Decoupling Economic Expansion from Environmental Degradation: A Panel ARDL Analysis of Renewable Energy’s Role in Arab MENA Countries

In light of the increasing challenges facing the global economy due to severe climate change, and with the conclusion of the activities of the United Nations Climate Change Conference (COP 28) in December 2023 in the UAE, attention has turned to the countries of the Middle East and North Africa (MENA). The main concern is how these countries can strengthen their climate actions and develop a strategic approach to ensuring the successful transformation of the region to clean energy. As reported by the United Nations Framework Convention on Climate Change [1], climate projections for the MENA region anticipate a global temperature rise of approximately 3 to 4 degrees Celsius by the end of the 21st Century. It is already the scarcest source of water region in the world, and rising temperatures are expected to lead to more persistent and severe droughts. It has become evident for the MENA region that the traditional growth model, characterized by excessive reliance on traditional energy resources and the proliferation of greenhouse gas-intensive industries, will pose a significant threat to environmental integrity and threaten the long-term sustainability of economic advancement in the long term. Therefore, decoupling energy consumption demand from greenhouse emissions, specifically carbon dioxide (CO₂) discharge, is the cornerstone of efforts to meet the objectives of the Paris Agreement and decarbonize the world’s economy. In this context, by expanding the proportion of renewable energy (RE) usage in their portfolio, MENA nations can significantly reduce their carbon footprint while fostering sustainable economic growth (EG). This green energy transition supports global climate goals and promotes the region’s energy security and economic resilience. Following these economic and environmental goals, the MENA countries have been showing a growing interest in sustainable development, including through efforts to change energy consumption patterns. This interest is fostered by (1) a continued increase of the fossil fuel energy demand in the MENA Arab countries, which is expected to nearly double by 2040, particularly for electricity needs [2]. Demographic developments will continue to drive up energy consumption demand until [3]. (2) An overall energy mix is over 98% fossil fuels, including gas, oil, and coal, with a significant portion coming from natural gas [4]. (3) Huge RE endowments. The MENA region has one of the most significant solar energy potentials globally and a substantial wind energy potential, especially in Morocco and Saudi Arabia.

Despite the substantial potential of RE and the increasing acknowledgment of its critical role in addressing environmental degradation globally, only limited empirical examinations have emphasized the substantial influence that RE consumption, besides economic expansion, may play in reducing the aggregate greenhouse emissions for the MENA region in the long term [5-9]. In this context, Albaker et al. [5] investigated the effects of RE and green innovation on carbon emission levels in MENA countries, showing the significant potential of RE to reduce discharge despite having restricted geographical coverage of the Arab MENA region. Also, Charfeddine and Kahia [9] investigated the relationship between RE, financial development, and carbon discharge using panel vector autoregression, focusing on the wider MENA region, including Turkey. However, Omri and Saidi [7] concentrated on the impacts of renewable and non-RE sources on CO₂ discharge, emphasizing the dominant role of fossil energy. Collectively, these studies highlight the need for a more integrated analysis that considers RE as the centerpiece and considers its long-term implications for Arab MENA countries.

Most existing studies have often overlooked assessing the dynamic relationship between CO₂ discharge and RE use per se; instead, several have analyzed the repercussion of fossil energy usage from the perspective of the growth–environment linkage in isolation [10-19]. To fill the current research gap, this study investigates the long-term connection and short-term dynamic interactions linking sustainable energy usage, EG, and environmental degradation across six Arab MENA territories (Algeria, Tunisia, Egypt, Morocco, Jordan, and Saudi Arabia) during the period 1990 – 2020. The primary objective is to assess how RE adoption and economic expansion affect environmental quality. This investigation uses a robust econometric analysis using the Panel Autoregressive Distributed Lag (PANEL-ARDL) model, focusing on MG and PMG estimators. Therefore, our study aims to enhance the existing body of empirical studies on the connection between RE consumption, EG, and environmental degradation and seeks to provide significant policy implications, especially since decoupling energy consumption demand from greenhouse emissions is an indispensable condition for Arab MENA countries to attain their long-run sustainable development.

The remaining study sections have the following structure. We begin in Section 2 with a comprehensive exploration of current studies on the substantial consequences of green energy use and economic expansion on environmental quality, explicitly focusing on the MENA territories. Next, Section 3 outlines the estimating process, model, and data. Subsequently, in Section 4, we present a detailed breakdown of our empirical findings. Finally, Section 5 concludes with MENA economic reality-based policy recommendations.

