International Journal of Energy Economics and Policy
International Journal of Energy Economics and Policy (IJEEP) is the international academic journal, and is a double-blind, peer-reviewed academic journal publishing high quality conceptual and measure development articles in the areas of energy economics, energy policy and related disciplines. The journal has a worldwide audience. The journal's goal is to stimulate the development of energy economics, energy policy and related disciplines theory worldwide by publishing interesting articles in a highly readable format. ISSN: 2146-4553 2024 CiteScore: 3.4 37/78: General Energy (Scopus®) 81/284: Economics, Econometrics and Finance (Scopus®) Ranking: 2024 SJR: 0.343 Editorial Board: 51 members from 26 countries/regions
Submission of an article implies that the work described has not been published previously , that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, will not be published elsewhere in the same form, without the written consent of the Publisher. The Editors reserve the right to edit or otherwise alter all contributions, but authors will receive proofs for approval before publication.
Exploring the Nexus between Environmental Degradation and Human Health in the MENAT Region: The Role of Financial Institutions’ Development
The paper examines the role played by financial institutions’ development on the nexus between environmental degradation and human health in countries in the region encompassing the Middle East, North Africa, and Turkey (MENAT). The paper argues that ecological degradation leads to better human health. However, financial institutions’ development (depth, access, and efficiency) weakens the impact of environmental degradation on human health. A comparison of oil-producing and non–oil-producing countries shows that financial institutions’ development influences the relationship between environmental degradation and human health. In oil-producing countries, enhanced financial institutions tend to significantly weaken the detrimental impact of environmental degradation on human health. However, in the non–oil-producing countries, human health tends to be weakly correlated with ecological degradation when the role of financial institutions is enhanced, confirming that financial institutions play a greater role in directing more funds to power plant projects, which enabled these countries to have less environmental degradation and stable levels of human health. These outcomes offer valuable guidance to policymakers regarding the role played by financial institutions’ development in the link between environmental degradation and human health, driving economies in the MENAT region to promote public health by adopting more effective ecofriendly programs associated with continued development of financial institutions.
Copyright (c) 2025 International Journal of Energy Economics and Policy
Decarbonizing Growth: The Role of Human Capital Development and Innovation in Malaysia’s Pursuit of SDG 13
This study investigates the impact of human capital development and technological innovation on environmental sustainability in Malaysia, as part of the Malaysian commitment to Sustainable Development Goal 13 (Climate Action). Using Autoregressive Distributed Lag (ARDL) model and time series data covering the period 1990-2022, the analysis explores the dynamic relationship between CO2 emissions and major macroeconomic variables, namely economic growth, energy consumption, technological innovation, trade openness, foreign direct investment (FDI), quality of governance, education, and GINI coefficient. The empirical findings reveals that technological innovation and human capital development significantly contribute to long-run decline in CO2 emission, hence emphasis their role in ensuring a sustainable low-carbon economy. On the other hand, FDI correlates with higher emissions, which gives relevance to pollution haven hypothesis in the Malaysian case. The study emphasis the need to invest in green technology, incorporate sustainability in the education system and tightening environmental standards in the foreign investments. Such policy steps are necessary to ensure that economic progress is no longer linked to environmental degradation and accelerate Malaysia’s transition towards a climate-resilient future.
Carbon, Growth and Clean Energy: Decoding Bulgaria’s Sustainability Equation
Carbon emissions represent a critical and pressing challenge in the 21st century. This study examines the impact of economic growth on carbon emissions in Bulgaria, an emerging economy in Eastern Europe. Utilizing annual time series data spanning from 1990 to 2020, we analyzed the relationship between carbon emissions and key explanatory variables, including GDP growth and renewable energy consumption. To investigate the long-term dynamics among the variables, the study employed the Autoregressive Distributed Lag (ARDL) Bounds testing approach for co-integration. The empirical findings confirm the existence of a long-run relationship among the model variables. Notably, economic growth was found to have a significant positive effect on carbon emissions in Bulgaria. Conversely, renewable energy consumption exhibited an insignificant negative impact on emissions, indicating that the renewable energy sector remains underdeveloped and insufficiently integrated into the national energy mix. These findings carry important implications for policymakers. To balance economic growth with environmental sustainability, it is essential to promote and invest in renewable energy sources. Strengthening this sector could help mitigate the environmental consequences of economic expansion in Bulgaria.
Energy Transition and Economic Growth in Asia Region: Evidence with Panel Quantile Regression
Countries in the Asia region are increasingly aware of the importance of realising the Sustainable Development Goals (SDGs), The energy transition policy that has been carried out will affect their economic growth, so this research is focused on an in-depth study of the effect of energy transition on the economic growth of countries in Asia region. The results show that this study reveals that the energy transition plays an important role in driving economic growth in the Asia region. Variables such as sustainability and regulation as well as political commitment are shown to have a significant influence on increasing economic growth, highlighting the importance of policies that support clean energy. However, other results also suggest a potential trade-off between sustainability and economic growth for Asia countries in the short term, emphasising the need for a cautious approach in designing energy transition policies in the region.
Impact of Green Growth Factors on Foreign Direct Investment: Evidence from Central Asia
One of the pressing issues in developing countries with abundant mineral resources is the impact of foreign investment on economic development without harming the environment. The purpose of this research is to assess the impact of CO2 emissions from Industrial Processes, electricity production oil, gas and coal sources, and Oil price indicators, among the green growth factors, on foreign direct investment in Central Asian countries (Kazakhstan, the Kyrgyz Republic, and Uzbekistan). For this purpose, statistical data for the period 1998-2023 were obtained from the World Data Bank database. The pooled mean group-autoregressive distributed lag (PMG-ARDL) methodology was applied. The model results showed the cumulative impact of these factors for Central Asia. When testing the model for each country separately, a statistically significant impact of the factors was revealed. Since all three countries are sufficiently rich in natural resources, priority should be given not only to effectively develop mineral resources, but also to minimize damage to nature and protect it. In this regard, the authors shared a number of recommendations in the concluding section.
Re-Examining Energy-Growth Nexus in 27 Selected South Countries: Heterogeneous Panel Model
This paper examines the link between energy consumption and economic growth using a panel data sample of 27 Southern countries observed over the period 2002-2020. To capture long-run effects, we used appropriate panel data econometric techniques in the presence of cross-sectional dependence and slope heterogeneity, while Dumitrescu and Hurlin (2012) causality tests examined short-run causal effects. Our results show that (i) in the long run, energy consumption has a negative and significant effect on economic growth in all countries, while other variables have a positive and significant effect, except institutional quality form, which is not significant both in short and long run on economic growth. (ii) in the short run, all variables have a positive and significant effect on economic and, (iii) causality tests confirm the feedback hypothesis between energy consumption and growth. The study concludes by calling on policymakers to strengthen institutional qualities and adopt financial and energy efficiency policies that could sustain economic development in the long run.
Structural Transformation in the Blue-Green Nexus: Maritime Trade, Conservation Areas, and Energy Intensity Patterns
Improving energy efficiency is one of the key pillars in the transition to a low-carbon economy and sustainable development. However, amidst increasing urbanization, labor force growth, and renewable energy adoption, energy intensity in Emerging markets and developing economies (EMDEs) still shows a stagnant trend. This indicates the existence of non-sectoral structural dynamics that have not been fully identified in previous literature. This research is motivated by the urgent need to quantitatively examine how multidimensional transformation affects national energy efficiency in EMDEs countries. This study aims to analyze the influence of container port traffic (container trade volume), marine protected areas (% of territorial waters), urban population (% of total population), labor force participation rate (% of working-age population), and renewable energy consumption (% of total final energy consumption), on the energy intensity level of primary energy in EMDEs countries over the period 2017-2021. Based on previous theoretical studies and empirical trends, it is hypothesized that container port traffic, and marine protected areas, urbanization, and renewable energy consumption reduce energy intensity, while labor force participation tends to increase energy intensity if not accompanied by sectoral and technological reforms. The research methodology uses a panel data regression approach with the Fixed Effect Model. The analysis shows that partially, container port traffic, and marine protected areas, urban population, and renewable energy consumption have a negative and significant effect on energy intensity, while labor force participation rate shows a positive and significant effect. Simultaneously, the five variables have a significant effect on energy intensity. The coefficient of determination (R2) of 0.994898 indicates that 99.48% of the variation in energy intensity can be explained by the variation in the five independent variables. This finding confirms the importance of policy formulation that integrates demographic structural transformation, renewable energy transition, maritime trade infrastructure modernization, and marine environmental governance to sustainably reduce energy intensity in EMDEs countries.
Modeling Carbon Emissions and Energy Transition in the Context of Indonesia’s Economic Expansion
This study looks at how economic growth, renewable energy use, and carbon dioxide emissions interact in Indonesia’s energy plans. It uses data from 1990 to 2023 and a method called ARDL bounds testing to study both long-term and short-term changes in these areas. The results show that economic growth increases CO2 emissions, but using renewable energy helps reduce this effect. This highlights the importance of renewables for low-carbon growth. The study also finds that CO2 emissions lead to more renewable energy use, suggesting that environmental concerns, not just economic growth, influence energy policies in Indonesia. These findings support the idea that as economies grow, they can become more environmentally friendly. However, Indonesia’s current efforts to cut emissions may not be enough to meet climate goals due to infrastructure and policy challenges. This study suggests the need for new policies, better energy grids, stronger accounting-based transparency in carbon markets, and cooperation between public and private sectors to speed up the shift to sustainable energy. Indonesia’s experience offers important lessons for other developing countries trying to balance economic growth with environmental care.
Information Communication Technology, Electricity Consumption and Economic Growth Nexus in Botswana
When discussing economic growth, electricity consumption and information and communication technology are both crucial components. Effective resource allocation is made feasible by ICT, which raises demand and drives down prices. Electricity, on the other hand, is critical to modern life since it powers industries, technologies, and necessary services, improving living standards and facilitating social and economic growth. The study aims to assess how ICT, electricity consumption, and economic growth are related in Botswana. This study investigates whether there is a causal link between ICT, power use, and economic expansion. In order to assess the nexus relationship, the study used the autoregressive distributed lag model. The findings showed that ICT has a long-term beneficial impact on economic growth, while economic growth has a long-term negative impact on ICT. The study also demonstrated directional causality between electricity use and ICT. This implies that rising electricity consumption raises the need for electricity, which in turn raises ICT investment. It was discovered that Botswana's economic growth was negatively impacted by education. Long-term economic growth in Botswana is enhanced by a rise in industrial expansion. A two-way causal relationship between ICT and electricity use was also demonstrated; as electricity use rises, so does the demand for ICT investment, which in turn raises ICT investment. The study recommends that in the diversification thrust of Government of Botswana, electricity and ICT should be given priority since they can be catalyst for economic growth in the long run.
State Policy Responses to Urban Development and CO2 Emissions in Kazakhstan: The Role of Global Uncertainty in Shaping Environmental Governance
This paper examines the dynamic link between urbanisation and carbon dioxide (CO2) emissions in Kazakhstan with the focus on the impact of global uncertainty. Using annual data from 1990 to 2020, the study uses an autoregressive distributed lag (ARDL) model in error correction form, based on the Environmental Kuznets Curve (EKC) hypothesis. The findings of the paper show that GDP per capita is the main factor influencing both short- and long-term CO2 emissions. Urbanisation dramatically lowers emissions over time, defying popular belief and indicating efficiency improvements in Kazakhstan’s cities. Crucially, the insignificance of the WUI and its interaction term indicates that global uncertainty neither directly affects emissions nor modifies the urbanization - emissions link, contradicting the findings of other authors. These findings have significant policy ramifications: Kazakhstan needs to increase the use of renewable energy sources, diversify its energy sources, and design its cities wisely to divorce growth from emissions. When properly controlled, urbanisation can be a tool for sustainable growth. The analysis concludes that global uncertainty has no discernible impact on Kazakhstan’s emissions trajectory and that domestic structural reforms have a greater impact on emissions reduction than external shocks.
