Retesting the EKC hypothesis through transmission of the ARMEY curve model: an alternative composite model approach with theory and policy implications for NAFTA countries

Catch-up growth with alpha and beta decoupling and their relationships between CO2 emissions by GDP, population, energy production, and consumption

This study explores the relationship between CO2 emissions by GDP, population, energy production, and consumption in the United States, China, Romania, and Thailand economies from 1990 to 2019. It evaluates the phenomenon of catch-up growth, which transpires when an lagging economy goes through an expansionary phase after a period of below-average performance. We used the stochastic model to illustrate in terms of alpha and beta decoupling techniques. The outcomes validated by positive and negative decoupling attitudes play a crucial role in predicting a rise in CO2 emissions owing to oil, gas, and coal use in comparison to Romania. Thailand and Romania have a more viable road to sustainability than the United States and China. The United States and China appear to have an antagonistic relationship, as suggested by decoupling attitudes. Thailand and Romania are considered to be highly environmentally sustainable countries on account of their minimal carbon emissions, efficient energy usage, and forward-thinking environmental policies. Accordingly, policy recommendations are offered based on CO2 emissions and effective mitigation policies, since this allows for determining which countries with high emissions need technological advances, best practices, and intersectoral policies.

Evaluating the effects of ECON-ESG on load capacity factor in G7 countries

For the first time, this study introduces the ECON-ESG quadruple, developed by Işık et al. (2024a), by adding the economy (ECON) dimension to the classical ESG (environment, social, governance) triad. Based on this new concept, it explores the impact of ECON-ESG factors on the Load Capacity Factor (LCF) in G7. The impact of ECON-ESG factors on LCF is vital because sustainability through these factors plays a critical role in a sustainable environment with LCF. CS-ARDL model finds that while governance factors (GOVNF) positively affect LCF, economic factors (ECONF) have negative effects. Environmental factors (ENVF) and social factors (SOCF) do not affect LCF. These findings can be interpreted as follows: (i) Negative effects of ECONF on LCF can be interpreted as high productivity levels in G7 leading to high resource consumption, exceeding biocapacity. (ii) In G7 with high-income levels, increased consumption may lead to overconsumption of natural resources and exceeding biocapacity. (iii) High technological progress in G7 can sometimes paradoxically lead to greater resource consumption rather than encouraging more efficient resource use, increasing an ecological footprint. The positive effects of GOVNF on LCF can be interpreted as follows: (iv) High and quality governance practices and policies in G7 can increase biocapacity. (vi) Under good governance, governments and environmental organizations can positively impact LCF by raising public awareness of environmental issues and enabling society to use natural resources more sustainably. Therefore, policymakers should harmonize economic policies through ECONF and governance policies through social factors (GOVNF), which contradict each other in LCF. Additionally, the effect of the single composite form ECON-ESG introduced and proposed in this study on LCF is found to be negative. This requires policymakers and firms to re-evaluate their sustainability one more time from a holistic perspective, including economic factors, as done in this study.

The impacts of renewable energy and institutional quality in environmental sustainability in the context of the sustainable development goals: A novel approach with the inverted load capacity factor

It is crucial to fulfill sustainable development goals in combating environmental pollution. Recently, there has been a growing literature on environmental pollution; however, while many proxies represent environmental pollution, few proxies represent environmental sustainability. In this paper, we examine the effects of institutional quality (SDG-16), economic growth (SDG-8), and renewable energy (SDG-7) on the inverted load capacity factor (SDG-13) in OECD countries from 1999 to 2018. The objective is to ensure environmental sustainability within the Sustainable Development Goals (SDGs) framework. In this respect, the study differs from the existing literature by approaching the sustainable environment literature from a broader perspective. Long-term empirical estimates from the PMG-ARDL technique have shown that institutional quality, reel income, and population increase the inverted load capacity factor, that is, decrease environmental sustainability. However, on the contrary, renewable energy decreases the inverted load capacity factor. Therefore, renewable energy consumption helps reach SDG-7 and SDG-13 in OECD countries. In addition, it is found that economic growth is significant both in the long run and in the short run, and the impact of economic growth on the environment is greater in the short run than in the long run. This result supports the environmental Kuznets curve (EKC) hypothesis for OECD countries. The panel causality test results find a bidirectional causality relationship from renewable energy and population to inverted load capacity factor and a unidirectional causality relationship from institutional quality to inverted load capacity factor. This study argues that policymakers should concentrate on deploying environmentally friendly technology to slow down environmental degradation, increase the usage of renewable energy sources, and promote sustainable development in line with the SDGs.

