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The environmental degradation in the Middle East and North Africa (MENA) region leads to significant challenges regarding economic sustainability and the attainment of sustainable development goals (SDGs). The extensive use of fossil fuels in the region, as well as rapid urbanization and economic growth, has led to significant carbon emissions, together with unprecedented ecological footprints compromising environmental sustainability. The study aims to elucidate the influence exerted by technological innovation, trade openness, and natural resources on environmental sustainability in Turkey and Egypt for the period 1990–2022. In assessing the empirical relations, the study employed the Fourier function incorporate estimation techniques, that is, Fourier ADF for unit root test, Fourier ARDL, and Fourier NARDL for long-run and short-run elasticities of technological innovation (TI), trade openness (TO,) and natural resources rent (NRR) on load capacity factor (LCF) and inverted LCF (ILCF); finally, the directional causality evaluate through Fourier TY causality test. The results revealed that both Turkey and Egypt have severe environmental problems due to their high carbon emissions and ecological footprints. Technological change and international trade separately negatively affect environmental sustainability; however, these negative impacts have mixed character. On the one hand, technology can improve efficiency and reduce ecological footprints by obviating the use of high-impact processes or allowing cleaner production systems. In the same vein, trade openness helps transfer green technologies more quickly, but it can also lead to unsustainable resource extraction and pollution. The findings of the paper propose that in order to move forward, Turkey and Egypt need strategic policy shifts to ensure environmental sustainability, including transitioning towards renewable energy from fossil fuels while bolstering their capacity for energy efficiency. Policymakers must balance economic development with environmental conservation to reduce the harmful effects of climate degradation and help safeguard continued economic survival in the face of increasing climatic instability. This research helps to inform policy and investment decisions about how the SDGs can be achieved and how they are relevant for sustainable development in the MENA region.

Policymakers and environmental scientists have proposed numerous measures toward achieving a sustainable environment. Some of these measures include the efficient use of energy and a clean energy transition. This study empirically investigates the role of non-renewable energy efficiency and renewable energy utilization in driving environmental sustainability in India over the period from 1965 to 2018. Using the approach of the Dynamic Autoregressive Distributed Lag (DyARDL) simulations, the empirical evidence shows that non-renewable energy efficiency and renewable energy utilization promote environmental sustainability through an increase in the load capacity factor. The effects of financial development and trade impede environmental sustainability through a decrease in the load capacity factor. The results further show that the relationship between income and load capacity factor is characterized by an inverted U-shape. This suggests that the load capability curve (LCC) hypothesis is not valid for India. Given the overall findings of this study, it is suggested that policymakers should promote energy efficiency and renewable energy technologies as the ultimate policy measure to mitigate the accumulation of CO2 emissions and other significant climatic changes in India.

Technological innovations have been a matter of contention, and their environmental consequences remain unresolved. Moreover, studies have extensively evaluated environmental challenges using metrics such as nitrogen oxide emissions, sulfur dioxide, carbon emissions, and ecological footprint. The environment has the supply and demand aspect, which is not a component of any of these indicators. By measuring biocapacity and ecological footprint, the load capacity factor follows a certain ecological threshold, allowing for a thorough study on environmental deterioration. With the reduction in load capacity factor, the environmental deterioration increases. In the context of the environment, the interaction between technological innovation and load capacity covers the demand and supply side of the environment. In light of this, employing the dataset ranging from 1980 to 2017 for the case of South Africa, the bound cointegration test in conjunction with the critical value of Kripfganz and Schneider showed cointegration in the model. The study also employed the ARDL, whose outcome revealed that nonrenewable energy usage and economic growth contribute to environmental deterioration, whereas technological innovation and globalization improve the quality of the environment. This study validated the hypothesis of the environmental Kuznets curve for South Africa, as the short-term coefficient value was lower than the long-term elasticity. Furthermore, using the frequency-domain causality test revealed that globalization and economic growth predict load capacity in the long term, and nonrenewable energy predicts load capacity factors in the long and medium term. In addition, technological innovation predicts load capacity factors in the short and long term. Based on the findings, we propose that policymakers should focus their efforts on increasing funding for the research and development of green technologies.