Asymmetric Effects of Electricity Consumption and Population Growth on South Africa’s Employment in the Private-Sector
This paper empirically investigated the relationship between energy consumption, population growth, and unemployment in South Africa over the period from 1990 to 2022, employing the nonlinear autoregressive distributed lag (NARDL) model. The research aims to analyse how fluctuations in energy consumption and demographic changes influence unemployment rates in the country. By examining the long-run and short-run dynamics among these variables, the study seeks to provide insights into the critical role of energy policies and demographic trends in shaping employment outcomes. The study found that electricity consumption has a nonlinear effect on employment, with positive and negative fluctuations impacting employment differently. Population growth showed no significant effect on private-sector employment in both the short and long run. The results suggest that reduced electricity consumption is associated with increased private-sector employment in South Africa, emphasizing the need for targeted energy policy reforms.
Asymmetric Effects of Fiscal and Monetary Policies on Environmental Quality in South Africa
The effect of fiscal and monetary policies can either improve or worsen environmental quality, depending on how the policies are implemented, this may lead to asymmetrical impacts. Therefore, the aim of this study was to investigate the asymmetric effects of fiscal and monetary policies on environmental quality in South Africa from 1990 to 2023 using the nonlinear autoregressive distributed lag (NARDL) technique. The study found that a positive shock in discount rate has a positive and significant influence on carbon emissions (CO2) in the long run however, a negative shock has an insignificant negative impact. Moreover, economic growth was reported to have a significant positive impact on carbon emissions (CO2) in the long run. A positive shock in government expenditure was found to have a significant and negative influence on carbon emissions (CO2), while a negative shock in government expenditure has a significant positive impact in the long run. The effect of fiscal and monetary policies on environmental quality were found to be asymmetrical in the long run. The reported findings have a significant implication for fiscal and monetary policies in South Africa and other countries with similar economic settings. Both monetary and fiscal policies have a significant influence on environmental quality, policymakers could implement strategies to enhance environmental quality by alleviating carbon emissions (CO2). In addition, policymakers should consider coordinating fiscal and monetary policies to attain decarbonisation.
Unpacking Clean and Dirty Energy Market Linkages: Fresh Evidence from Quantile-on-Quantile Connectedness and Causality-in-Quantiles
This research investigates the interrelationships between clean and dirty energy markets, focusing on both return and volatility dynamics over the period from March 03, 2005 to August 30, 2024. Employing the recently developed quantile-on-quantile connectedness (QQC) framework, alongside a causality-in-quantile (CiQ) analysis, the study explores directional spillovers across varying market conditions. The findings reveal several key insights. First, connectedness is highly heterogeneous across quantiles, with stronger spillovers observed in the tails of the distribution—indicating that extreme market conditions foster intensified transmission between energy sectors. Second, total connectedness among directly related quantiles is consistently higher than that of reversely related quantiles, for both return and volatility spillovers. Third, the connectedness between clean and dirty energy markets surpasses that between clean energy and WTI crude oil, reflecting tighter financial integration between equity-based energy indices. Notably, while the dirty energy market initially receives shocks from the clean market, it later emerges as a shock transmitter. Meanwhile, WTI plays a more symmetric role in return spillovers but predominantly transmits volatility shocks at moderate to higher quantiles. Additionally, quantile-based spillovers show marked time variation, spiking during systemic events such as the global financial crisis and the COVID-19 pandemic. CiQ analysis confirms the existence of bidirectional causality. These findings have important implications: for policymakers, they highlight the need to account for sectoral interdependence in energy transition planning; for investors, they underscore the limited hedging capacity between clean and dirty energy assets and the necessity of quantile-aware risk management strategies.
Comparative Study of Agricultural Value Added in China and India on CO2 Emissions: Based on K-nearest Neighbor Algorithm
This study contributes to the current discourse on the relationship between environmental sustainability and economic growth by examining the connections between poverty, carbon emissions, and the value generated in the agricultural sector. We assess the agricultural sectors of China and India, analyzing their roles in global carbon emissions through empirical data, econometric models, and machine learning techniques. We find a nonlinear relationship between economic growth and emissions; initially, development elevates carbon output, while subsequent progress encourages sustainability through technological innovations and policy initiatives. Among the machine learning methods employed, the K-Nearest Neighbors (KNN) algorithm demonstrated the highest predictive accuracy. The results indicate that China’s agricultural sector is the dominant contributor to carbon emissions, accounting for 78.2%, while India’s sector contributes 21.8%. These findings underscore the disparities in agricultural carbon footprints between the two nations and highlight the necessity of integrated strategies that balance economic growth with environmental protection. Policy implications involve implementing focused poverty reduction initiatives, renewable energy strategies, and sustainable farming methods to lessen the effects of climate change while promoting economic growth. The study highlights how artificial intelligence and machine learning can improve predictive accuracy and guide effective climate policies.
Effects of Oil Shocks on the Trade Balance of Azerbaijan: Evidence from the TVP-VAR Model
This study examines the effect of oil shocks on Azerbaijan’s trade balance using a Time-Varying Parameter Vector Autoregression (TVP-VAR) model, drawing on monthly data from December 1994 to November 2024. The results indicate that the negative effects of oil production shocks on Azerbaijan’s trade balance exhibit considerable variation over time and that these adverse impacts become statistically significant in the post-COVID-19 period, indicating a heightened sensitivity of the trade balance to oil production fluctuations in the wake of the pandemic. Although the time-varying responses to oil price shocks are generally positive, they lose statistical significance during periods of sharp decline, suggesting a weakening of the transmission mechanism under extreme market conditions. The impact of exchange rate misalignment on the trade balance fluctuates, showing positive responses following major devaluation or policy changes. This study underscores the necessity of reducing dependence on oil exports and diversifying public revenues to lessen reliance on oil. These results provide important information for controlling external balances in nations that rely heavily on natural resources.
Studying How Macroeconomic Variables Affect Carbon Dioxide Emissions in Saudi Arabia: An ARDL Bounds Testing Approach to Cointegration
Most countries around the world face significant environmental challenges due to their heavy reliance on non-renewable energy sources for economic growth. Therefore, a careful study of air quality in these countries is crucial, given the increasing impact of air pollution on public health and environmental sustainability. So, this study investigates the intricate relationships between carbon dioxide (CO2) emissions from power industry (Energy) and three key economic drivers: manufacturing, trade, and foreign direct investment (FDI) in Saudi Arabia from 1990 to 2023. The Autoregressive Distributed Lag (ARDL) model was employed to explore both short-term and long-term dynamics. The optimal model identified was ARDL(1,4,1,4). The findings suggest that manufacturing and trade exert a negative effect on CO2 emissions, whereas FDI contributes positively to the long run. The error correction model (ECM) indicates that economic adjustments occur over approximately 2 years.
Mind Over Market: Behavioural Determinants of Renewable Energy Investment Adoption in India
This study investigates the psychological and behavioural drivers affecting the adoption of renewable energy investments in India, a rapidly developing nation with urgent energy transition targets. Despite technological and financial incentives, adoption remains minimal, necessitating an exploration of the cognitive and dispositional factors influencing human investment intentions. A structured questionnaire was distributed to 416 urban participants in Tier-I and Tier-II Indian cities. Metrics including cognitive biases, behavioural inertia, gain/loss framing, personality factors, and green behavioural spillover were assessed utilising validated scales. The data were analysed using Structural Equation Modelling (SEM) in IBM AMOS, which facilitated the evaluation of both the measurement models for understanding the behavioural determinants of renewable energy investment adoption. The findings indicated that all five behavioural characteristics had a substantial impact on plans to invest in renewable energy. Green behavioural spillover revealed as the most significant predictor, succeeded by cognitive biases and personality characteristics. The model explained 67% of the variance in investment intentions, underscoring the significance of behavioural factors in renewable energy transitions. This paper proposes an innovative behavioural framework specific to India, addressing deficiencies in current techno-economic adoption models. The results provide practical guidance for developing behavioural treatments, focused awareness campaigns, and policy instruments that correspond with psychological motivators, so improving the efficacy of renewable energy adoption methods.
Climate Change and Monetary Policy in Indonesia: Evidence from Asymmetric Time Varying Granger Causality
This study examines the asymmetric time-varying climate change shocks on monetary policy in Indonesia over the period January 1990 to March 2025. Performing a recent novel asymmetric time-varying Granger causality (AS-TVGC) technique, we capture the asymmetric climate change leading to monetary policy proxied by M0, M1, M2, and BI policy rate significantly. Empirical findings reveal that date stamping of climate change to monetary policy from TVGC estimations. In addition, the AS-TVGC profoundly exposes how the monetary policy responds to both positive and negative climate change shocks significantly. Specifically, we reveal that the monetary policy responds variously to climate change-positive, but persistently to climate change-negative. Consequently, in addition to addressing the exposure of asymmetric causal climate change to monetary policy, the central bank policy makers should take the mandate to design new climate-based monetary operations to set price stability and sustainable growth in the net-zero central banking framework.
Renewable Energy and CO2 Emissions in Upper-Middle Income Transition Countries
The aim of this study is to examine the relationship between renewable energy consumption and CO2 emissions in a sample of 12 upper middle income transitioning countries using data from 1995 to 2022. This study relies on a number of panel data estimation methods such as OLS, fixed effects regression and cointegration techniques. Across all estimations with find that renewable energy decreases CO2 emissions even after controlling for economic growth and trade openness. In addition, the results from Dumitrescu and Hurlin (2012) suggest that there is unidirectional causality from renewable energy to CO2 emissions in our sample. This study offer a number of policy implications and avenues for future research.
Macroeconomic Pathways to Renewable Energy Expansion: Implications for Investment and Climate Policy
The rising global demand for sustainable energy, driven by volatile fossil fuel prices and resource depletion, underscores the urgent need to understand the drivers of renewable energy adoption. This study empirically examines the macroeconomic determinants influencing renewable energy consumption in Somalia. Using national data from 1990 to 2022, the analysis employs the Autoregressive Distributed Lag (ARDL) and Dynamic Least Squares (DLS) approaches to estimate both short-run and long-run elasticities of key economic variables. The findings reveal that GDP has a positive but statistically insignificant effect on renewable energy use, with a 1% increase in GDP leading to a 0.021% rise in consumption over the long term. In contrast, foreign direct investment (FDI) and domestic investment exhibit negative effects, reducing renewable energy use by 0.002% and 0.046%, respectively. Trade openness is also negatively associated with renewable energy consumption (coefficient: -0.009), suggesting that greater trade liberalization may hinder renewable energy adoption. Conversely, population growth positively influences renewable energy use, while carbon emissions show a negative relationship, emphasizing the importance of tailored energy strategies aligned with national economic conditions. Based on these findings, the study recommends that the Somali government establish a comprehensive renewable energy policy framework, revise trade policies to support clean energy goals, incentivize green FDI, and strengthen regulatory institutions to foster sustainable energy investment.
Promoting Electricity-Saving Practices in Urban Office Settings: The Role of Employees in Vietnam’s Banking Sector
This study looks into the key motivators that influence the attitude of bank employees toward electricity-saving, viewed in the light of energy productivity at the workplace and its connection to more general sustainability aims. This study posits a contribution toward the understanding of pro- environmental behavior in the workplace by examining factors, including attitudes, awareness toward electricity- saving, and intention, that influence low-carbon behavior for banking employees. This study makes use of a quantitative research design on details obtained from 405 employees selected by convenience sampling from various levels of hierarchy in the firm. This will provide a varied view of behavioral patterns linked to the use of energy. The findings of this study will bring out the motivation of employees to support the corporate electricity-saving conservation initiative in the prevailing trend of rising importance of environmental concern and strategic significance of employee engagement towards the sustainability drive of the organization. More specifically, subjective standards, perceived behavioral control, sense of responsibility, and cognition of electricity price are factors that influence electricity-saving behaviors among the banking employees in HCMC. These findings show a strong connection between these factors and the actual uptake of the practice by the employees. These insights should, therefore, inform the action of banks in Ho Chi Minh City in taking electricity-saving opportunities while reducing the negative environmental impacts that result from their operations. Moreover, saving on electricity presents organizations with enormous economic benefits due to resultant cost savings, which enhances their competitiveness. In this regard, implementing the findings of this study may help the employees in banking services raise awareness regarding electricity-saving and provide the valuable knowledge for practices as well as scholars.