The nexus between government spending, economic growth, and tourism under climate change: testing the CEM model for the USA

This study examines the impact of government spending, income, and tourism consumption on CO2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO2 emissions varies across states, with some US states experiencing a decrease while others see an increase.

A revisit of the EKC hypothesis in top polluted African countries via combining the ARMEY curve into the Kuznets curve: A Fourier ARDL approach

The present research reexamines the validity of the EKC hypothesis in the top three polluted nations in Africa, Algeria, Egypt, and South Africa, over the period 1970-2020. The central idea of the research is to reexamine the EKC hypothesis by incorporating the ARMEY curve linking government spending and GDP into the Kuznets curve, as suggested by Işık et al. Environ Sci Pollut Res 29(11):16472-16483, (2022) and Ongan et al. Environ Sci Pollut Res 29(31):46587-46599, (2022). To this end, the ARDL equation with a Fourier function is implemented to estimate the long-run drivers of environmental deterioration. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model results revealed that the composite model is only valid in Algeria, and the optimal government spending that maximizes CO2 emissions is 16.88% of gross domestic product. On the contrary, the results showed that the composite model is not valid for South Africa and Egypt due to the failure of the desired shapes for the three curves. The outcomes also confirm the role of energy consumption and population as key drivers of environmental degradation in the three countries.

The role of government spending within the environmental Kuznets curve framework: evidence from G7 countries

This study assesses the role of government spending on environmental sustainability based on a framework that combines the environmental Kuznets curve (EKC) hypothesis with the Armey curve hypothesis. Specifically, the inverted U-shaped relationships between carbon (CO2) emissions and economic growth (EKC hypothesis) and between government spending and economic growth (Armey curve hypothesis) are analyzed using a composite EKC model tested for cross-sectional dependence and heterogeneity, panel unit root, panel co-integration, and the augmented mean group estimation. In so doing, this study pursues a potential transmission mechanism leading from government spending to CO2 emissions through the growth channel and presents a novel way to develop a better understanding of how economic growth policy and energy policy can be synchronized. Empirical results show that economic growth acts as a transmitter between government spending and CO2 emissions in the USA, UK, and Canada. However, the composite EKC hypotehesis is confirmed only for the USA and Canada, where the optimal level of government spending that maximizes CO2 emissions is 29.87% and 29.22% of GDP, respectively. In contrast, the optimal level of government spending equivalent to 28.30% of GDP minimizes CO2 emissions in the UK. The key policy implication is that governments can achieve sustainable economic growth by setting standards for their spending levels.

Sustainable environment quality: moderating role of renewable energy consumption in service sector for selected HDR listed countries

Considering environmental deterioration, an emerging global problem, this study is aimed at determining the impact of the service sector economic activity on environmental quality from the environmental Kuznets curve (EKC) perspective and finding ways to reduce the carbon impact of service sector within the EKC relationship. This study proposes that renewable energy intensity in the economy plays an important role in reducing carbon print of service sector. This study is based on secondary data from 1995 to 2021 for different development-wise categorized country groups leading to 115 countries, according to the Human Development Report (HDR) on the Human Development Index (HDI). Estimated results using panel feasible generalized least squares (FGLS) have confirmed inverted U-shaped for very high HDI and medium HDI and U-shaped EKC for low HDI countries. This study is instrumental in confirming the moderating role of renewable energy in the service sector EKC. Policymakers can plan a gradual reduction of carbon footprint in the service sector by transitioning toward renewable energy.