In the last two decades, the tourism and energy sectors have grown rapidly and boosted economic growth, but it is inevitable that these sectors will cause environmental changes. So far, attempts have been made to determine the impact of the tourism and energy sectors on environmental degradation by examining pollution indicators such as CO 2 emissions and ecological footprint. However, these indicators neglect the supply side of the environment. In this context, this paper, for the first time, examines the influence of tourism, income, and energy consumption on the load capacity factor that results from dividing biocapacity by ecological footprint. Thus, the study aims to conduct a comprehensive sustainability analysis for Turkey by assessing the environmental quality on the supply and demand side. For this purpose, the study employs the novel dynamic Autoregressive-Distributed Lag (ARDL) simulations for the period 1965–2017, and the results indicate that tourist arrivals, energy consumption, and economic growth have a negative long run effect on the load capacity factor. Among these factors, only economic growth exerts a significant impact on the load capacity factor in both the short and long run. In the long run, the negative environmental effect of economic growth is less than in the short run. Therefore, the environmental Kuznets curve hypothesis is valid for Turkey. Based on the results, some policy recommendations are proposed to help Turkey improve its environmental quality.

This study explores the interplay among economic growth, financial globalization, urbanization, fossil fuel consumption, and renewable energy usage and their combined impact on the load capacity factor in Mexico. This research employs the load capacity factor as a unique measure of ecological health, facilitating a comprehensive ecosystem assessment by sequentially evaluating biocapacity and ecological effects. Using time series data spanning from 1971 to 2018, this study employs the Autoregressive Distributed Lag (ARDL) method to analyze both long-term and short-term dynamics and cointegration. The findings reveal that economic growth, fossil fuel usage, and urbanization reduce Mexico’s load capacity factor, thereby diminishing environmental quality. In contrast, the adoption of renewable energy sources and the influence of financial globalization exhibit positive effects on the load capacity factor over the long and short term. These outcomes remain consistent even when compared with alternative estimation techniques, including dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). As a priority, Mexican policymakers should accelerate the transition to renewable energy sources, encourage sustainable urban development, and foster a more ecologically conscious economic agenda. Furthermore, promoting greener technologies can enhance the load capacity and mitigate environmental degradation. Ultimately, Mexico can establish an environment conducive to expanding sustainable investments by encouraging cross-border investments, enabling global trade in financial services, and cultivating greater integration of capital and financial markets.

Currently, the most crucial economic and ecological issues are related to environmental degradation and sustainability. On this backdrop, this paper examines the impact of financial globalization and natural resource rent on load capacity factor, using the novel dual adjustment approach and time–frequency domain causality approaches, in the case of India. This study contributes to the extant body of knowledge in the area of environmental economics. First, it is the first attempt to analyze the factors responsible for load capacity factor, specifically for India. As such, studies on environmental concerns on both the supply and demand sides are put into consideration. Empirical results show that only renewable energy consumption lessens the load capacity factor, while economic growth and financial globalization are positively correlated with the load capacity factor, and natural resource rent is insignificant in the short run. In the long run, only economic growth is negatively correlated with load capacity factor, while the other series positively influence load capacity factor. To reap greater ecological merits, policymakers should focus on transitioning from conventional non-renewable energy sources that contribute to rising carbon emissions to more cost-effective and dependable renewable sources of energy that support sustainable growth and a healthy environment.

