Environmental degradation and financial development: do institutional quality and human capital make a difference in G11 nations?

Analysis of human capital effects introducing Bayesian quantile regression in the process of industrial structural upgrading

In recent years, with the continuous evolution of the global economy and the adjustment of industrial structures, the understanding of the role played by human capital in the process of economic development has become particularly important. However, existing research on the impact of human capital on economic growth often adopts traditional regression methods, failing to comprehensively consider the heterogeneity and nonlinear relationships in the data. Therefore, to more accurately understand the influence of human capital on economic growth at different stages, this study employs Bayesian quantile regression method (BQRM). By incorporating BQRM, a better capture of the dynamic effects of human capital in the process of industrial structure upgrading is achieved, offering policymakers more targeted and effective policy recommendations to drive the economy towards a more sustainable direction. Additionally, the experiment also examines the impact of other key factors such as technological progress, capital investment, and labor market conditions on economic growth. These factors, combined with human capital, collectively promote the upgrading of industrial structure and the sustainable development of the economy. This study, by introducing BQRM, aims to fill the research gap regarding the impact of human capital on economic development during the industrial structural upgrading process. In the backdrop of the ongoing evolution of the global economy and adjustments in industrial structure, understanding the role of human capital in economic development becomes particularly crucial. To better comprehend the direct impact of human capital, the experiment collected macroeconomic data, including GDP, industrial structure, labor skills, and human capital, from different regions over the past 20 years. By establishing a dynamic panel data model, this study delves into the trends in the impact of human capital at various stages of industrial structure upgrading. The research findings indicate that during the high-speed growth phase, the contribution of human capital to GDP growth is 15.2% ± 2.1%, rising to 23.8% ± 3.4% during the period of industrial structure adjustment. Technological progress, capital investment, and labor market conditions also significantly influence economic growth at different stages. In terms of innovation improvement, this study pioneers the use of BQRM to gain a deeper understanding of the role of human capital in economic development, providing more targeted and effective policy recommendations. Ultimately, to promote sustainable economic development, the experiment proposes concrete and targeted policy recommendations, emphasizing government support in training and skill development. This study not only fills a research gap in the relevant field but also provides substantive references for decision-makers, driving the economy towards a more sustainable direction.

Effects of atmospheric particulate pollution on lung function of athletes

There is a knowledge gap on how ground-level particulate pollution affects labor productivity in emerging nations due to a lack of study, especially when it comes to outdoor work settings like couriers in the express delivery industry. Combining findings from two research projects, this paper examines the socioeconomic consequences of particulate matter and ground-level particulate pollution. Special panel dataset from China's express delivery companies are used, we study how particulate pollution affects courier productivity. The instrumental variable of our analysis was built by particulate pollution data from upwind towns. Moreover, a comparable rise in particulate levels during the 30 days caused a significant 23.7% decline in worker productivity. This draws attention to a neglected area of the economic effects of particulate pollution, especially in underdeveloped countries. Our results also highlight the wider health hazards connected to outdoor activities in high-pollution locations, drawing comparisons on outdoor exercisers and particulate matter concentrations. The critical need for coordinated policy attention addressing both ground-level Particulate and particle matters in developing nations is highlighted by the increased risk of lung function impairment among outdoor exercisers owing to excessive particulate matter concentrations. The interrelated risks that air pollution poses to public health and economic productivity are clarified by this Comprehensive viewpoint.

Trade openness, human capital, natural resource, and carbon emission nexus: a CS-ARDL assessment for Central Asian economies

There is a call for global efforts to preserve the ecological systems that can sustain economies and people's lives. However, carbon emission (CEM) threatens the sustainability of humanity and ecological systems. This analysis looked into the influence of energy use (ERU), human capital (HCI), trade openness (TOP), natural resource (NRR), population, and economic growth (ENG) on CEM. The paper gathered panel data from the Central Asia region from 1990 to 2020. The CS-ARDL was applied to establish the long-term interaction among the indicators. The paper's findings indicated the presence of the environmental Kuznets curve (EKC) in the Central Asia regions. Also, the empirical evidence highlighted that energy use, natural resources, and trade openness cause higher levels of CEM. However, the research verified that CEM can be improved through human capital and urban population growth. The study also found that HCI moderates the interaction between NRR and CEM. The causality assessment indicated a one-way interplay between ENG, ERU, NRR, and CEM. The study proposes that to support ecological stability in these regions, policy-makers should concentrate on developing human capital, investing in renewable energy sources, and utilizing contemporary technologies to harness natural resources in the economies of Central Asia.