A substantial corpus of previous research has studied the interactions tying environmental degradation and EG but has ignored the potential influence of green energy use on these interactions. Therefore, such neglect may cause misleading results for some countries in the MENA region, mainly where a series of economic and environmental reforms can induce some permanent structural changes in their sustainable development in the long run. Before developing our predetermined expectations regarding these variables into a cohesive framework, we scrutinize the bilateral interconnection between environmental pollution, RE use, and economic expansion separately.

The research investigations exploring the interaction between pollutant emissions (CO₂) and EG in the MENA area remain a contention between researchers. On the one hand, numerous empirical research studies have suggested that EG often enhances the mitigation of CO₂ emissions, which are key indicators of environmental pollution in the MENA region. Among these studies, Ben Cheikh and Ben Zaied [20] carried out one noteworthy research using a nonlinear panel threshold regression framework to reexamine the dynamic interplay between CO₂ pollutant emissions and per capita income in the MENA region. Their results reveal a threshold effect in carbon dioxide evolution, indicating that the influence of income growth follows a nonlinear pattern and is influenced by various energy-related factors. Similarly, to explore the dynamic interactions between economic expansion, energy transition, and technological level in 21 MENA countries from 1997 to 2021, Alariqi et al. [21] applied a Vector Error Correction model (VEC)for the short-run analysis and the ARDL model for the long-run analysis. The authors indicated that as MENA countries experience EG, they tend to direct resources toward environmentally friendly technologies and sustainable practices, which helps minimize pollutant (CO₂) emissions. Omri et al. [22] explored the main factors influencing the CO₂ output for 16 countries in the MENA region between 1990 and 2018. Their study emphasized the capacity of economic development and energy use to influence the dynamics of CO₂ emissions. For this objective, the authors decomposed the economy into a triad of core components: industry, services, and agriculture. The aggregate traditional energy demand was divided into fossil and green energy sources. The authors applied an econometric tool represented by the Augmented Mena Group (AMG) and the Common Correlated Effect Mean Group (CCE-MG). Their empirical findings suggest that a structural shift towards a RE-based economy, driven by EG, can significantly reduce CO₂ emissions.

However, some empirical investigations have indicated a direct interdependence between economic expansion and CO₂ emissions; environmental quality continues to degrade with rising per capita income. in the MENA area. In this context, we can reference the research conducted by Alshehry and Belloumi [23] for 17 MENA countries to examine the asymmetric and symmetric effects of traditional energy use and economic expansion on aggregate CO₂ emissions from 1990 to 2020. To this end, the authors applied a panel linear and nonlinear ARDL estimation approach. They concluded that expanding economic activities in the MENA nations may result in environmental degradation through increased CO₂ discharge in the long term. Meanwhile, increasing energy demand could increase CO₂ emissions in the short-run and long-run.

Additionally, Omri and Saidi [7] assessed the impacts of fossil fuel and green energy sources on CO₂ flows across 14 MENA countries between 1990 and 2019, using vector error correction and fully modified least-squares techniques. Their analysis revealed that fossil energy usage significantly increases CO₂ discharge, while green energy sources have a mitigating effect. However, the overall effect of EG remained detrimental to environmental quality.

To examine the potential impact of excessive usage of traditional energy, urban growth, and economic development on the increase of CO₂ output in Belt and Road countries from 1985 to 2017, Liu et al. [24] applied some econometric techniques, including a panel cointegration approach, Granger causality tests, and heterogeneity analysis. According to their findings, the main factors that negatively affect CO₂ emissions are the increasing use of traditional energy, the expansion of the economy, and the spread of urbanization. Furthermore, according to the panel causality study, their energy usage, GDP growth, urbanization, and CO₂ emissions are all positively correlated.

In the same context, Fodha and Zaghdoud [25] examined the pollutant emissions of Tunisia’s economy from 1961 to 2004 with the EG nexus. Employing Johansen's cointegration analysis, the study is conducted regarding the environmental Kuznets curve theory, with CO₂ emission and GDP serving as the environmental and economic indicators, respectively. The findings demonstrated that, over time, the connection between GDP and CO₂ emissions is monotonically growing. In addition, the causality test findings showed that the link between pollution and income in the Tunisian economy is one-way, with income changing the environment and not the other way around.

Several factors explain the apparent contradictions in the literature. The different econometric estimations (such as panel data, time series analysis, or econometric methods such as ARDL and EKC models) often yield different results. Moreover, sample selection variations greatly influence findings; studies of developed nations often find a decoupling effect between EG and emissions, while studies of developing countries frequently report a positive correlation. Also, temporal differences are essential, with the effects of green technologies and policy reforms more likely to be captured in recent studies than in earlier studies. Understanding how economic development and environmental degradation are related across different settings requires the analysis of these patterns.