In this paper, we assess the effects of fiscal policy on load capacity factor using data spanning from 1990 to 2018 in BRICS nations (Brazil, Russia, China, India, and South Africa). Unlike both CO 2 emissions and ecological footprint, the load capacity factor captures both the demand and supply sides of the environment. This research leverages on co-integration test, second-generation unit root tests, and the novel panel nonlinear autoregressive distributed lag (PNARDL). The results revealed that the major contributors to environmental deterioration are economic expansion and nonrenewable energy, while environmental sustainability is attributed to increased renewable energy. Furthermore, a positive shock in taxation revenue increases the quality of the environment while positive (negative) shocks in government expenditure decrease environmental quality. In affirming the PNARDL testing approach findings, the current study employed the pool mean group (PMG) and mean group (MG) estimators to assess the linkage between the independent and dependent variables. The results of the MG and PMG estimators align with the panel nonlinear ARDL results. Besides, the panel causality test also revealed unidirectional causality from renewable energy, nonrenewable energy, economic growth, government expenditure, and taxation revenues to load capacity factor. These findings affirm the findings of the PNARDL testing approach. The study suggests that the BRICS nations’ governments should use the fiscal policy to enhance ecological sustainability by promoting investment and projects in renewable sources.

Industrialization plays a crucial role in socio-economic development as it holds significant potential for creating new jobs, tightening the income gap, and promoting the use of advanced technology. As global competition intensifies, emerging economies emulate industrialized economies in accelerating manufacturing activity to improve national welfare and join the new global order. However, policymakers’ understanding of how competitiveness in the industrial sector helps developing countries accomplish their sustainable development goals must be deepened. This paper aims to analyze the connections among competitive industrial performance, renewable energy consumption, urbanization, and load capacity factor (LCF) in the BRICS economies for the period between 1990 and 2018. Robust evidence from the continuously updated fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) models shows that greater industrial competitiveness enhances environmental quality. The findings also reveal that income growth ultimately evolves as an ecologically friendly factor, confirming the validity of the load capacity curve (LCC) hypothesis. Another outcome of the econometric analysis indicates that renewable energy consumption contributes to the LCF, whereas urbanization damages the environment. Therefore, BRICS policymakers should concentrate on maintaining their competitiveness, implementing resilient urban planning, and promoting the usage of renewable energy to safeguard the environment while simultaneously achieving rapid economic growth. Graphical Abstract

In this study, the focus is on examining the influence of renewable energy consumption, economic risk, and financial risk on the load capacity factor (LF) within the BRICS countries. The analysis covers the time span from 1990 to 2019. The empirical strategy uses the Method of Moments Quantile Regression (MMQR) and long-run estimators (Fixed Effects Ordinary Least Squares, FE-OLS; Dynamic Ordinary Least Squares, DOLS; and Fully Modified Ordinary Least Squares, FMOLS). The findings highlight the presence of a cointegrating relationship. Moreover, fossil fuels and economic growth cause LF to decrease, while economic risk and the use of renewable energy sources increase the deepening of the LF. Furthermore, the results of the MMQR method are confirmed by DOLS, FMOLS, and FE-OLS estimates. Causality results also demonstrate that these factors may forecast ecological quality, indicating that policies for renewable energy consumption, financial risk, renewable energy, and economic growth can all have an impact on the degree of LF. In light of this research, policymakers should strongly encourage expenditures on environmentally friendly technologies and economic and financial stability to increase energy efficiency as well as sustain the widespread adoption and use of energy-saving products.

In the empirical literature, few studies assessed the influence of the insurance market on carbon emissions. However, the effects of insurance markets on the load capacity factor (LCF) have been ignored. In this regard, the objective of the current work is to assess the potential impact of the insurance market on environmental sustainability in 27 OECD countries from 1990 to 2018 based on the LCF, which implies the strength of a state to enhance the population based on the current lifestyle. The present work employed the novel Method of Moments Quantile Regression (MMQR). This model is the prime and correct technique to better understand the association between the insurance market and the LCF across heterogeneous quantiles and to yield more robust empirical outcomes. The MMQR findings indicate a negative interaction between the insurance market and the LCF. In other words, the insurance sector has a powerful influence on economic activities and investments, such that insurance activities lead to an increase in the level of energy utilization, and thus have a negative influence on ecological sustainability. In contrast, the findings illustrate a positive and considerable association between renewable energy consumption and LCF. Based on the overall outcomes, it is suggested that OECD countries should focus on policies that encourage the use of renewable energy rather than incentivizing the insurance market. OECD country governments should also support green insurance activities to minimize the environmental damage of the insurance market.