Renewable energy, economic freedom and economic policy uncertainty: New evidence from a dynamic panel threshold analysis for the G-7 and BRIC countries

This study aims to demonstrate the impact of renewable energy consumption (REC) on environmental degradation using the EKC hypothesis testing for the BRIC and G-7 countries. Two EKC models were created and tested, with Model 2 including REC and other independent variables such as economic freedom (EF) and economic policy uncertainty (EPU), which affect the level of renewable energy consumption and CO2 emissions. Empirical findings indicate that the EKC hypothesis is verified faster in the REC-EF-EPU-based EKC model (Model 2) than in the EF-EPU-based EKC model (Model 1) for G-7 countries since the turning point takes place earlier in Model 2 than in Model 1 with REC. This suggests that renewable energy consumption accelerates the reduction of CO2 emissions. Moreover, this earlier turning point results in lower environmental cleaning costs, less time vesting, and saving resources and money for G-7 countries. However, the study found no evidence supporting the EKC hypothesis for the BRIC countries.

Environmental sustainability through aggregate demand and knowledge economy interaction-a case of very high-HDI countries

The magnitude of the economic activities is immense in very high-Human Development Index (HDI) countries, leading to environmental degradation, a crucial problem. This study is aimed at testing aggregate demand's role in the environmental Kuznets curve (EKC) perspective and explores the role of four pillars of the knowledge economy, viz., technology, innovations, education, and institutions, as proposed by World Bank, in maintaining sustainable development of environmental quality in these countries. The analysis covers the period ranging from 1995 to 2022. The departure of normality of the variables provides a solid base for panel quantile regression (PQR). Unlike ordinary least squares (OLS) regression, which estimates the conditional mean of the dependent variable, PQR estimates the conditional quantiles. The estimated results using PQR confirm both U and inverted U-shaped aggregate demand-based EKC. In fact, these knowledge pillars in the model determine the shape of EKC. Results also reveal that two knowledge pillars, i.e., technology and innovations, are responsible for significantly reducing carbon emissions. In comparison, education and institutions are responsible for expanding carbon emissions. As a moderator, all knowledge pillars except institutions are shifting the EKC downward. The key lessons from these findings are that technology and innovation can reduce carbon emissions, while education and institutions may have a mixed impact. The relationship between knowledge pillars and emissions may be moderated by other factors, underscoring the need for further research. Moreover, urbanization, energy intensity, financial development, and trade openness significantly contribute to environmental deterioration.

Moving towards sustainability: how do low-carbon energy, current account balance, and reserves induce environmental deterioration in the Big 3?

Promoting financial sustainability is the focus of current state policies while addressing the concerns of environmental pollution. The alarming impacts of climate change on economies motivate us to revisit an intensive empirical study to explore the dynamic relationships of low-carbon energy, current account balance, and reserves with carbon dioxide (CO₂) emissions in the most polluted countries across the globe for the years 1981-2020. We applied the dynamic autoregressive distributive lag (D-ARDL) simulation model to investigate the short and long-run connection. The empirical outcomes of the study uncover that in the short run, a 1% increase in renewable energy reduces CO₂-based emissions by 0.417%, 0.169%, and 0.619% in China, the USA, and India, respectively. We further explored that China's and the USA's economic growth causes environmental deterioration. In contrast, a 1% increase in current account balances improves the environmental quality of China and India by 0.3% and 0.6%, respectively. This research concludes that model variables significantly impact the environment. Therefore, it is necessary to draw policy implications to increase the consumption of low-carbon energy to sustain economic growth by limiting the adverse impacts of economic activities.

Modeling the economic viability and performance of solar home systems: a roadmap towards clean energy for environmental sustainability

Energy is a necessary source of economic development and social prosperity, linked with primary production and consumption activities worldwide. In this regard, solar home systems (SHSs) are beneficial in two ways, i.e., saving vitality overheads and meeting the energy demand of small enterprises. The current study aims to evaluate the performance of adopting SHS to develop the small-scale industry in Pakistan. An inclusive questionnaire survey was conducted, and respondents were selected using the purposive sampling method. As a step further, we scrutinize the moderating role of awareness and understanding of technology between the node of adopting SHS and the monetary enactment of small-scale industry. We authenticate the model using a sample of 357 respondents by applying the partial least square structural equation modeling (PLS-SEM) technique. The results indicate that low-cost energy through SHSs has a progressive and substantial linkage with the demonstration of small-scale industry and enhances the quality of energy supply in Pakistan. Similarly, awareness and understanding of SHS significantly moderate the relationships between enhanced energy supply through SHS, the quality of SHS, and the performance of the small-scale industry. These findings provide a valuable guideline to the regulation developing authorities that more attention is needed to focus on SHS to further improve the performance of small-scale industry.