The literature reveals a complex and multifaceted interrelation between sustainable energy use and environmental pollution in the MENA area. While some studies indicate that green energy consumption can indeed contribute to diminishing CO₂ output pollution, others suggest that, under specific conditions, its adoption may not always translate into environmental improvement. For this instance, Adun et al. [26] ran a scenario study in Algeria, Morocco, Tunisia, Egypt, and Libya using the Energy-PLAN simulation environment to assess the hourly feasibility of clean energy generation for power and freshwater production through desalination. Their research showed that increasing the RE share to 52% in Morocco by 2030 could lead to a 52.09% reduction in carbon emissions. Their empirical result highlights how RE may greatly enhance environmental quality, especially with technological advances.

Al-Ayouty [27] studied 18 MENA nations plus Turkey to scrutinize the interconnection between economic complexity and pollutant emissions from 1990 to 2020. The author employed panel data econometric techniques based on the Fully Modified Ordinary Least Squares (FMLOS) and Granger causality tests. The estimation findings indicated that green energy adoption demonstrates a substantial inverse relationship with CO₂ output, suggesting a significant amelioration in environmental quality. In addition, the econometric estimations validate the Environmental Kuznets Curve concept across the MENA and Turkey. This study’s key policy implication is that Turkey should acknowledge the need to pair EG and industrialization with a shift from traditional to knowledge-based economies. Albaker et al. [5] analyzed the effects of shifting to sustainable energy on EG and the emission of greenhouse gases in the MENA region between 1997 and 2021. Advanced econometric techniques (e.g., Method of Moments Quantile Regression) were used. They concluded that RE use adds significantly to economic expansion and reduces CO₂ emissions, implying more investment in renewable technologies.

Alharthi et al. [28] investigated the main factors of CO₂ evolution in MENA countries that adopted empirical aspects of the EKC structure by employing econometric quantile techniques, using data set from 1990-2015 on real per capita income, CO₂ emissions, fossil and green energy sources, and urbanization. The results of their study demonstrated that carbon discharge decreases drastically with the use of sustainable energy, which is observed to be more effective at higher quantiles. This means, in turn, that an expansion in the size and overall real income of economies makes sustainable energy relatively more effective at reducing environmental harm.

On the other hand, some other research reveals that RE consumption may not always translate into environmental improvement. In this context, we can mention the study by Kahia et al. [10] for 24 countries in the MENA area from 1980 to 2012 to analyze the potential impact of sustainable energy use on CO₂ evolution, EG, and financial development. To do so, the authors used the Panel Vector autoregression technique. Their findings revealed that RE use had little influence, indicating that these nations’ energy sectors are immature. The results also showed that the examined countries should strengthen the RE industry by facilitating bank loans for green energy project investments to prevent environmental harm and boost EG.

Similarly, in their study, Bélaïd and Youssef [29] applied the ARDL cointegration technique to analyze the correlation between CO₂ emissions and renewable electricity usage in Algeria from 1980 to 2012. Their econometric findings indicate that renewable electricity usage shows no statistically significant effect on CO₂ emissions in the short or long term. However, their empirical results indicate that the utilization of renewable power has a Granger-causal relationship with long-term CO₂ emissions. Lin and Abudu [30] analyzed energy-saving and substitution policies and plans to lower CO₂ output in the electricity sector in the MENA region. Using data from 2000 to 2015, they found that RE intensity is too low to reduce CO₂ discharge effectively.

Moreover, non-renewable energy intensity remains high, contributing to poor energy efficiency at just 40%. Consequently, current production methods and policies, like subsidies for non-renewable energy, block significant CO₂ reduction. Thus, the region’s EG is tied to non-renewable energy use, meaning that cleaner energy and climate goals need substantial policy and technology changes.

The EG-RE consumption nexus has secured substantial attention in the literature due to its implications for sustainable development and policy planning. In this context, using panel data techniques, Bhattacharya et al. [31] examined the interconnection between RE usage and EG across 38 countries from 1991 to 2012. The estimation findings demonstrated a positive long-term elasticity between RE investments and EG in more than half of the sample, underscoring the global significance of RE in promoting sustainable development. In the same regard, Kayesh and Siddiqa [32] also examined the dynamic associations between RE consumption, natural gas consumption, and EG in Bangladesh from 1980 to 2018. The authors used a combination of the Autoregressive Distributed Lag (ARDL) model for long-term relationship analysis and the Vector Error Correction Model (VECM) for causal inference. Their results revealed a unidirectional long-run causality from RE usage to EG, indicating the key role in achieving Bangladesh’s sustainable development goals. In their work, Yildirim et al. [33] explored the U.S. economy’s RE consumption–EG nexus over a six-decade period from 1949 to 2010 using bootstrap-corrected and Toda-Yamamoto causality tests. Their empirical result indicated that while biomass-waste-derived energy positively influences GDP, other renewable sources exhibit weaker economic ties.