Do institutions contribute to environmental sustainability? A global analysis using the dynamic spatial Durbin and threshold models

There has been a recent surge in attention to the potential involvement of institutions in enhancing environmental quality. This research contributes to the ongoing debate by analyzing the spillover and nonlinear effects of institutions on the load capacity factor (LCF) in a sample of 100 countries between 2000 and 2019. The spillover effects are analyzed using the dynamic spatial Durbin model (DSDM), while the dynamic threshold model is implemented to estimate the nonlinear impacts of institutions. The Moran's I and Geary's C tests reveal a positive spatial autocorrelation for the LCF. The DSDM indicates the existence of positive direct and indirect (spillover) effects of political stability, control of corruption, and the rule of law on the LCF. Moreover, control of corruption has the highest positive influence on the environment. When conducting the threshold analysis, the locally weighted scatterplot smoothing curve indicates a nonlinear relationship between institutions and LCF, while the threshold test suggests a single threshold and two regimes. The dynamic panel threshold model reveals that government effectiveness and the rule of law positively affect the environment under both regimes. On the contrary, the positive effects of control of corruption, regulatory quality, and political stability are only observed under the upper regime. Furthermore, control of corruption has the highest positive environmental impact, albeit it needs more time to be achieved. The research emphasizes the importance of international collaboration and the design of both short- and long-term strategies to enhance institutional quality and, consequently, safeguard the environment.

How do information and communication technology, human capital and renewable energy affect CO2 emission; New insights from BRI countries

If nations want to attain sustainable development with the exponential growth of information and communication technology (ICT) around the world, they must understand the connection between ICT and carbon emissions. Therefore, this study has used panel data from 64 ''Belt and Road Initiative economies between 2000 and 2021 while finding the impact of ICT, renewable energy consumption (REC), human capital (HC) and economic growth (EG) on CO2 emissions. This study employs the Augmented Mean Group (AMG) estimator, Mean Group (MG) estimator and the Dumitrescu-Hurlin panel causality. The findings indicate that the use of ICT, HC and the REC are inversely related to CO2 emissions, whereas EG is positively associated to CO2 emissions and hence poses a danger to environmental sustainability. In addition, the interaction term of EG with ICT, REC and HC has negative impact on CO2 emissions in BRI economies. Intriguingly, the results reveal that ICT and CO2 emissions has inverted U-shape relationship in BRI economies. Furthermore, the causality results show that ICT, REC, and human capital are all cause and effect linkages that affect CO2 emissions in both directions. In order to reduce energy utilization and boost economic growth, the findings stress the importance of implementing cutting-edge ICT and REC in the industrial sector.

Supply chain in transition navigating economic growth and environmental sustainability through education

The growing interest in the Management of Eco-Friendly Supply Chains warrants this study. Green supply chain management (GSCM) is an approach to supply chain management (SCM) that takes into account environmental factors. Therefore, GSCM is vital in shaping the cumulative environmental effect of businesses engaged in supply chain operations. In addition, GSCM may help improve the effectiveness of sustainability initiatives. Manufacturing companies, particularly in developing nations like India, are trying to adjust essential procedures and supply chains because of the rising need to be ecologically sustainable. However, such efforts must be deployed strategically to be ecologically sustainable and economically successful. As a result, this study focuses on the relationship between green supply chain management and education that affect environmental sustainability and economic performance. As a further step toward more sustainable development, the mediating function of education is sustainable economic growth and environmental health. The data was collected by distributing a well-crafted questionnaire to manufacturing facilities in India. We employed PLS-SEM to analyze and interpret the data test hypotheses based on data from 415 replies. The findings point to cost and profit as the primary metrics of corporate success. Disposal of trash, usage of resources, and release of greenhouse gases are alternative measures of environmental sustainability. Distributed online links and in-person interviews with employees at companies throughout India who use GSCM procedures provided the basis for the study's primary data set. The data was gathered with the use of an organized survey form. The findings of tests conducted on the hypotheses were considered. According to this research, cost, profit, waste, resource, and GHG emission impacts vary depending on which GSCM techniques are implemented. Green supply chain management strategies significantly affect price, trash disposal, resource utilization, and GHG emissions. There was no discernible trend between GSCM methods and financial success. In addition to discussing the unique elements of sustainable supply chains and the limits of current research, this article also discusses how a company's bottom line will benefit monetarily from establishing a sustainable supply chain. This should inspire more study in this area. Our investigation revealed patterns and voids, and we used that information to outline a thorough plan for future GSCM studies. The research helps manufacturing company management improve their sustainable policies while providing policymakers with pointers.