Are economic growth and environmental pollution a dilemma?

For the first time, this study introduces-proposes using the Armey curve hypothesis (ACH) for testing the environmental Kuznets curve hypothesis (EKCH) in the relevant literature. The rationale for this new proposed methodology is that both hypotheses are expected to have similar inverted U-shaped curves. Hence, we combine the aforementioned hypotheses to obtain a single composite model. This single model may allow us to calculate a maximum (optimum) level of government expenditures that will increase or decrease CO₂ emissions for USMCA (the USA-Mexico-Canada Agreement) countries. To this end, our study employs an augmented mean group (AMG) estimator. The results demonstrate that the EKCH is verified by way of the AC model only for Mexico. Additionally, with the advantage of this approach, we calculated the optimal government spending level, which will increase both per capita real GDP (RGDPPC) and CO₂ emissions in this country by around 26.4% of RGDPPC. This level of spending will be a kind of threshold point for the Mexican government's policymakers. Hence, they will know that if they continue to spend more than this level, both the RGDPPC and CO₂ emissions will decrease, implying either a lower RGDPPC or a cleaner environment. The primary purpose of the proposed methodology in this study is to reveal the possible effects of the government's economic growth-oriented increased public expenditures on the environment in a single composite model. In other words, the relationship between economic growth and the environment is approached from the perspective of public spending, and it is reminded that governments should have harmonious and sustainable public spending policies for both economic growth and a cleaner environment.

The effect of mandatory environmental regulation on green development efficiency: evidence from China

The existing literature finds that mandatory environmental regulation (MER) can significantly reduce environmental pollution. However, much less is known about how the implementation of MER affects green development efficiency (GDE). Based on the Air Pollution Control Action Plan which was enforced in 2013 in China's most developed regions as an exogenous shock, we find that first, MER has a significant negative effect on the improvement of GDE by reducing regional scale efficiency. Second, MER mainly reduces the GDE of cities with stronger regulation intensities and with larger economic volumes. Third, MER also has a negative impact on regional green total factor productivity by changing technical progress. We suggest that when implementing MER, governments should enhance regional and global cooperation, promote green technology, and use comprehensive policy tools to stimulate firms' green innovation.

Analyzing the determinants of sustainability of China Pakistan Economic Corridor (CPEC) projects: an interpretive structural modelling (ISM) approach

China Pakistan Economic Corridor (CPEC) is a game changer initiative of South Asian Pacific Rim. It has great importance for almost all Asian countries. Its success is expected to dictate the economic development of the stakeholders. The aim of this study is to evaluate the essential determinants deriving the sustainability of CPEC projects. The design of the study comprises of the review of literature, data collection, and analysis. Population under study is the folk of stakeholders of CPEC. Sampling envisages on purposive sampling design, i.e., 14 experts from within the stakeholders. Primary data is collected in the field setting through a survey questionnaire appropriate for the study. ISM is used for modelling and MICMAC for analysis and classification using inductive approach. The findings of the literature survey show that there are 23 prime determinants of sustainability of CPEC projects. The results of ISM show that 13 determinants are at Level-I, nine at Level-II, and one determinant namely "economic globalization" is at Level-III being the most critical and driving determinant. The findings of MICMAC show that only one determinant is classified in independent quadrant, and all the remaining determinants are in linkage quadrant, whereas, no determinant is shown in autonomous and/or dependence quadrant. But most of the determinants have potential to be classified in dependent and independent quadrants. It is intimately evident that the results of MICMAC corroborate the results of ISM. It is useful for folk of the stakeholders by way of developing an understanding about the multitude of determinants, intra-determinant relations, prioritizing the determinants for policy decisions, and/or for building future studies. This study has some limitations, e.g., the study uses qualitative approach and answers what and how questions that do not quantify the relations or tell the cause of indicated relations.