Similarly, Ocal and Aslan [34] examined the connection between RE consumption and EG in Turkey from 1990 to 2010, using ARDL bounds testing and Toda-Yamamoto causality. Their econometric results provided evidence from Turkey supporting the conservation hypothesis, which suggests that EG drives RE consumption rather than the reverse. These findings show that EG and RE consumption interact in a complex and context-specific manner and highlight the necessity of local and targeted energy policies.

Our review of the literature on the renewable energy-environmental pollution nexus in the MENA region shows that most studies focus on the growth-environment link in isolation, overlooking the dynamic relationship between renewable energy (RE) adoption and pollution. This gap limits understanding of how RE adoption and economic growth affect carbon emissions, especially in the MENA region, where RE sectors are still developing, and economic structures vary significantly. Addressing this relationship is crucial to identifying feedback mechanisms and guiding policy. By analyzing these dynamics, policymakers can better promote economic growth and environmental sustainability, while future research can provide stronger empirical evidence to improve models and predict the long-term effects of green energy transitions. Our study aims to fill this gap and offer actionable policy recommendations for the MENA region.

Our current study analyses the long-term and short-term repercussions of green energy use and economic expansion on environmental pollution across six Arab MENA territories. The study covers four countries in North Africa: Tunisia, Algeria, Morocco, and Egypt, as well as two countries in the Middle East: Saudi Arabia and Jordan. To reach the main objective of our study, we have a panel-ARDL estimation technique.

The choice of the PANEL-ARDL model in this study is driven by its suitability for analyzing datasets with mixed integration orders, accommodating variables that are integrated of order I(0) and I(1). This feature ensures robustness when estimating both short- and long-term relationships among RE consumption, EG, and CO₂ discharge. The model’s dynamic framework is particularly advantageous for capturing the long-run equilibrium alongside short-run fluctuations, which coincides substantially with the study’s objective of examining the interconnections between economic and environmental factors. Furthermore, using Mean Group (MG) and Pooled Mean Group (PMG) estimators enhances the model’s flexibility by addressing heterogeneity across countries while providing efficient estimates of long-run coefficients. Also, several assumptions of the PANEL-ARDL model are tested to validate our approach’s reliability. Cross-sectional independence is assessed using Pesaran’s CD test, slope homogeneity is examined via Pesaran and Yamagata’s slope homogeneity test, and stationarity and cointegration properties are verified through second-generation unit root and cointegration tests.

As a first step, we utilize the CD test developed by Pesaran [35] to test the hypothesis of cross-section dependence (CSD) in residuals. Also, three other tests are applied to investigate the presence of CDS in both fixed and random effects panel models: the Pesaran scaled LM test, the Breusch-Pagan LM test, and the Bias-corrected scaled LM test, which helps in identifying hidden correlations among the panel units. These tests are essential when the analyzed data are panel data that may exhibit cross-sectional dependencies due to standard economic or environmental policies that may impact the countries. Treating cross-sectional dependence (CSD) is indispensable in establishing panel data reliability. The omission of CSD generates inconsistent parameter estimates and invalid inference procedures, as unaccounted for cross-unit interactions through common factors and spatial spillovers violate the fundamental assumption of cross-sectional independence. By employing appropriate CSD diagnostic tests and robust estimation procedures, we obtain consistent and asymptotically efficient parameters reflecting true cross-country economic relationships while controlling for spatial dependencies. Furthermore, to address heterogeneity across the individual units, our model includes fixed and random effects to obtain more accurate findings that reflect the specific characteristics of each country. The following econometric model describes this approach:

where, lnCO₂ represents the logarithm of CO₂ emissions, lnRGDP denotes the logarithm of the real gross domestic product, and lnREC represents the logarithm of RE consumption. The term $\mu_{i t}$ encompasses three components: $\alpha_i$, representing time-invariant heterogeneity across the countries; $\lambda_i f_t$, an unobserved com factor yet exhibits heterogeneous loadings, thus addressing time-variant heterogeneity and facilitating the representation of Cross-Section Dependence (CSD); and $\varepsilon_{i t}$ is the stochastic error term. The letters (i) and (t) represent the respective countries and year intervals.