020). Oil at risk: Political violence and accelerated carbon extraction in the Middle East and North Africa. Energy Econ. 92, 104935. doi:10.1016/j.eneco.2020.104935

CrossRef Full Text | Google Scholar

Mogaddam, A. (2022). Allocating the CO₂ emissions of an oil refinery with aumann–shapley prices: Comment. Energy Econ. 32, 243–255. doi:10.1016/j.eneco.2006.02.002

CrossRef Full Text | Google Scholar

Moutinho, V., and Madaleno, M. (2022). Does economic sectorial diversification affect the relationship between carbon emissions, economic growth, energy consumption, coal and gas consumption? Evidence from OPEC countries using panel cointegration analysis. Energy Rep. 8, 23–28. doi:10.1016/j.egyr.2022.01.039

CrossRef Full Text | Google Scholar

Moutinho, V., Madaleno, M., and Elheddad, M. (2020). Determinants of the Environmental Kuznets Curve considering economic activity sector diversification in the OPEC countries. J. Clean. Prod. 271, 122642. doi:10.1016/j.jclepro.2020.122642

CrossRef Full Text | Google Scholar

Murshed, M., Apergis, N., Alam, M. S., Khan, U., and Mahmud, S. (2022c). The impacts of renewable energy, financial inclusivity, globalization, economic growth, and urbanization on carbon productivity: Evidence from net moderation and mediation effects of energy efficiency gains. Renew. Energy 196, 824–838. doi:10.1016/j.renene.2022.07.012

CrossRef Full Text | Google Scholar

Murshed, M., Haseeb, M., and Alam, M. (2022b). The environmental Kuznets curve hypothesis for carbon and ecological footprints in South asia: The role of renewable energy. GeoJournal 87 (3), 2345–2372. doi:10.1007/s10708-020-10370-6

CrossRef Full Text | Google Scholar

Murshed, M., Khan, S., and Rahman, A. A. (2022a). Roadmap for achieving energy sustainability in Sub-Saharan Africa: The mediating role of energy use efficiency. Energy Rep. 8, 4535–4552. doi:10.1016/j.egyr.2022.03.138

CrossRef Full Text | Google Scholar

Nathaniel, S. P., Yalçiner, K., and Bekun, F. V. (2021). Assessing the environmental sustainability corridor: Linking natural resources, renewable energy, human capital, and ecological footprint in BRICS. Resour. Policy 70, 101924. doi:10.1016/j.resourpol.2020.101924

CrossRef Full Text | Google Scholar

Ng, S., and Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica 66, 1519–1554. doi:10.1111/1468-0262.00256

CrossRef Full Text | Google Scholar

Nwani, C., and Adams, S. (2021). Environmental cost of natural resource rents based on production and consumption inventories of carbon emissions: Assessing the role of institutional quality. Resour. Policy 74, 102282. doi:10.1016/j.resourpol.2021.102282

CrossRef Full Text | Google Scholar

Office of the Historian, (2022). OPEC oil embargo 1973–1974. Washington, DC: U.S. Department of State, Office of the Historian. https://history.state.gov/milestones/1969-1976/oil-embargo (accessed May 05, 2022).

Google Scholar

Onifade, S. T., Gyamfi, B. A., Haouas, I., and Bekun, F. V. (2021). Re-Examining the roles of economic globalization and natural resources consequences on environmental degradation in E7 economies: Are human capital and urbanization essential components? Resour. Policy 74, 102435. doi:10.1016/j.resourpol.2021.102435

CrossRef Full Text | Google Scholar

OPEC (2021). Opec: Annual report 2021. Retrieved from: https://www.opec.org/opec_web/static_files_project/media/downloads/publications/AR%202021.pdf (accessed February 12, 2022).

Google Scholar

Ouédraogo, M., Peng, D., Chen, X., Hashmi, S. H., and Sall, M. I. (2021). Dynamic effect of oil resources on environmental quality: Testing the environmental Kuznets curve hypothesis for selected african countries. Sustainability 13 (7), 3649. doi:10.3390/su13073649

CrossRef Full Text | Google Scholar

Ozturk, I. (2017). Measuring the impact of alternative and nuclear energy consumption, carbon dioxide emissions and oil rents on specific growth factors in the panel of Latin American countries. Prog. Nucl. Energy 100, 71–81. doi:10.1016/j.pnucene.2017.05.030

CrossRef Full Text | Google Scholar

Pesaran, M. H., Shin, Y., and Smith, R. J. (2001). Structural analysis of vector error correction models with exogenous I(1) variables. J. Econom. 97, 293–343. doi:10.1016/S0304-4076(99)00073-1

CrossRef Full Text | Google Scholar

Saboori, B., Al-mulali, U., and Bin Baba, M. (2016). Mohammed AH. Oil-Induced environmental Kuznets curve in organization of petroleum exporting countries (OPEC). Int. J. Green Energy 13 (4), 408–416. doi:10.1080/15435075.2014.961468

CrossRef Full Text | Google Scholar

Sachs, J., and Warner, A. M. (1995). Natural resources abundance and economic growth. Cambridge, MA: National Bureau for Economic Research NBER. Working Paper 5398. doi:10.3386/w5398

CrossRef Full Text | Google Scholar

Sachs, J. D. (2007). How to handle the macroeconomics of oil wealth. Editors M. S. Humphreys, and J. E. JD/Stiglitz, 173–193. (assessed on https://policydialogue.org/publications/working-papers/how-to-handle-the-macroeconomics-of-oil-wealth/ January 16, 2022).