Which factors influence the decisions of renewable energy investors? Empirical evidence from OECD and BRICS countries

The importance of using renewable energy (RE) sources has increased significantly in recent times, especially considering the growing concerns about climate change problems and rising fossil fuel prices, which pose a significant threat to the national economies. Therefore, empirical studies that can be used both domestically and internationally in harmony can be created in line with rising investments in RE. However, there has no more analysis of RE investments from the viewpoint of investors in the literature up to this point, and it is crucial to highlight the best investor practices when deploying RE. This research provides theoretical and empirical support for the factors influencing RE investments; used in this analysis are newly constructed panel data on 34 OECD countries and the 5 BRICS countries that range from 2000 to 2020. Specifically, the generalized moment method (GMM), robustness check, fixed and random effects models, panel unit testing, and other panel regression techniques were employed in the study to analyze the determinants of RE investment. The main findings of this paper suggest that economic growth, RE policy, and R&D expenditures all have a statistically significant and positive relationship with RE capacity. Furthermore, RE investment is inversely relative to energy use, electricity use, and carbon (CO₂) emissions. As a result, rigorous governmental or state regulation (policy, R&D) is essential for RE investment.

The effect of industrialization, militarization, and government expenditure on carbon dioxide emissions in Ghana

The need to attain lower carbon dioxide emissions has become a topical issue in recent times. The effect of a number of economic variables on carbon dioxide emissions has been empirically assessed. Rising government expenditure, industrialization, and militarization have characterized many developing countries including Ghana. While it is undeniable that such situation has socio-economic importance to offer developing countries, their environmental effects have become a matter of debate among researchers. This study assesses the carbon dioxide emissions effect of industrialization, government expenditure, and militarization in Ghana. Based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, the study models Ghana's carbon emission as a function of income, population, industrialization, government expenditure, and military expenditure. Time series data over the 1971-2018 period was used for investigation. The techniques employed to analyze the data were unit root test, cointegration test, and regression analysis. The autoregressive distributed lag (ARDL) regression approach reveals there is an inverted U-shaped relationship between income and carbon emission confirming the environmental Kuznets curve hypothesis. Also in the long run, carbon emissions are positively influenced by population, industrialization, and militarization but reduced by government expenditure. Similar outcome was obtained in the short run. The paper concludes that the level of income, industrialization, militarization, and population matters to deal with carbon dioxide emissions in Ghana. Policy implications of the findings include the urgent need for authorities to promote the use of eco-friendly production methods for military and industrial activities to sustain the economic growth without harming the environment.

The impact of smart city pilots on corporate total factor productivity

The existing literature on smart city pilots mainly focuses on the city level and rarely addresses the firm level. This paper assesses the impact of smart city pilot policy (SCP) on firms' total factor productivity (TFP) and explores the impact of SCP under different heterogeneities as well as the mechanisms of action of the SCP. The LP approach is used in this paper to measure firms' TFP, and the impact of SCP is analyzed by the DID model with firms' panel data from 2009 to 2019 as research objects. First, it was found that the SCP can significantly increase the TFP of firms (0.041). Second, through heterogeneity analysis, we found that SCP can strengthen the monopoly position of monopolistic firms and state-owned enterprises. Moreover, the SCP can also alleviate the development imbalance of TFP between firms in coastal and non-coastal areas. In addition, SCP can significantly improve TFP of heavy polluting enterprises. Finally, we find that the important ways for SCP to improve firms' TFP is increasing investment in technological innovation, talent agglomeration, attracting financing, improving resource allocation efficiency, and digital transformation. The study provides unique insights for policy makers and business managers in China and other emerging countries to enhance TFP and achieve corporate sustainable development.