Volatility Spillover between Stock Returns and Oil Prices in ASEAN: A Post-Pandemic Reassessment Using EGARCH
This paper re-examines the volatility spillover effects between oil prices and stock market returns in ASEAN countries in the post-COVID-19 context. Utilizing daily data from March 2021 to December 2023, the study employs the EGARCH (1,1) model to measure asymmetric volatility transmission across six ASEAN markets—Indonesia, Malaysia, Singapore, Thailand, Vietnam, and the Philippines. The findings indicate significant volatility spillovers, albeit with varying degrees of magnitude and direction compared to the pandemic period. Notably, oil price shocks continue to influence emerging ASEAN markets, reflecting heightened integration with global commodity markets. The results have practical implications for investors and policymakers in managing risk and structuring portfolios during economic normalization.
The Effects of Environmental Quality, Technological Progress and Aggregate Risk on Green Growth in the Mena Region
Green growth (GG) or environmentally adjusted multifactor productivity growth is essential to achieve the dual objectives of economic development and pollution reduction. In this context, very little work has addressed the issue of sustainable development in the MENA region. Therefore, our work studies the impacts of environmental quality, technological progress and aggregate risk on green growth of this region in the aggregate level. Using the autoregressive distributed lag (ARDL) model over the period 1996-2020, the results demonstrate that GG is positively related to R&D expenditure and natural resource rents but inversely associated with aggregate (economic, financial, and political) risks. In the long run, a 1% increase in total risk decreases GG by 0.7%. In contrast, a 1% increase in profits from fossil fuel exports and innovation increases GG by 0.8% and 0.3%, respectively. The impact of renewable energy consumption is positive but not significant on GG. These findings are also confirmed by alternative regressions and offer several policy recommendations.
Governance Framework of Energy Transition in Uzbekistan
Currently, Uzbekistan, a double-landlocked country in Central Asia, is facing an increasing number of environmental and energy-related problems such as worsening air quality, frequent electricity interruptions, high levels of old and inefficient infrastructure, and energy supply insecurity. They are all associated with an increasing population and a rapidly developing economy and may cause a slowdown in the country's economic growth. The study examines Uzbekistan's energy transition using the UNDP Energy Governance Framework. Applied methods and tools include content, thematic, policy, and stakeholder analysis. A comprehensive analysis was conducted across four focus areas: inclusive institutions, policy frameworks, civic engagement, and oversight mechanisms. Key findings highlight the need to strengthen institutional coordination, improve data quality, develop clear regulatory policies, increase stakeholder participation, and establish independent oversight bodies. Significant challenges remain in such areas as data quality, policy coherence, and civic engagement. Addressing these issues is crucial for Uzbekistan to successfully navigate its energy transition and to ensure long-term energy security while meeting sustainability goals. Applying the UNDP Energy Governance Framework can help address the challenges by promoting transparent, inclusive and sustainable energy governance. Recommendations include enhancing inter-ministerial collaboration, expanding renewable energy deployment, fostering community engagement, and building capacity of oversight institutions.
Economic Growth and Environmental Quality Indicators
The economic growth of a nation is deeply intertwined with the availability and quality of its environmental resources. However, industrialisation, urbanisation, and agricultural expansion often pursued in the name of development have led to the overexploitation of natural assets, resulting in environmental degradation, climate change, and biodiversity loss. This paper examines the trade-off between economic growth, measured by Gross Domestic Product (GDP), and environmental quality indicators such as CO2 emissions, maximum, minimum, and mean temperatures, total greenhouse gas emissions, water stress levels, annual rainfall, and freshwater withdrawals by agriculture and industry. Drawing on data from 1990 to 2020, the study employs statistical analysis to investigate these relationships in the Indian context. The findings reveal a significant and positive correlation between GDP growth and environmental degradation, particularly in terms of rising emissions and temperature levels, increased water stress, and unsustainable freshwater use. These results underscore the need for policies that align economic development with environmental sustainability to safeguard long-term growth and resilience.
Green Finance and Low-Carbon Transformation: The Dual Mediation of Cost Optimization and Technological Innovation under Market Demand Moderation
This study explores how green finance drives the development of green and low-carbon enterprises in China and examines the moderating role of green market demand. Using quantitative methods, data were collected from 404 valid questionnaires covering industrial enterprises of varying sizes, regions, and years of establishment. Structural equation modeling and artificial neural network analysis were employed to test the proposed framework. The findings reveal that green finance significantly supports low-carbon transformation by enabling sustainable practices. Two key mediators—optimization of financing costs and low-carbon technological innovation—play crucial roles in this process. However, increased green market demand negatively moderates the effect of financing cost optimization, while positively enhancing the impact of technological innovation. These results highlight the dual moderating effects of market demand. The study contributes by constructing a hybrid model that integrates green finance mechanisms with low-carbon enterprise development and provides empirical insights based on Chinese industrial data. It underscores the importance of tailoring green finance policies to varying market conditions. Future research may expand on these findings by examining how green finance operates in different industrial contexts or market structures.
The Effect of Environmental Performance, Environmental Management System, and Institutional Ownership on Carbon Emission Disclosure with Media Exposure as a Moderating Variable
This study examines the effects of environmental performance, environmental management systems, and institutional ownership on carbon emission disclosure. It also investigates the moderating role of media exposure in these relationships. The research population comprises non-financial sector companies listed on the Indonesia Stock Exchange (IDX) from 2021 to 2023. A purposive sampling method was employed, resulting in 174 units of analysis. Secondary data were collected using documentation techniques. The study applies descriptive and inferential analyses, utilizing panel data regression and Moderated regression analysis (MRA) with the EViews software. The results show that environmental performance does not significantly affect carbon emission disclosure. Environmental management systems positively influence carbon emission disclosure, while institutional ownership has a negative impact. Additionally, media exposure does not moderate the relationships between environmental performance, environmental management systems, and institutional ownership with carbon emission disclosure. This study differs from previous research in that it uses specific indicators for environmental performance and includes media exposure as a moderating variable.
Industrial Exports and Global Carbon Emissions: Assessing the Impact of the U.S. and China Using a Decision Tree Algorithm
This research employs a decision tree approach to investigate the impact of industrial exports from China and the United States on global carbon emissions in the industrial sector. Drawing on panel data from 1992 to 2023 provided by the World Bank, the results reveal a substantial positive relationship between China’s manufacturing exports- accounting for 81% of the feature importance- and global industrial CO2 emissions (Pearson coefficient: 0.837). The feature importance of U.S. exports, on the other hand, is lower at 19%, suggesting a negative association (Pearson coefficient: −0.901). With an R-squared value of 0.96 and a mean squared error (MSE) of 0.002, the decision tree model outperformed the other two models, random forests and support vector machines, among the five machine learning models evaluated. These findings demonstrate the disparate environmental effects of export-driven industrialization, with a focus on China’s significant emissions from energy-intensive manufacturing, and the urgent need for focused measures, like carbon pricing, the incorporation of green technologies, and sustainable trade agreements, to bring industrial growth into line with climate goals, especially the Sustainable Development Goals (SDGs 9 and 13) of the United Nations. This study advances the application of machine learning in environmental economics, providing valuable insights for balancing economic and ecological priorities in international trade systems.
The Role of Green Consumer Behavior in Shaping Electric Vehicle Adoption Among Future Business Leaders
The study investigates the intention of future business leaders to adopt electric vehicles (EVs). A survey of 248 business leaders found that environmental concern is the strongest predictor of EV adoption as a mediator. Structural Equation Model (SEM) was used to investigate the determinants of EV adoption, focusing on perceived benefits, social influence, effort expectancy, performance expectancy, environmental concerns, and electric vehicle adoption. The study suggests that EV marketers should promote environmental awareness in future business leaders’ mindsets to drive long-term behavioural change. Strategies that enhance public understanding of environmental issues, improve perceived ease of use, and emphasize the practical and social benefits of EVs are essential for accelerating the transition to sustainable transport systems. Additionally, out of four, three determinants significantly influenced environmental concerns, while one determinant, like perceived benefit, is insignificant. Environmental concerns are crucial in shaping consumer behaviour towards electric mobility. The research contributes to the theoretical development of the electric vehicle adoption model in green technology contexts and offers actionable insights for marketing strategists and public policymakers aiming to promote widespread electric vehicle acceptance among consumers.
A Resource-Based View on Low-Carbon Value: Governance and Environmental Management Accounting Pathways via Carbon Disclosure and Stakeholder Pressure
This study aims to examine the effect of Corporate Governance and Environmental Management Accounting on Firm Value, with Carbon Emission Disclosure as a mediating variable and Stakeholder Pressure as a moderating variable. Grounded in the Resource-Based View (RBV) and Triple Bottom Line (TBL) frameworks, this study conceptualizes Carbon Emission Disclosure as a strategic internal capability that enhances firm legitimacy and value creation. Using panel data regression on 105 observations from 21 Indonesian energy companies listed on the Indonesia Stock Exchange during 2019-2023, this study finds that Environmental Management Accounting and Carbon Emission Disclosure have a significant positive effect on firm value. Corporate Governance also positively influences firm value but has a negative impact on Carbon Emission Disclosure, indicating that governance mechanisms in emerging markets may still be symbolic rather than substantive. The study further reveals that Carbon Emission Disclosure mediates the relationship between EMA and firm value, but not between Corporate Governance and firm value. Stakeholder pressure functions as a pure moderator that strengthens the positive relationship between Carbon Emission Disclosure and firm value. The findings provide actionable insights for policymakers and managers in carbon-intensive industries by emphasizing the need to strengthen environmental accounting systems and stakeholder engagement mechanisms to enhance firm value. This study offers a novel integration of RBV and TBL perspectives in explaining the indirect and moderated pathways linking governance, environmental management, and firm value, particularly in the context of a developing economy with evolving sustainability regulations.
Toward Sustainability Tourism: An ARDL Analysis of the Differential Impacts of International Tourism and Air Transport on CO2 Emissions in Thailand
This study investigates the differential impacts of international tourism and air transport on CO2 emissions in Thailand by employing the Autoregressive Distributed Lag (ARDL) approach. Analyzing data from 1995 to 2020, the findings indicate a significant negative correlation between international tourism and CO2 emissions, suggesting that increased tourist arrivals can lead to enhanced environmental efficiency under specific conditions. Conversely, air passenger numbers demonstrate a direct positive relationship with CO2 emissions in the short term, pointing to the inherent greenhouse gas intensity associated with air travel. The high explanatory power of the ARDL model, with an adjusted R-squared of 0.971397, emphasizes the robustness of these results, although caution is advised in interpreting the P-values due to the potential biases from automated model selection processes. These insights contribute to the broader understanding of how tourism dynamics interact with environmental outcomes, particularly in countries like Thailand, which heavily rely on tourism for economic growth. The implications highlight the urgent need for policies that balance tourism development with sustainability mandates, ultimately guiding Thailand’s trajectory toward carbon neutrality and sustainable tourism practices.