Google Scholar

Shahbaz, M., Kablan, S., Hammoudeh, S., Nasir, M. A., and Kontoleon, A. (2020). Environmental implications of increased US oil production and liberal growth agenda in post-Paris Agreement era. J. Environ. Manage. 271, 110785. doi:10.1016/j.jenvman.2020.110785

PubMed Abstract | CrossRef Full Text | Google Scholar

Shao, S., and Yang, L. (2014). Natural resource dependence, human capital accumulation, and economic growth: A combined explanation for the resource curse and the resource blessing. Energy Policy 74, 632–642. doi:10.1016/j.enpol.2014.07.007

CrossRef Full Text | Google Scholar

Shehzad, K., Zeraibi, A., and Zaman, U. (2022). Testing the N-shaped environmental Kuznets Curve in Algeria: An imperious role of natural resources and economic globalization. Resour. Policy 77, 102700. doi:10.1016/j.resourpol.2022.102700

CrossRef Full Text | Google Scholar

Shen, Y., Su, Z. W., Malik, M. Y., Umar, M., Khan, Z., and Khan, M. (2021). Does green investment, financial development and natural resources rent limit carbon emissions? A provincial panel analysis of China. Sci. Total Environ. 755, 142538. doi:10.1016/j.scitotenv.2020.142538

PubMed Abstract | CrossRef Full Text | Google Scholar

Shin, Y., Yu, B., and Greenwood-Nimmo, M. (2014). “Modelling asymmetric cointegration and dynamic multiplier in an ARDL framework,” in Festschrift in honor of peter schmidt: Econometric methods and applications. Editors W. C. Horrace, and R. C. Sickles (New York, NY, USA: Springer Science and Business Media), 281

CrossRef Full Text | Google Scholar

Shittu, W., Adedoyin, F. F., Shah, M. I., and Musibau, H. O. (2021). An investigation of the nexus between natural resources, environmental performance, energy security and environmental degradation: Evidence from Asia. Resour. Policy 73, 102227. doi:10.1016/j.resourpol.2021.102227

CrossRef Full Text | Google Scholar

Shuai, S. H. A. O., and Zhongying, Q. I. (2009). Energy exploitation and economic growth in western China: An empirical analysis based on the resource curse hypothesis. Front. Econ. China 4 (1), 125–152. doi:10.1007/s11459-009-0008-1

CrossRef Full Text | Google Scholar

Sinha, A., and Sengupta, T. (2019). Impact of natural resource rents on human development: What is the role of globalization in asia pacific countries? Resour. Policy 63, 101413. doi:10.1016/j.resourpol.2019.101413

CrossRef Full Text | Google Scholar

Tiba, S., and Frikha, M. (2019). The controversy of the resource curse and the environment in the SDGs background: The african context. Resour. Policy 62, 437–452. doi:10.1016/j.resourpol.2019.04.010

CrossRef Full Text | Google Scholar

Ulucak, R., and Khan, S. U. D. (2020). Relationship between energy intensity and CO₂ emissions: Does economic policy matter? Sustain. Dev. 28 (5), 1457–1464. doi:10.1002/sd.2098

CrossRef Full Text | Google Scholar

Ulucak, R., Danish, , and Ozcan, B. (2020). Relationship between energy consumption and environmental sustainability in OECD countries: The role of natural resources rents. Resour. Policy 69, 101803. doi:10.1016/j.resourpol.2020.101803

CrossRef Full Text | Google Scholar

Wang, L., Vo, X. V., Shahbaz, M., and Ak, A. (2020). Globalization and carbon emissions: Is there any role of agriculture value-added, financial development, and natural resource rent in the aftermath of COP21? J. Environ. Manage. 268, 110712. doi:10.1016/j.jenvman.2020.110712

PubMed Abstract | CrossRef Full Text | Google Scholar

World Bank (2022). World development indicators. Washington, D.C: World Bank. https://databank.worldbank.org/reports.aspx?source=world-development-indicators (accessed January 21, 2022).

Google Scholar

Zafar, M. W., Zaidi, S. A. H., Khan, N. R., Mirza, F. M., Hou, F., and Kirmani, S. A. A. (2019). The impact of natural resources, human capital, and foreign direct investment on the ecological footprint: The case of the United States. Resour. Policy 63, 101428. doi:10.1016/j.resourpol.2019.101428

CrossRef Full Text | Google Scholar

Zhang, M., Ajide, K. B., and Ridwan, L. I. (2021). Heterogeneous dynamic impacts of nonrenewable energy, resource rents, technology, human capital, and population on environmental quality in Sub-Saharan African countries. Environ. Dev. Sustain. 24, 11817–11851. doi:10.1007/s10668-021-01927-7

CrossRef Full Text | Google Scholar