Optimal decisions for green supply chain with a risk-averse retailer under government intervention

This paper investigates the effects of the financial subsidy and product access policies on the performance of green supply chains (GSCs). Based on the game theory and preference theory, we study a green supply chain consisting of a risk-neutral manufacturer and a risk-averse retailer under government interventions from different power structures. The result reveals that green production can be effectively promoted only when product access exceeds a certain threshold. The Nash equilibrium game has the highest greenness and expected utility of GSC. It also shows that regardless of the market structure and government intervention policy, the retailer's risk aversion is positively correlated with the highest level of product access. Moreover, once effective product access is implemented, the retailer's risk aversion does not affect the optimal greenness of manufacturer production. Besides, compared with other intervention policies, the highest optimal product greenness exists in the scenario of financial subsidy with effective product access. The study suggests that the government needs to set certain green standards when implementing subsidy policies and promoting the risk aversion of retailers.

Do pilot free trade zones improve the green total factor productivity? Evidence from a quasi-natural experiment in China

China's pilot free trade zone (PFTZ) is an important national strategy to achieve high-quality development, so it is necessary to discuss the effect of PFTZ implementation on green total factor productivity (GTFP). Based on the data from 279 cities in China from 2004 to 2018, this study takes the establishment of PFTZ as a quasi-natural experiment and uses the difference-in-differences (DID) method to systematically evaluate the effect of PFTZ on urban GTFP. The empirical results of this paper are shown as follows: Firstly, the construction of PFTZ has a significant effect on urban GTFP, and this effect has increased gradually over time. Secondly, the construction of PFTZ mainly promotes the urban GTFP by increasing the level of science and technology innovation, reducing government intervention and improving the level of human capital. Thirdly, the effect of PFTZ construction on GTFP is more pronounced in regions with earlier waves of PFTZ and in western regions where environmental concerns are higher. In addition, there is a significant positive linkage between the construction of the PFTZ and the Belt and Road Initiative to improve the urban GTFP. The findings of this paper enrich the relevant literature on PFTAs and sustainable development and provide a theoretical basis for further promotion of PFTZ construction.

Risk management in sustainable supply chain: a knowledge map towards intellectual structure, logic diagram, and conceptual model

The global spread of COVID-19, international trade protectionism, geopolitical conflicts, and climate change presents challenges and risks to sustainable supply chains (SSCs). In recent years, scholarly interest in sustainable supply chain risk management (SSCRM) has continued to rise. A helpful literature review is necessary to enable supply chain practitioners to apply empirical findings from academic research or conceptual frameworks to their operations to maintain the stability and competitiveness of sustainable supply chains. The knowledge map of SSCRM is explored in this study using both quantitative and qualitative analysis. A total of 793 articles were retrieved to reveal the knowledge map of SSCRM. Scientometric and context analysis are combined in quantitative analysis to identify the intellectual structure of risk management research related to SSC. Then, a critical review is conducted in qualitative analysis to summarize and analyze the motivations, strategies, approaches, and tools of SSCRM. Combining the quantitative and qualitative analysis results, a conceptual model is constructed for SSCRM from three aspects: (1) risk identification, (2) risk assessment, and (3) risk mitigating and responding. Finally, future research directions are suggested based on the conceptual model for guiding the theories and practice of SSCRM. This study can work as a roadmap for providing appropriate risk management policies and toolkits to SSC, which could advance theoretical thinking on how to mitigate SSC risks.

Investigation of economic and financial determinants of carbon emissions by panel quantile regression analysis: the case of Visegrád countries

This study determines the impacts of gross domestic product, domestic bank credits given to private sector, and military expenditures on carbon emissions based on 1990-2019 time period. The panel quantile regression approach is applied for the Visegrád group countries. Our empirical results reveal that domestic bank credit given to private sector has a positive and meaningful impact on carbon emissions at medium and high quantile levels. On the other hand, it has been determined that gross domestic product has a reducing impact on carbon emissions, but military expenditures have an increasing impact on carbon emissions. Besides, as consequences of such tests, the difference between the quantiles, that is, the heterogeneous structure was revealed. A separate model was created with a different panel quantile approach for robustness control, and the results were compared by giving different values to penalty term. These results provide strong evidence for decision-makers and implementers.