The Moroccan Evidence through an ARDL Approach to the Education, Renewable Energy Consumption, and Economic Growth Nexus
Education is a key component of sustainable development since it influences economic growth, the energy transition, and environmental behaviors. In the Moroccan context, the increase in the rate of solarization reflects public initiatives around education, with potential benefits for productivity and technological innovation. The current study aims to determine Morocco’s impact on CO2 emissions, renewable energy consumption (REC), education, general government consumption spending (GGCS), and economic growth (EG). This study used an autoregressive methodology for stationarity and distributed degradation in conjunction with the least squares ordinary approach to evaluate the short- and long-term correlations between the model’s variables. For the study, World Development Indicators (WDI) annual data for the years 1993 through 2020 has been collected. The bound test was employed to assess long-term relationships, while the White test was used to check for heteroscedasticity in model residuals. The empirical research demonstrated numerous relationships between the independent and dependent variables. The actual data showed that although all independent variables were not stationary in the first difference, they became stationary in the second difference, while the dependent variable was stationary in the first difference. The model simulation using the bound test confirmed a long-term relationship between the independent and dependent variables. However, the long- and short-term relationships between EG and education were disproved. The model residuals exhibited no signs of heteroscedasticity. The findings highlight the complex interplay between education, CO2 emissions, renewable energy consumption, government spending, and economic growth in Morocco. Policymakers should consider these relationships when designing strategies for sustainable development, particularly in balancing economic expansion with environmental sustainability and education development.
Dynamics of ICT, Natural Resource, Green Innovation, and Environmental Sustainability in Developing-8 organization of Economic Cooperation Countries: A Cross-Sectional ARDL Approach
The member states of developing-8 orD-8 organization for economic cooperation have been facing various environmental hitches posing different challenges. The interlinkages between information and communication technologies (ICT), natural resources, green finance, green innovation and environmental footprint are turning to be pivotal in this regard. This study examines the interrelationships among, natural resource rents (NRR), green technology innovation (GI), economic growth (EG), green finance (GF), and ecological footprints (EFP) in the D-8 member countries using data for the period 1995-2024. After checking data for the cross-sectional dependence (CSD), a cross-sectional augmented autoregressive distributive lag (CS-ARDL) approach is employed for the estimation. The empirical results show that natural resources increase ecological footprint. Green finance, information and communication technologies, green innovations, and technological advancements all contribute to reducing ecological footprints. The Dumitrescu and Hurlin (2012) causality testing show a one-way causal relationship between economic growth, green finance, ecological footprints, and information and communication technologies. This study incorporates new knowledge from the D-8 nations in the existing body of knowledge related to causes of environmental pollution. In addition, this study provides a benchmark by which policymakers and government institutions can evaluate their investments in the ICT, green finance, and environment-friendly technology to mitigate environmental emissions.
Institutional Quality, Foreign Direct Investment, and Renewable Energy Production: Evidence from Eastern European Countries Using a Panel VAR Model
Renewable energy is crucial for mitigating climate change, stabilizing energy prices, and preventing energy crises; however, governance quality and foreign direct investment (FDI) in promoting clean energy development are often overlooked. Renewable energy production depends on political decisions and capital, technology, and expertise provided through FDI. This paper examines how institutional quality and FDI inflows affect renewable energy production. We analyze data from 1996 to 2022 across 12 Eastern European countries with growing economies and potential for renewable energy development. Our findings reveal that these countries cannot meet the institutional quality standards and FDI inflows required for renewable energy development.
The Impact of GDP, Government Effectiveness, Globalization, and Carbon Emissions on ASEAN Tourism Receipts: An Empirical Study
This study examines the impact of GDP, globalization, government effectiveness, and carbon emissions on International Tourism Receipts (ITR) across ten ASEAN countries during the period 2003-2018. Employing Fixed-effect model, Unit Root Tests, and Johansen Fisher Panel Cointegration techniques, the findings reveal that GDP and globalization have a significant positive effect on ITR. By contrast, government effectiveness and carbon emissions have a significant negative impact on tourism revenue. These results suggest that the success of the tourism sector is influenced not only by economic growth, but also by the quality of governance and environmental conditions. This study highlights the importance of efficient public policy, global openness, and environmental management in promoting sustainable tourism growth in the ASEAN region.
Oil Price Volatility across Timeframes and its Impact on ASEAN Stock Indices: Changes Observed since the COVID-19 Pandemic
Oil is considered a vital energy source and changes in oil prices have important implications for developed as well as developing economies. By keeping this point of view, the current study aimed at analyzing the impact of oil prices on the stock prices of the most dynamic region of the world namely; The Association of South East Asian Nations (ASEAN). The post-COVID-19 data period was selected by the authors because the COVID-19 pandemic created oil price shocks which translated into global oil prices. The empirical findings demonstrate that oil prices significantly affect ASEAN stock indices. Nonetheless, the effect differs at various frequency levels. In the short to medium term, market participants should be cognisant of oil price volatility and its immediate effects. In the long term, investors and governments should prioritise basic economic indicators as stock markets increasingly detach from oil price volatility. These findings indicate that investors and governments ought to consider varying time horizons. In the short and medium term, oil price fluctuations considerably affect stock markets, necessitating effective risk management measures. Ultimately, attention should transition to more comprehensive economic indicators, as the stock market becomes increasingly less affected by oil prices. This comprehension is essential for formulating educated investment strategies and influencing energy policies in the ASEAN region.
An Analysis of the Effect of Tourism Revenues, Exchange Rates, and Oil Prices on GDP in Kazakhstan Using the Quantile Regression Method
This study investigates the impact of international tourism revenues, the real effective exchange rate, and oil revenues on economic growth in Kazakhstan using the quantile regression method. Unlike traditional linear models that primarily focus on average effects, analyzing the determinants of economic growth across different distribution points (or quantile levels) provides more nuanced and valuable insights for policymakers. The research utilizes annual time series data from 1995 to 2023. After testing the stationarity of the variables using the Augmented Dickey-Fuller (ADF) test, both least squares regression analysis and quantile regression models were applied. The results indicate a positive and statistically significant effect of oil revenues on Gross Domestic Product (GDP) at all quantile levels. In contrast, while tourism revenues and the real effective exchange rate index also had a positive impact on economic growth, these effects were not found to be statistically significant in the quantile regression models. These findings suggest that the Kazakh economy remains heavily reliant on energy revenues, which may heighten its economic vulnerabilities. The study emphasizes the need for increased economic diversification, support for the tourism sector through effective policies, and a review of exchange rate policies. It also highlights the importance of tailoring growth strategies not just based on average performance but also according to different levels of economic outcomes.
Sustainable Development Challenges in Central Asia: Empirical Evidence on the CO2-Growth-Energy-Employment Nexus
The following paper analyzes relationships between CO2 emissions, economic growth, total energy consumption, and employment across five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) over the period between 1992 and 2022, and uses panel econometric methods to do so. Annual World Bank data has been log-transformed to improve statistical properties and interpret coefficients as elasticities. The empirical strategy includes panel unit root tests (LLC, IPS, ADF-Fisher, PP-Fisher), Pedroni cointegration test, Pooled Mean Group-Autoregressive Distributed Lag (PMG-ARDL) estimation, Dumitrescu-Hurlin panel Granger causality tests, and Forecast Error Variance Decomposition (FEVD). The results have shown the variables to be first-order integrated and have a long-run equilibrium relationship. The short-term analysis has revealed an economic growth’s unidirectional effect on CO2 emissions, indicating a direct deterioration of the environmental situation against economic activity expansion. The long-term analysis has shown how economic growth, energy use, and employment jointly determine emission dynamics while adjustments occur based on the emissions indicator. The variance decomposition has revealed GDP and energy use to be the key long-term determinants and insignificance of employment’s effect. Recommendations include reducing energy intensity, developing low-carbon energy, diversifying the economy, creating green jobs, and strengthening regional cooperation.
Environmental-Related Technology on Ecological Footprint: The Case of Germany
In this study, GDP per capita (GDP), non-renewable energy consumption (NREC), renewable energy consumption (REC), and environmental-related technology (ET) on the ecological footprint (EF) were investigated by applying the Autoregressive Distribution Lag Model (ARDL) using time series data from 1990 to 2020 in Germany. According to the results, in the short-run, GDP, NREC and ET increase the EF, while REC decreases the EF. In the long-run, NREC and ET increase the EF, while GDP decreases the EF. Additionally, FMOLS and DOLS robustness tests support the ARDL results. According to these tests, NREC and ET increase the EF in the long-run. DOLS test results also show that REC and GDP will reduce the EF in the long- run. The reason why the increase in environmental technologies in Germany increases the EF is that the number of patents based on environmental technologies can have a positive impact on the environment after reaching a certain level. Accordingly, it is great importance that environmental- related technologies are designed within a framework that supports renewable energy and serves growth that excludes environmental degradation.
Unveiling the Role of ESG in Ensuring Low-Carbon Energy Transition
Currently, the position of ESG in energy transition is becoming one of the hot research topics in the academia. In this context, this work studies the impact of ESG on low-carbon energy risk in the panel of 148 nations over the period 2000-2023. As an econometric tool, Method of Moments Quantile Regression is employed which is robust method for heteroscedasticity. The estimations reveal that the promotion of ESG reduces low-carbon energy risk across all the quantiles from 10% to 90%. Furthermore, sub-dimension tests are conducted using environmental, social and governance indices of ESG separately. They also show the negative impact on low-carbon energy risk. Overall, the findings are aligned with both theoretical and economic linkages.
The Impact of Primary Energy Consumption, Trade Openness and Foreign Direct Investment on Economic Growth: Evidence from MENA Countries
This research examined how primary energy use, trade openness, and foreign direct investment influence economic growth in seven selected countries in the MENA region. Based on data availability (Algeria, Egypt, Morocco, the United Arab Emirates, Saudi Arabia, Oman, and Qatar) from 2000 to 2023, using three methods: the Panel Pooled Mean Group-Autoregressive Distributed Lag Model (PMG-ARDL), the Panel Fully Modified Least Squares (FMOLS), and the Panel Dynamics Least Squares (DOLS) models to explore the long-term relationships between these factors. The estimation results for PMG-ARDL, Panel-FMOLS, and Panel-DOLS indicate that capital, the labour force, primary energy consumption, and trade openness all have a statistically significant positive impact on economic growth in the MENA region. Foreign direct investment has a statistically significant negative impact on economic growth in the MENA region. In general, these results simply indicate that capital, labour forces, energy consumption, and trade openness are the main drivers of long-term economic growth in the MENA region. The study suggests enhancing investment in human and physical capital, increasing trade openness, and focusing on energy efficiency to stimulate long-term economic growth while reevaluating policies for attracting foreign direct investment and ensuring their alignment with developmental priorities.
Balancing Growth and Sustainability: The Role of Fossil and Renewable Energy in BRICS Economies
This study investigates the relationships between fossil fuel availability, access to renewable energy, economic growth, and CO2 emissions in BRICS countries over the period 1990–2019. Employing FMOLS, DOLS, and Method of Moments Quantile Regression, the analysis reveals that fossil fuel availability and renewable energy access both exhibit a significant negative impact on economic growth in FMOLS and DOLS estimations, suggesting a limited role in driving growth in these countries. However, fossil fuels significantly increase CO2 emissions, while renewable energy access significantly reduces emissions, highlighting their contrasting environmental effects. The quantile regression results further show that fossil fuel availability consistently hinders economic growth across all quantiles but raises CO2 emissions, whereas renewable energy positively influences economic growth and lowers emissions throughout all quantile levels. These findings underscore the complex interplay between energy sources, economic development, and environmental sustainability, offering important policy implications for promoting balanced growth and emission reductions in the BRICS economies.