Decoding the green supply chain: Education as the key to economic growth and sustainability

The value of environmental safeguarding is rising in both private and public spheres. What is meant by the term "green supply chain management" (GSCM)? It is minimizing the negative effects of a company's operations on the natural world. Particularly in the research and academic disciplines of the expanding economy of the China region, the concept of the intersection of green supply chain management and sustainable development is dissected at a foundational level. However, there has been little attention paid to how GSCM, GHC, environmental performance, and economic performance all relate to one another. This study fills that void in the literature by giving hard data to encourage businesses in the China area to adopt GHC (green human capital) and SCM (sustainable supply chain management) in order to significantly improve their environmental and economic outcomes. To better understand the interplay between these ideas, we constructed a conceptual framework. The information was gathered using a survey consisting of questionnaires. Manufacturing companies from ten (10) different areas in China provided the 470 responses. The information was analyzed using structural equation modeling (SEM). Research shows that green human capital and green supply chain management have a beneficial influence on economic performance but no discernible effect on environmental outcomes. The results also demonstrate that green supply chain management is an effective act as a mediator between environmental performance and economic performance, with a beneficial effect on both. An initial conclusion may be made that bettering the green human capital stock was more important for China's green economy's growth than bettering the human capital structure. Research like this helps fill out the picture of the green economy and informs policy decisions at the national level.

Unraveling the non-linear impact of financial development on environmental sustainability: insights from developing countries agreeing the accord

This study delves into the intricate relationship between financial development and environmental sustainability by considering the role of the Paris Agreement in the context of developing countries. By employing advanced econometric techniques method of moment quantile regression (MMQR) and considering a period spanning from 1996 to 2021, this research unravels the non-linear impact of financial development on environmental degradation while considering population and GDP as control variables. The study reveals an inverted N-shaped relationship between financial development and environmental degradation, indicating that environmental degradation (ED) decreases as financial development increases. However, this is followed by a rise in ED before eventually witnessing a further decline. Additionally, the study highlights the positive correlation between GDP and population with ED across all quantiles, with a more pronounced impact observed in higher quantiles. Furthermore, the coefficient of the Paris Agreement demonstrates its effectiveness in decreasing environmental degradation, particularly at higher quantiles of ED. The findings of this study hold practical implications for policymakers, emphasizing the importance of designing and implementing coherent environmental and economic policies in developing countries. This study contributes to understanding the complex dynamics between financial development and environmental sustainability, offering valuable insights for fostering sustainable development pathways.

The impact of environmentally related taxes and productive capacities on climate change: Insights from european economic area countries

In a world increasingly threatened by climate change and its associated risks, there's an urgent need to actively seek solutions for environmental protection and sustainable economic development. Central to this effort is understanding the role of environmental taxes and productive capacities in shaping environmental outcomes. Focusing on countries within the European Economic Area (EEA), this research uses advanced second-generation econometric techniques to examine this relationship. The use of cross-sectional autoregressive distributive lag (CS-ARDL) and dynamic common correlated effects (DCCE) models allows for a robust examination of panel data and provides reliable results. The results reveal an inverted U-shaped relationship, or Environmental Kuznets Curve (EKC), between GDP growth and environmental degradation in the EEA economies. Furthermore, while our data reveal a significant negative correlation between environmental taxes and CO2 emissions, we find that productive capacities have a more significant impact on reducing these emissions. These findings call for further research into the effectiveness of policies to support productive capacities in achieving environmental protection goals in the EEA.