Can Forests Endure the Energy Race and Ecological Pressures? A VAR Analysis of MINT Countries
This study investigates forest resilience in the face of intensifying energy competition and ecological pressures in MINT countries (Mexico, Indonesia, Nigeria, and Turkey) from 1990 to 2024. Energy competition is represented by renewable and non-renewable energy consumption, while ecological pressures are assessed through environmental degradation, green economic growth, and population density. Using a Vector Autoregression (VAR) approach, all variables are treated as endogenous to capture dynamic feedback relationships. Stationarity tests confirm that most variables are first- difference stationary without long-run cointegration. Granger causality analysis reveals bidirectional relationships between forest area (FA) and non-renewable energy consumption, and between environmental degradation and population density. Unidirectional causality is also found from renewable energy consumption, environmental degradation, and green economic growth to FA; from environmental degradation to renewable energy consumption; and from FA and non-renewable energy consumption to population density. Impulse response and variance decomposition results suggest that non-renewable energy consumption and ecological, such as environmental degradation and population density have a negative impact on FA, whereas renewable energy consumption and green economic growth contribute positively. The findings highlight the urgent need to integrate energy, environmental, and development policies to support forest sustainability amid growing global energy demands and ecological stress.
Energy Consumption and Economic Growth: A Panel Causality Analysis in Eastern Africa
Addressing current and future energy needs alongside economic growth has raised global concerns about the causal relationship between energy use and economic performance, particularly in developing regions facing energy deficits. This study examines this relationship in East Africa, where remarkable economic expansion has coincided with persistently low energy consumption, presenting a paradox over whether energy consumption is a driver or merely an outcome of economic growth. The analysis uses annual panel data from 13 countries for the period 2012-2021, applying an augmented neoclassical growth model as the analytical framework. The Dumitrescu and Hurlin panel causality test and a two-step system GMM estimator are employed to assess the nature of causality and the effects of energy on growth. Results reveal unidirectional causality from energy consumption to economic growth, supporting the growth hypothesis. Energy consumption has a positive effect, while energy prices exhibit a significant negative impact. Capital formation, though statistically significant, shows a negative relationship, suggesting inefficiencies or misallocation. Labor shows a causal link to growth, though not statistically significant in the dynamic model. The study recommends that regional energy-growth policy actions focus on expanding energy infrastructure to increase energy consumption, stabilizing prices, and improving capital investment to foster regional economic growth.
The Nexus of Energy Consumption and Economic Growth: A Case Study of the East Asia and Pacific Region
Energy plays a vital role in the economic development of most countries. However, the relationship between energy consumption and economic growth remains a subject of ongoing debate within academia. Some studies suggest that energy consumption drives economic growth, while others indicate an inverse effect or no clear correlation. This study aims to assess the impact of energy consumption on economic growth in countries within the East Asia and Pacific region. Research data was collected from the World Development Indicators and the International Energy Agency for the period 2001–2024. The estimation method employed is Feasible Generalized Least Squares, which effectively controls for econometric issues such as heteroscedasticity and autocorrelation in panel data. The research findings reveal that energy consumption has a negative impact on economic growth in the East Asia and Pacific region. In other words, increasing energy consumption not only fails to boost growth but may also hinder economic development in this area. This finding carries a significant implication for policymakers: reducing energy consumption, coupled with enhancing energy efficiency and promoting a transition to cleaner energy sources, could be an appropriate strategy to ensure sustainable growth while mitigating negative impacts on the environment and long-term economic stability.
Hierarchical Mixed-Effects Modeling of Socioeconomic Factors Influencing Renewable Energy Adoption: A Case Study in the Western Balkans
The Western Balkans encounter significant challenges in their pursuit of EU accession, necessitating accelerated renewable energy deployment and enhancement of energy security to achieve the objectives of the European Green Deal. Three-tier models evaluate renewable energy capacity data from IRENA covering the period from 2000 to 2024, with World Bank socioeconomic indexes and EU accession criteria. Spatial correlation structures encapsulate technological diffusion impacts among proximate nations, employing LASSO regularization for variable selection and leave- one-country out cross-validation for model validation. The advancement of EU candidacy is strongly associated with renewable growth (2010-2024). Serbia (3,413 MW), Albania (2,827 MW), and North Macedonia (1, 633 MW) have the highest absolute capacity levels, driving regional development. The amount of renewable energy that can be used in the region grew by 98% from 5, 709 MW in 2000 to 11,305 MW in 2024. Hierarchical mixed- effects models can explain 79.6% of the differences in deployment patterns, estimating a controlled annual growth rate of 5.3% expansion in each region every year (P < 0.001). The progression of economic and institutional structures via EU accession promotes adoption, while spatial dynamics suggest that coordinated policies may improve efficiency, thus informing strategies for post-transition economies.
Factors Affecting Urban and Rural Household Electricity Demand in South Sulawesi Province, Indonesia
This study aims to analyze the factors influencing household electricity demand in urban and rural areas of South Sulawesi Province. The seven independent variables used in this study include electricity price, household income, number of family members, electronic device ownership, education level, number of rooms, and a dummy variable for urban-rural areas. The analysis method used was multiple linear regression with a quantitative approach based on data from 400 household respondents. The results show that household income, number of family members, electronic device ownership, number of rooms, education level, and the dummy variable for urban-rural areas have a positive and significant effect on electricity consumption. Conversely, electricity price has a significant negative effect. This finding indicates that household economic and physical characteristics are more important determinants of electricity demand than social factors. This study recommends electricity tariff policies tailored to household socioeconomic conditions and improved energy access and education, especially in rural areas.
ESG Crypto-Assets and Environmental Signals in the Energy Transition: A Quantile-Frequency Perspective
This study examines the dynamic interconnectedness between ESG-oriented crypto-assets, traditional cryptocurrencies, equity markets, and environmental attention related to digital assets, within the context of the global energy transition. Using a quantile-frequency connectedness framework, the analysis captures heterogeneous spillover effects across market regimes and investment horizons, focusing on systemic risk and sustainable portfolio design. The results indicate significant linkages between ESG crypto-assets and conventional cryptocurrencies, especially under extreme market conditions. ESG digital assets offer diversification and hedging benefits during bearish phases, while displaying predictive influence on equity markets in bullish states. Environmental attention on cryptocurrencies, considered as a behavioral proxy, reveals weak and unstable connectedness patterns, suggesting its limited systemic role. Spillovers are mainly concentrated at short-term frequencies, highlighting the long-term diversification potential of ESG crypto-assets. From a portfolio perspective, connectedness-minimizing strategies outperform traditional variance-based approaches under stable conditions, achieving better risk-adjusted outcomes. These findings provide practical insights for investors and policymakers by underlining the value of incorporating ESG-oriented digital assets into sustainable investment frameworks. The study contributes to the ongoing discussion on integrating climate-conscious instruments into financial systems while addressing systemic risk transmission in the digital asset space during the global energy transition.
Exploring Economies of Scale in Household Energy Consumption across Seasons and Uses
The implementation of carbon pricing, without accounting for economies of scale in household energy consumption, may disproportionately impact smaller households. This study utilizes data from a survey of Japanese households to investigate variance in energy consumption patterns in response to household composition, energy source combinations, and weather conditions. First, we define the minimum energy requirement (MER) as the energy consumed during the month of lowest usage and analyze the influence of household consumption on the MER. Our findings indicate a notable economy of scale in household energy consumption; however, the extent of this effect varies across households utilizing different energy source combinations. Next, we examine how household composition impacts winter energy usage (WEU) by analyzing the energy consumption growth rate, expressed as the ratio of the WEU to MER. The results demonstrate a higher growth rate among lower-income households. Additionally, household composition and the choice of energy sources significantly influence the energy consumption growth rate. Households use energy for various purposes, and economies of scale are likely to differ across these uses. We classify the purposes of energy use into five categories, namely space heating, space cooling, hot water supply, cooking, and appliance use, and estimate the economies of scale for each. The results suggest that per capita energy consumption for space heating, cooking, and appliance use decreases significantly as the number of household members increases.
Analyzing the Interplay of Industrial Growth, Energy Use, and Employment in Turkiye: A Least Squares Approach
The aim of this study is to examine the relationship between the development of the industrial sector, employment rates and energy consumption in Turkiye. The annual data series between 2001-2020 is used in the research. According to the LCC regression results, the F test is significant and the significance coefficient R2 has a value of 0.3698. These two results show that the independent variables used in the model together are statistically significant in explaining the dependent variable, and the model explains about 36% of the increase and decrease in employment rates, which is the dependent variable. According to the results of the t-test, which shows whether the coefficients obtained for the independent variables are statistically significant, while the coefficients calculated for energy consumption are significant from the 95% confidence interval, the coefficient calculated for the industrial sector growth is meaningless.
ESG Disclosure, Intellectual Capital, and Firm Value in the Energy Sector in Indonesia: The Moderating Role of Firm Size
This study aims to analyze the impact of Environmental, Social, and Governance (ESG) disclosure, Intellectual Capital (IC), and capital structure proxied by Debt to Equity Ratio (DER) on Firm Value (FV), with Firm Size (FS) as a moderating variable, in energy sector companies listed on the Indonesia Stock Exchange (IDX) for the 2021-2023 period. Using a panel data regression method on 31 companies, this study found that ESG disclosure had a positive and significant effect on FV. However, IC did not show a positive impact on FV, even tending to be negative in Model 1, indicating that the market has not fully valued this intangible asset in the energy sector. Meanwhile, DER showed contradictory results (positive in Model 1, negative in Model 2), reflecting sensitivity to model specifications. FS itself had a negative and significant effect on FV, implying diseconomies of scale or agency problems in large companies. The important moderating role of FS is evident in its adverse moderating impact on the relationship between ESG and FV, where larger firms are less effective in translating ESG disclosure into higher value. Conversely, FS positively moderates the relationship between DER and FV, indicating that larger firms utilize debt more optimally. However, FS does not moderate the relationship between IC and FV. This research provides critical insights for investors and management of energy sector companies, particularly in addressing the complex relationship between sustainability practices, intangible assets, financing structures, and market value amid the global energy transition.
Input Energy Price Volatility and Profitability in Vietnam’s Steel Industry: A Panel Data Approach
The steel manufacturing industry is one of the most energy-intensive sectors, making it highly sensitive to input cost fluctuations, especially raw material and energy prices. This study investigates the impact of key input price volatility - including iron ore, coking coal, and fuel oil - on the profitability of listed steel companies in Vietnam between 2019 and 2024. Using panel data of ten publicly traded firms and applying robust estimation techniques including Pooled OLS, Fixed Effects, and Feasible Generalized Least Squares (FGLS), the study evaluates how variations in input costs affect return on equity (ROE), a proxy for financial performance. The empirical results reveal that rising prices of coking coal and fuel oil have a significantly negative effect on profitability, whereas fluctuations in iron ore prices exhibit a more complex and less consistent impact. Additional control variables such as exchange rate and financial leverage also contribute to profitability volatility. The findings underscore the vulnerability of energy-dependent industrial sectors in emerging markets to raw material cost shocks, particularly under global supply disruptions and geopolitical tensions. This paper provides policy implications for risk mitigation, suggesting that firms in the steel sector should adopt hedging strategies and diversify energy sources, while national policymakers should consider strategic stockpiling and tax incentives to stabilize energy input costs. The results also add to the literature on energy price transmission and profitability under uncertainty in transitional economies.
Forecasting Carbon Emission Allowance Prices With Deep Learning Models
As the effects of the climate crisis deepen, the measures taken against it are increasing. These precautionary mechanisms significantly affect companies. One of these mechanisms is carbon trading systems, which limit companies’ carbon emissions. These systems create additional costs for companies, and predicting these potential costs is crucial today. For this reason, the importance of correctly estimating carbon permit prices has increased. To estimate carbon permit prices, the correct variables must first be determined. Many factors affect the carbon markets due to their complex nature. Using the correct estimation method is another important issue. Traditional econometric models cannot clearly explain the complex structure of the carbon market, resulting in low accuracy. In this direction, artificial intelligence-based estimation models have been developed to estimate carbon permit prices. This study estimated the prices of European Union Emissions Allowances (EUA) using energy and power market prices and the economic outlook. The estimation model utilized deep learning algorithms, which are feedforward neural networks and recurrent neural networks (Elman). As a result of the study, both models were successful, and strong accuracy was obtained. While the FFNN model provided more stable and low-variance results, the Elman model provided advantages in short-term predictions.
Dynamic Impacts of Energy Consumption on Agricultural Growth in Iran and Selected Developing Countries
Many countries across the globe are facing difficulties in meeting energy demand in their production sectors. Non-renewable feature of fossil fuels necessitates enhancing their efficiency in all economic sectors including agriculture. Touching this goal, requires reliable evidence on the impact of energy on sectoral economic growth. This study aims at estimation of the effect of energy use on agricultural growth in selected developing and developed nations. We applied country panel data, conventional parametric and non-parametric approaches as our materials and methods. Our findings show that the impact of energy use on agricultural growth varies over time in both groups of countries indicating its dynamic influence. In addition, the non-parametric approach captures such an impact in a better manner. Keeping sustainable growth and environmental concerns in mind, agricultural energy efficiency promotion in high carbon dependent countries through technology investment is recommended.
Impact of Climate Change and Climate Hazzards on Individual Livelihood Vulnerability: Can Climate Finance-backed Initiatives Be a Solution?
Despite its limited resources, Bangladesh currently faces the challenge of minimizing the detrimental consequences of climate change and climate hazards while simultaneously fulfilling its obligations for climate change adaptation. As a result, it is imperative to conduct a comprehensive examination of the efficacy of Bangladesh’s climate financing in mitigating its vulnerability to climate change. Thus, this study aimed to investigate the impact of climate change and climate hazards on individual livelihood vulnerability, as well as the mitigation and adaptation strategies enabled by climate finance-backed programs. We have administered a structured questionnaire to 406 respondents from various coastal regions of Bangladesh, including Barishal, Khulna, and Chattogram divisions. Additionally, we have developed 12 hypotheses based on the existing literature to explore the study objectives. With Smart PLS 4.1.0.0, we implemented the PLS algorithm and a bootstrapping test. The study’s results indicated that the incidence of climate change catastrophes has a substantial impact on the vulnerability of individuals’ livelihoods to climate change, as well as their human, social, financial, physical, and natural capital. Our research also demonstrated that the implementation of measures to alleviate and adapt to climate change and its hazards could potentially mitigate the susceptibility of livelihoods to its adverse effects. At present, Bangladesh’s mitigation and adaptation strategies are inadequate. The implementation of methods to mitigate and adapt to climate change and climate risks has validated Bangladesh’s climate finance-backed programs. This study offers substantial insights into Bangladesh’s climate-related challenges, which will mitigate the vulnerability of livelihoods to the effects of climate change.
Mapping Current Trends in Electricity-Saving Behaviour: A Bibliometric Study
This study explored 1,230 publications related to electricity-saving behaviour (ESB), extracted from the Web of Science database. Prior to 2010, research in this field was limited, with fewer than 20 publications per year. The results show that academic interest in the field has risen sharply since 2015, with a peak of over 160 publications in 2021. This growth reflects increasing concern over sustainable energy and climate change, as well as interest in influencing individual and household behaviours related to energy reduction. While the study of ESB is relatively young, it has developed quickly. Analysis of institutional contributions revealed the U.S. Department of Energy, the Beijing Institute of Technology and the University of California to be the top contributors, indicating their significant research accomplishments and a commitment to sustainability research. ESB is a globally important subject with contributions from a range of countries. China was the top contributor with nearly 370 publications, followed by England, Italy, India and Spain. VOSviewer was used to visualise keyword co-occurrence, revealing significant clusters around “behavior,” “energy efficiency” and “conservation.” The keyword analysis also revealed a significant shift from a focus on technological initiatives, such as “smart meters” and “buildings,” to an emphasis on the psychological and environmental components of “habit,” “climate” and “residents” in more recent studies. Together, the findings demonstrate the interdisciplinary nature and increasing complexity of ESB research and have significant implications for future research and policy in the field of energy conservation and sustainable development.
Growth and the Environment in Sudan: Myth or Reality of the EKC Hypothesis?
The link between economic development and environmental outcomes has become increasingly evident. The study examines how economic growth influences environmental degradation in Sudan, using annual time series data spanning 1980-2022. The analysis accounts for potential structural breaks in unit root and cointegration testing. An Autoregressive Distributed Lag model is employed to assess the long-run relationship. The Environmental Kuznets Curve hypothesis is evaluated using three different approaches. Findings indicate that the EKC does not hold in the case of Sudan. The results suggest that, as developing a country, Sudan’s income level remains below the threshold at which economic growth would start to reduce environmental harm. The study also highlights the significant impact of energy consumption on the country’s carbon emissions. To address these challenges, robust and well-enforced environmental policies are recommended to mitigate the adverse effects of future generations.
Investigating the Effect of Green Productivity and CO2 Emissions Intensity in Developed and Developing CPTPP Countries: An Application of Panel Threshold
Rising CO2 emissions, a major driver of climate change, demand urgent measures to reduce fossil fuel dependence, adopt clean technologies, and promote sustainable development. This study examines the relationship between green productivity and CO2 emissions intensity among CPTPP nations from 2001 to 2021 using panel data and econometric models, including panel Autoregressive Distributed Lag (ARDL) tests, panel Fully Modified Ordinary Least Square analysis (FMOLS), and a panel threshold model. The results reveal a U-shaped relationship, aligning with the Jevons Paradox but diverging from the conventional EKC hypothesis. Specifically, green productivity improvements initially result in higher emissions, but they lead to environmental benefits beyond a certain threshold of technology use. These findings highlight the critical need to balance economic growth with environmental protection through enhanced green productivity. The study also underscores that the effectiveness of the green economy varies across countries, emphasizing the importance of tailoring green economic strategies to the unique conditions of developed and developing nations to achieve a win-win outcome for climate health and economic progress.
Energy Independence Risk and Energy Policy Risk: Theory and Empirical Testing
The study investigates the unique relation in the middle of regulatory risk in the energy sector and energy independence risk across 135 countries from 2000 to 2023. The method of moments quantile regression (MMQR) is conducted for the empirical estimations along with the second generation methods such as CIPS unit root and Westerlund cointegration tests. The outcomes illustrate a vital positive effect of power policy risk on energy independence risk across all the (10%-90%) quantiles of the regression. The policy implications are provided to consider the function of energy policy in achieving fuel independence.
Governance Moderation in ESG Impact: Market Value Shifts Pre- and Post-COP 21 in the Oil and Gas Sector
This study examines the effect of ESG performance on firm market value in the oil and gas sector, using 6,872 firm-year observations from 52 countries (2011–2022). A two-stage least squares (2SLS) regression is employed to address endogeneity, with institutional governance government effectiveness, regulatory quality, and control of corruption tested as moderators. Results show ESG positively impacts firm value only after COP21. Institutional quality enhances firm value but weakens ESG’s marginal effect. The findings highlight the conditional nature of ESG’s value relevance and offer implications for firms, investors, and policymakers in varying governance contexts.
Fostering a Green Future: The Role of Environmental Education in Community Empowerment
The present research examines how community engagement, community empowerment, and environmental education affect environmental sustainability in the industrial sector of Pakistan particularly among the working employees of the HEIs. A survey research design was adopted and a self-developed structured questionnaire adopted from research conducted in similar studies was used in gathering data from 322 participants in different capacities in HEIs. The participants included clerical workers up to managerial level like deans of the colleges to increase the generalizability of the results. Smart partial least squares structural equation modeling was employed to analyze the data to explore the links between the constructs under investigation as well as their impact on environmental sustainability. The analysis showed that there were positive relations between community engagement and environmental education and environmental sustainability and that community engagement had the strongest relationship. Community empowerment was another variable that was positive with environmental sustainability albeit with a much smaller effect size compared to the others. Community engagement and community empowerment were discovered to have a limited moderating effect which has led to the understanding that their direct contribution to sustainability is greater than their moderation role. Therefore, the results highlight the need to continue encouraging community participation and environ mental awareness in order to encourage sustainable behavior. The findings of this research would be of great interest to policymakers, educators, and industry players interested in bolstering environmental sustainability initiatives within the Pakistani industry.
Who Turns the Green Gear? Stakeholder and TPB, Environmental Uncertainty, and the Finance Innovation Performance Chain in Chinese SME
Chinese small and medium-sized enterprises experience pressure to be “green” in pursuit of green finance, as the Chinese government has established dual-carbon goals in addition to the Sustainable Development Goals (SDG). This paper applies the Theory of Planned Behaviour, Stakeholder Theory, and the concept of environmental uncertainty to explain the process by which green finance intentions lead to green innovation and to further understand the sustainability implications in terms of their impact on triple-bottom-line performance. Drawing on a SmartPLS analysis of 526 SMEs across nine Chinese cities, we find that managers’ green attitudes and peer-driven norms are the primary drivers of financing intent; self-efficacy and supportive conditions indirectly boost intent via perceived control. Green leadership and environmental literacy forge positive attitudes, while regulatory and competitive signals reinforce norms. Once intention crystallizes into funding, SMEs unlock green innovations that yield clear economic, social, and environmental returns. Even amid turbulence, regulatory mandates and managerial confidence remain reliable anchors. These findings provide a roadmap for policymakers to issue stable and transparent green finance mandates. Financial institutions can tailor their credit based on behavioral cues, and SMEs should invest in leadership and capacity building.
The Impact of Trade on Environmental Quality and Sustainable Development in ASEAN Region
This study investigates the impact of trade on environmental quality and sustainable development in the ASEAN region, focusing on the long-term implications of trade liberalization under the ASEAN Free Trade Area (AFTA). While trade has played a central role in boosting economic growth and regional integration, concerns about its environmental consequences have intensified, particularly with rising carbon emissions, resource depletion, and ecological degradation. Using a dynamic Autoregressive Distributed Lag (ARDL) modeling approach, this study explores the relationship between trade openness, carbon dioxide (CO2) emissions, and adjusted net savings as proxies for environmental sustainability and sustainable development. The empirical findings reveal a significant and negative long-run relationship between trade openness and both CO2 emissions and adjusted net savings. This suggests that, without robust environmental and social safeguards, increased trade activities may exacerbate environmental degradation and compromise the region’s long-term development goals. In contrast, the short-run effects appear weaker and mostly insignificant, implying that the detrimental impacts of trade develop progressively over time. These results challenge the conventional assumption that trade liberalization automatically promotes sustainable development. In the context of ASEAN, trade-driven growth may undermine environmental commitments outlined in the Sustainable Development Goals (SDGs), particularly those related to climate action and responsible consumption. The study underscores the urgent need for ASEAN policymakers to integrate trade policy with comprehensive environmental regulations to ensure that economic integration aligns with sustainability principles and intergenerational equity.
Crude Constraints: Oil Price Asymmetries and the Growth Path of Saudi Arabia’s Services Sector
This study explores the dynamic relationship between oil dependency and the growth of the services sector in Saudi Arabia over the period 1980–2023. Using both linear Autoregressive Distributed Lag (ARDL) and nonlinear ARDL (NARDL) models, we examine whether oil price shocks exert symmetric or asymmetric effects on the share of services in GDP. The results reveal that oil rents significantly reduce the services sector’s contribution in the long run, highlighting structural dependencies within the economy. Short-run dynamics vary across macroeconomic indicators, with real oil prices showing more immediate but less persistent effects. The NARDL model provides new insights, uncovering strong asymmetries: negative oil price shocks have a greater and more significant adverse impact on services value added than positive shocks, both in the short and long term. Unit root tests support the ARDL framework, and bounds testing confirms cointegration. These findings underscore the challenges of reducing oil dependence and suggest that economic diversification strategies under Saudi Vision 2030 must account for the asymmetric vulnerabilities introduced by oil price volatility.
Short and Long-Term Analysis of Relations between Transportation and Industrial Sectors Energy Consumption and Foreign Trade in New Industrialized Countries
This study investigates the effects of transport sector energy consumption, industrial sector energy consumption and imports on exports in Newly Industrializing Countries (Mexico, Turkey, Brazil, China, India, Indonesia, South Africa and Thailand). In the study, using data for the period 1990- 2022, tests that take into account horizontal cross-section dependence and heterogeneity and long and short-run analyses at panel and country level were applied. As a result of the study, it is found that transportation sector energy consumption has a negative effect on exports and imports have a positive effect on exports in both short and long run. Moreover, the negative effect of transportation energy consumption decreases from the short-run to the long-run, whereas the positive effect of imports increases from the short-run to the long-run. In addition, it is determined that the positive effect of imports on exports is higher than the negative effect of transportation energy consumption in both the short and long run.
Drivers Influencing Green Growth in ASEAN Countries: The Role of Corruption Control, Foreign Direct Investment, Energy Consumption, and Financial Development
This study analyzes the impact of control of corruption, foreign direct investment, energy consumption, and financial development on green growth in ASEAN countries during the period 2002-2021. Applying panel data with feasible generalized least squares regression and quantile regression, the results show that control of corruption and financial development positively impact green growth. In contrast, foreign direct investment negatively and inconsistently impacts green growth. Quantile regression results show that the positive impacts of control of corruption and financial development are more pronounced in countries with high green growth. In contrast, foreign direct investment shows a substantial negative impact at high quantiles, implying the need to be more cautious with foreign direct investment projects during green growth aims. Factors such as population growth, urbanization level, service sector value added, and forest area all have negative impacts in most quantiles, emphasizing the urgency of effectively managing these factors to ensure sustainable green growth. Based on the empirical results, policy implications are recommended for ASEAN countries and emerging nations.
Analysis of a Log-Linear Model for Forecasting Electricity Demand Based on Economic Growth in Colombia
This study analyses the relationship between the Gross Domestic Product and Electricity Demand in Colombia. The development of these forecasting models supports long-term electricity sector planning. The study used annual data from 2006 to 2023 to construct two regression models—one linear correlation and the other log-linear. Actual data for 2024 were used to validate the predictive capacity of both models. Indicators such as R2, MAE, RMSD, and MAPE were used to evaluate the fitting period. The results show that the log-linear model achieved greater accuracy, with an MAPE of 1,30% in the fit and an error of 0,58% in the validation of the 2024 data. This approach demonstrates the usefulness of incorporating logarithmic transformations in energy models to obtain a more robust fit between economic and energy variables.
Investing in the Future: Clean Energy, Technological Advancement, and Environmental Quality as Catalysts for Foreign Direct Investment: Evidence from SSA
This study investigates the influence of clean energy, technological innovation, and environmental quality on foreign direct investment (FDI) inflows in sub-Saharan Africa (SSA). Employing panel data from 2004 to 2022 across SSA countries, the study applies advanced econometric models, including CS-ARDL, DOLS, panel cointegration, and Dumitrescu-Hurlin causality tests to assess long- and short-term dynamics. The results reveal a strong long-run cointegration between FDI and clean energy, technology, and environmental quality. Clean energy infrastructure and technological advancements are positively associated with FDI inflows in the short and long terms. Environmental quality, proxied by CO2 emissions and institutional strength, exhibits bidirectional causality with FDI, indicating a mutual reinforcement. Education and institutional quality exert unidirectional impacts on FDI, suggesting their foundational roles in fostering investment readiness. These relationships underscore the importance of aligning national strategies with sustainable development goals to attract ESG-conscious investors, particularly in contexts with improved environmental governance and innovation ecosystems. Unlike prior research focusing on isolated determinants, this study triangulates clean energy, technology, and environmental governance within a unified framework to address their interactive effects on FDI. It introduces a sustainability-driven model tailored to SSA, offering an empirical foundation for evaluating long-run equilibrium and causality among ESG-relevant variables in developing regions. SSA governments should incentivize clean energy, fortify environmental regulations, and invest in digital infrastructure and education to enhance investor confidence and ensure that FDI aligns with inclusive and sustainable growth trajectories.
Energy Management Practices, Renewable Energy Supply Chain, Government incentives and Environmental Performance among Manufacturing Firms
This study examines how energy management practices (EMPs), renewable energy supply chains (RENSC), and government incentives (GOVI) influence environmental performance (ENVP) among manufacturing firms in Oman. Drawing on the Resource-Based View, Natural Resource-Based View, and Dynamic Capabilities Theory, EMPs and RENSC are framed as internal capabilities, while GOVI serves as an external enabler. Data from 308 firms were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that management commitment, energy awareness, knowledge, and audits significantly enhance environmental performance. RENSC also directly improves ENVP and mediates the EMP–ENVP relationship. Moderation analysis reveals that government incentives strengthen the positive effects of management commitment, energy knowledge, and renewable energy supply chains on environmental outcomes. Despite policy support under Vision 2040, the adoption of renewable energy technologies remains limited. The study calls for firms to invest in dynamic energy capabilities and green supply chain integration, while urging policymakers to implement targeted, performance-based incentives. Situated in an underexplored national context, this research offers novel insights into how internal resources, operational systems, and institutional support interact to drive sustainability in resource-constrained economies, thus advancing theory and practice in environmental management.
Forecasting UAE Electricity Consumption by Sector Using the NDGM Model, Based on Data from 2012 to 2021
This work advances the efficiency of electricity demand forecasting in the United Arab Emirates (UAE) by utilizing the Non-Homogeneous Discrete Grey Model (NDGM) to predict electricity consumption from 2022 to 2040, with a focus on analyzing different sectors, filling up research gaps in this area. Based on historical data from 2012 to 2021, our model achieves a Mean Absolute Percentage Error (MAPE) of approximately 0.15%, indicating high accuracy. This makes our results more useful for energy planners and policymakers who want to make sure that supply matches demand and avoid overinvestment or load shedding. We also examine electricity use from a sector-specific perspective; a viewpoint that hasn’t been explored in previous research. Furthermore, our analysis uses data from sources that are specific to the UAE, like the Department of Energy in Abu Dhabi, DEWA, SEWA, and FEWA. The analysis includes sector-wise consumption for 2021, Relative Growth Rate (RGR), and Doubling Time (Dt) metrics. Results show future steady demand growth, with commercial and residential sectors dominating. These insights support sustainable energy planning and highlight the need for efficiency measures in high-consumption sectors. We offer some recommendations specific to the UAE that explain our empirical results and help policymakers of the country in making appropriate decisions about the future desired electricity supply.
Redesigning Sustainability: How Renewable Energy and Eco- Innovation Shape Ecological Footprints in Leading Tourist Destinations
This study investigates the environmental determinants of ecological footprint in the top 25 tourist destination countries. The primary objective is to assess how renewable energy consumption, green growth, environmental innovation, and financial development influence ecological sustainability. Using annual data from 2002 to 2022, the study applies second-generation econometric techniques, including DSUR, CUP-FM, CUP-BC estimators, and Dumitrescu-Hurlin panel causality tests to account for cross-sectional dependence and heterogeneity. Results confirm that renewable energy consumption, green growth, and environmental innovation significantly reduce the ecological footprint, while financial development has a detrimental effect. Bidirectional causality exists between the ecological footprint and key predictors, except financial development, which shows a unidirectional link. The findings validate the Environmental Kuznets Curve (EKC) hypothesis. The study’s novelty lies in its focus on tourism-intensive economies and the integration of innovation and green policy variables into an ecological footprint framework, which remains limited in prior research. It contributes methodologically by applying robust second-generation estimators. Policy recommendations include enhancing investment in clean energy, promoting green innovation, and integrating sustainability into financial decision-making to align tourism growth with ecological resilience.
Renewable Energy, Innovation and Adaptation to Climate Change: Evidence from Europe and Central Asia
The aim of this research is to examine the effect of renewable energy consumption and innovation on adaptation to climate change in Europe and Central Asia over the period 2000-2021. In this study, we use several panel data methods such as fixed effects method, two step system GMM estimator and panel corrected standard errors estimator to account for endogeneity, simultaneity and cross-sectional dependence. Our results show that renewable energy has overall positive link with adaptation to climate change, proxied by ND Gain index. We also document that innovation measured by number of patents has positive effect on ND Gain index in Europe and Central Asia. We conduct robustness tests by including additional socio-economic variables. The results remain robust. The study offers policy implications and suggests avenue for future research.
Rural Energy Access and Agricultural Productivity in South Africa
Access to energy is critical for agricultural productivity and it directly contributes to the promotion of a more commercialized agricultural sector. South Africa embarked on massive electrification programme across the country with the sole aim of promoting access to electricity in the country from 34 percent in 1991 to 77 percent in 2002 and to 85 percent in 2018 but the access to electricity more skewed to the urban areas than the rural areas. This arrangement has a more serious implications on the productive and economic activities located in the rural areas of South Africa since most agricultural related activities takes place in the rural provinces of the country. Therefore, issues related to access to electricity, especially in the rural areas, are crucial for the overall growth and development of the country since it largely determines the viability and productivity of agro-allied industries. Empirical studies conducted in South Africa mainly concentrated on energy policy guarding the provision of energy for industries and population living in the urban areas but largely neglects the relevance of rural energy access as a catalyst for agricultural productivity in South Africa. Hence, this study is premised on a Cobb-Douglas production function which describes the relationship between agricultural productivity as a function of access to electricity. The study found that rural energy access has a significant negative influence on agricultural productivity in South Africa. While urban energy access promotes promote agricultural productivity in South Africa. The result further indicates that labour force participation rate, gross fixed capital formation and adequate rainfall were seen to be relevant drivers of agricultural productivity in South Africa.
The Role of Natural Resources, Electricity Production, Economic Globalization, and R&D in CO2 Neutrality: An Empirical Investigation for Kuwait
At the 27th conference of parties in Egypt, Kuwait declared the environmental agenda of turning carbon neutrality by 2050, and many nations have started progressing towards carbon neutral agendas. Environmental research and development are essential factors in achieving these goals. This paper examines the relationship between natural resources, R&D, electricity production, economic globalization, and CO2 emissions in Kuwait from 1975 to 2020. We employed unit-root tests to verify the integrative properties of the variables. Additionally, the FARDL method was used to analyze the relationship between the variables. The Fourier Toda-Yamamoto causality test is applied to explore the causal links between natural resources, economic globalization, electricity production, R&D, and CO2 emissions. The empirical findings reveal that these variables are cointegrated and imply long-run relationships. Moreover, R&D expenditures reduce CO2 emissions, while natural resources, electricity production, and economic globalization increase CO2 emissions. Based on the empirical results, this study suggests attaining the targets of SDG-07(clean and affordable energy), SDG-09 (R&D, innovations), and SDG-13 (climate change).
Effectiveness of Climate Related Development Finance in Reducing Greenhouse Gas Emissions of Selected African Countries: The Role of Source and Recipient Country Income Levels
Despite CRDF allocation opportunities since the Kyoto Protocol in 1997, greenhouse gas emissions in developing countries remain high. Existing evidence on the CRDF-GHG emissions nexus is based on aggregate climate finance without also considering the impact of recipient income levels. This study examined the effectiveness of climate-related development finance in reducing GHG emissions, examine the role of CRDF sources in emissions reduction, and assess the influence of recipient country’s income level. The study used panel data from selected African countries (Botswana, Burkina Faso, Cameron, Ethiopia, Ghana, Kenya, Tanzania, Zambia, and Zimbabwe). Pooled OSL, Random Effects and Fixed Effects were used to analyse the relationship between GHGs emissions as the dependent variable and CRDF, CRDF sources, and recipient income levels as independent variables. The results revealed a significant negative relationship between aggregated CRDF and GHGs emissions. An increase in CRDF leads to investment in mitigatory measures that subsequently decrease GHGs emissions. Furthermore, the study found that CRDF sources have significant heterogeneous effects on developing countries' GHGs emissions where CRDF from Asia result in significant reductions in GHG emissions, while CRDF from Europe increases emissions. The interaction between CRDF and recipient incomes was also found to significantly increase emissions. The study highlights the critical role of CRDF in reducing GHG emissions in the selected African countries. The study recommends a continuous flow of CRDF to developing countries, prioritizing funding sources from Asia complemented by measures to decouple economic growth from emissions thereby further enhancing the effectiveness of CRDF in reducing GHG emissions.
Nonlinear Causal Relationship between Oil Prices, Global Uncertainty and Investor Sentiments
In recent years, as a result of developments in global markets, the financial decision-making mechanism of individuals has become one of the most debated topics. In the literature, despite the fact that linear relationship between energy market and investor sentiment is investigated, usually traditional tests are applied. Further, uncertainty conditions at the global level are not taken into account within the frame of markets and sentiment relations. The relationship between oil prices and investor sentiment is outstanding for asset allocation and portfolio risk management under conditions of uncertainty. This research paper examines the connection between energy market, global uncertainty and investor sentiment using monthly data between 2004 and 2024. In the analysis, firstly, it is examined that whether the series are linear or not employing linearity test. Then, quantile causality test is applied to the series that are determined to be non-linear. Empirical findings provide that investor sentiment cause oil prices while oil prices cause global uncertainty. In addition, global uncertainty and investor sentiment have a mutual causal relationship. Analysis results revealed that investor sentiment significantly affects the energy markets, and there is a strong association between global uncertainty and investment sentiment.
The Social Cost of Growth and Energy Use in Newly Industrialized Countries: The Role of CO₂ Emissions and Renewable Transitions
This study aims to analyze the factors influencing government spending in the health sector in ten newly industrialized countries. Focusing on economic, social, energy, and environmental aspects, this study aims to determine how variables such as economic growth, urbanization, fossil and renewable energy consumption, and carbon dioxide (CO₂) emissions contribute to the social costs of health. The methodology used is panel data analysis with multiple regression, using secondary data obtained from international institutions such as the World Bank and the IEA, processed using Stata 17 software. The results show that economic growth and urbanization significantly increase government spending in the health sector, while fossil and renewable energy consumption negatively affect the social costs of health. In addition, CO₂ emissions and coal consumption do not show a significant effect, emphasizing the importance of sustainable energy management. Based on these findings, recommended policies include increasing investment in renewable energy and environmentally friendly technologies, managing sustainable urbanization, and establishing energy policies that support efficiency and emission reduction. This step is expected to reduce social costs in the health sector while maintaining environmental sustainability, supporting the achievement of the Sustainable Development Goals (SDGs) and improving the quality of life of people in developing countries.
Climate Change Dynamics and the Operational Efficiency: Investigation of JSE-listed Manufacturing Companies in South Africa
Climate change has become a concerning problem for the green environment which causes the planet to deteriorate. The changes in temperatures create major shifts in weather conditions which results in increase in surface temperatures, adding vast quantities of greenhouse gases to those naturally occurring in the atmosphere escalating in the greenhouse effect and global warming. The study desired to help manufacturing companies consider disclosing their information on how climate change and the economic transition will affect their businesses and how they will influence the wider environment and society. This disclosure motivates investors by informing them about climate solutions and how the company is building its resilience against climate impacts so that they can make informed investment decisions. The study compiled data from 2005 to 2022 of JSE-listed manufacturing companies using the Iress database. Econometric techniques such as the panel data dependence technique, pooled multivariate regression, Generalised Method of Moments (GMM), feasible generalized least squares and Pooled Fixed and Random effects have been used for the study.
Renewable Energy and Economic Growth in the United Arab Emirates: A Causal Analysis of CO2 Emissions and Environmental Policy Trends
United Arab Emirates rapid economic expansion, environmental degradation, particularly CO₂ emissions, has emerged as a pressing challenge. The study explores the dynamic relationship between the utilization of renewable energy sources, CO₂ emissions, environmental policy, and economic growth over the period 2000–2023. Applied to yearly time-series data using Granger causality tests and the Autoregressive Distributed Lag (ARDL) model, the research identifies both immediate and long-term variations in equilibrium among the variables. The stationary nature of the variables at the first difference or degree was validated by the Augmented Dickey-Fuller (ADF) test, satisfying ARDL prerequisites. Testing for ARDL boundaries showed considerable long-term cointegration, demonstrating how these variables change in tandem over time. GDP is positively impacted by using renewable energy in a statistically significant way over the long run (coefficient = 0.275) and short term (coefficient ≈ 0.112), according to the data. CO₂ emissions exert a negative influence on long-term economic growth (coefficient ≈ –0.190). Environmental policy contributes positively to growth, reinforcing the role of governance in green transitions. Granger causality analysis further confirms that renewable energy and environmental policy unidirectionally influence GDP, whereas GDP and CO₂ emissions share a bidirectional feedback loop. These results highlight the crucial role of sustainable energy strategies and regulatory frameworks in supporting long-term economic resilience. For policymakers, the study offers actionable insights into how green investments and emission controls can reinforce development goals. Future research should consider sector-level disaggregation and integrate high-frequency or regional comparative datasets to refine policy analysis and advance GCC-wide sustainability efforts.
Macroeconomic Determinants of South African Oil Prices: Evidence from Alternating Market Conditions
The introduction of the adaptive market hypothesis (AMH) allows for the review of the relationship between macroeconomic variables and oil prices, such that the relationship is said to alternate with bull and bear market conditions. In an attempt to contribute to the revised literature, the study examines the influence of macroeconomy on South African (SA) oil index returns. The study incorporates six macroeconomic factors (inflation, money supply, short-term interest rates, long-term interest rates, gross domestic product (GDP), and exchange rate) and SA oil price index returns for the period February 1996 to December 2024. Using the Two-State Markov regime switching mode, the findings indicate that macroeconomic variables have an alternating effect on SA oil index returns. It is evident when macroeconomic factors have a significant effect on SA oil index returns in a bull regime, the effect is insignificant in a bear regime. Hence, SA commodity market, more especially the oil market is not efficient as proposed by the efficient market hypothesis and is better model by asymmetrical models.
Financing the Green Transition: Exploring the Role of Financial Inclusion and Renewable Energy in Driving Green Growth into More and Less Inclusive Financial Systems in the MENA Countries
This research examines the relationship among renewable energy, financial inclusion, and green growth in the MENA region, focusing on how financial access and the adoption of clean energy contribute to green growth. Using a dataset of 12 MENA countries from 2010 to 2023, and applying the System Generalized Method of Moments (SGMM), we examine the individual and interactive effects of financial inclusion and renewable energy on green growth. To account for the considerable heterogeneity within the region, we distinguish between countries with more inclusive financial system, and those with less inclusive systems, where financial access remains limited. As consequently, we used the fixed and random effect. For the full sample, the results reveal that financial inclusion significantly reduces green growth, while renewable energy does not exert any significant effect. For the disaggregate analysis, the effect of financial inclusion and renewable energy differs across countries with more inclusive financial systems, and countries with less inclusive systems. Moreover, the effectiveness of these drivers is strongly influenced by institutional quality and domestic investment. For the combined effect, we found that the interaction between financial inclusion and renewable energy promotes green growth only in countries with more inclusive financial systems, while it reduces green growth in countries with less inclusive systems. The study provides novel, region-specific evidence and offers practical guidance for policymakers to design strategies that align financial inclusion and renewable energy initiatives with long-term sustainability goals in the MENA region.
Examining Ecological Footprints in the backdrop of Institutional Quality, Economic Growth, FDI and Urbanisation
The objective of this study is to identify the impact of economic growth, international trade, cross-border capital movement, institutional quality and urbanisation upon the ecological footprints for the case of India for the period from 2000 to 2024. After checking the data for unit roots and ensuring data stability, the ARDL model was calculated, with bounds test and error correction. The model is able to explain 66.8 per cent of the total changes, bounds test results indicate long-term equilibrium relations among the variables. Error correction term satisfies stability, showing a negative and significant coefficient score of -1.20 rate of returning to equilibrium. Stability and diagnostic tests, recursive estimates indicate significant results. Impulse response function results show an asymmetrical relation with all the dependent variables. Inclusion of institutional quality adds uniqueness to this study, and this paper bridges the gap in identifying the role of institutional factors in impacting ecology considering economic factors and environmental challenges
Renewable Energy Development and Its Contribution to Sustainable Economic Growth in Kazakhstan
This study aims to analyze the relationship between the development of renewable energy sources and sustainable economic growth in Kazakhstan for the period 2000-2024. The study used official national statistical data: gross domestic product (GDP, by production method), labor productivity indices, GDP energy intensity, inflation dynamics, and renewable energy production capacities. In addition, the oil and gas sector, which is the traditional basis of the economy, was considered as a control variable. Methodologically, descriptive statistical analysis, correlation estimation, and econometric models were used. In particular, the autoregressive distributed lag (ARDL) method and the Granger causality test were used to identify short- and long-term relationships. Labor productivity, energy intensity, inflation, and oil and gas sector indicators were included in the econometric model as explanatory variables. Preliminary results show that the development of renewable energy sources has a positive impact on both GDP growth and labor productivity. At the same time, it was found that reducing energy intensity leads to increased economic efficiency. However, it was noted that inflationary volatility and dependence on the oil market limit the volume and sustainability of investments in renewable energy. The results of the Granger causality test revealed that renewable energy production contributes to economic growth. This study is one of the first empirical works to comprehensively analyze the development of renewable energy sources in Kazakhstan in the context of economic diversification. The results have important practical significance in achieving the UN Sustainable Development Goals, in particular SDG-7 (Affordable and Clean Energy) and SDG-8 (Sustainable Economic Growth and Productive Work). Recommendations include strengthening institutional support, increasing investments in renewable energy, and integrating energy efficiency policies into national development strategies.
Trade Openness, Renewable Energy, and Environmental Quality: The Role of Infrastructure in Developed and Developing Countries
This study examines the relationship between trade openness, renewable energy, and environmental quality, with a specific focus on the role of infrastructure in developed and developing countries. To address this objective, we employ a comprehensive panel dataset covering 154 countries over the period 1990 to 2024. To account for heterogeneity across different stages of development, the full sample was divided into 112 developing countries and 42 developed countries, enabling a comparative analysis of the dynamics across contexts. We perform the two-step System Generalized Method of Moments (SGMM) estimator, which effectively addresses potential endogeneity, unobserved heterogeneity, and dynamic relationships among the variables. The findings provide insights that trade openness significantly increases the CO2 emission; renewable energy significantly enhances the environmental quality, while the effect of infrastructure differs across samples. We also found that infrastructure moderates both the trade-CO2 emission and renewable energy- CO2 emissions relationships. Countries in the full sample and developing countries benefit from an interaction between trade, renewable, and infrastructure. These interactional relationships significantly decrease CO2 emissions. Overall, this study contributes to the understanding of the trade–energy–infrastructure-environment nexus and offers policy implications for designing sustainable development strategies tailored to diverse national contexts.
The Dynamic Interplay between Oil Rents, Financial Innovation, and Economic Growth in OPEC Countries: Evidence from a Structural VAR Approach
This paper analyses the dynamic interaction between oil rents, financial innovation, and economic growth among the OPEC countries on the time series 19802023 based on a Structural Vector AutoRegression (SVAR) model. The unit root test proves that the variables are of I (1) thus integrated, whereas the cointegration Johansen test depicts three long-run relationships of equilibrium which is evidence of steady relationship between oil rents, financial innovation and GDP. The SVAR findings indicate that the oil rent shocks impact on the financial innovation is very positive with cumulative impulse response hitting at 0.215 within the period of 24 periods. Forecast Error Variance Decomposition indicates that, oil rents capture 42.87 percent of the variance in financial innovation within one-year horizon, which demonstrates criticality of resource wealth in financial sector dynamics. The strength of the findings is verified through robustness checks. These findings mean that natural wealth may be used to fuel financial innovation and economic expansion subject to healthy institutions. Resource-dependent economies need, therefore, policy measures targeting on improving governance and developing a financial sector.