Impact of technological innovation and renewable energy on ecological footprint in G20 countries: The moderating role of institutional quality

The connection between ecological footprint and economic complexity has significant implications for environmental sustainability regarding the policy. Additionally, institutional quality is crucial in ensuring environmental sustainability and moderating the link between economic complexity and ecological footprint. The task of achieving sustainable environmental development and preventing further degradation of the environment poses a formidable challenge to policymakers. This study delves into the significance of technology innovation and renewable energy in creating a more sustainable environment. Recognizing the need for a more critical review, this research establishes the dynamic linkage between ecological footprint, renewable energy consumption, and technological innovation, especially in conjunction with a moderating component, particularly institutional quality, in G20 countries from 1990 to 2021. We employ advanced panel approaches to address panel data analysis concerns, such as cross-sectional dependence, slope heterogeneity, unit root, cointegration test and CS-ARDL. The long-term estimator indicates that renewable energy and technological innovation negatively but significantly impact the ecological footprint. Whilst economic growth, FDI, and urbanization have shown a positive and significant impact on ecological footprint; institutional quality negatively moderates the relationship between ecological footprint, renewable energy, and technological innovation in the G20 countries. Further evidence from the Dumitrescu-Hurlin Granger causality test shows that efforts to expand access to renewable energy, technological advancements, and economic growth will significantly affect environmental impacts. Based on our results, it is imperative to introduce more favorable legislation and encourage technological advancements in the field of renewable energy if we want to achieve our sustainable development objectives.

Towards environmental degradation mitigation: The role of regulatory quality, technological innovation and government effectiveness in the CEMAC countries

The study explores the interaction between regulatory quality, economic growth, technological innovation, energy consumption, government spending on research and development, and environmental degradation (EVD) in the Economic and Monetary Community of Central Africa (CEMAC) region. The study applied the econometric approach CS-ARDL to estimate the short and long-term interaction between the regressors and the explanatory variable. The study period covers from 1990 to 2020. To summarize the findings of this research, (1) the study discovered a positive relationship between energy consumption, government effectiveness, regulatory quality, and environmental degradation. (2) Economic growth, government spending on research and development, and technological innovation, on the other hand, extensively dissipates EVD in the CEMAC economies. (3) The causality analysis espoused a bidirectional connection between energy consumption, technological innovation, and EVD. (4) Lastly, a unidirectional interplay exists between economic growth, government effectiveness, regulatory quality, and EVD. This study also serves as a reference point for policymakers and governmental institutions to invest in cleaner technologies and increase government research and development spending to mitigate environmental degradation in these areas.

Macroeconomic determinants and their impact on environmental sustainability: the role of cultural and creative product prices

China has to deal with the twin challenges of economic structural reform and carbon emission reduction against global warming. While investing in and constructing new infrastructure is great for the economy, it has also added to the carbon emissions of major cities. The product design industry has recently become increasingly interested in creating and pricing cultural and creative goods in specific provinces. Thanks to the burgeoning global cultural and creative sector, a new platform has opened up for the evolution and modernization of China's ancient cultural practices. Cultural creativity has broken the rigid design and production pattern of traditional products from a business point of view, increasing their economic advantages and competition. Also, this study examines ICT's main and moderate effect on carbon emissions in the 27 provinces of China's economy from 2003 to 2019 using panel estimators. The estimated outcomes show the positive contribution to environmental damages by physical capital, tourism, cultural product prices, innovative, creative prices, and trade openness, while ICT significantly reduces emissions. Besides the moderate role of the digital economy on physical capital, tourism, CP, ICP, and tourism significantly reduce CO2 emissions. However, the granger causality outcomes also show a robust analysis. Furthermore, this study also proposes some interesting policies to obtain environmental sustainability.

An empirical investigation of the effects of poverty and urbanization on environmental degradation: the case of sub-Saharan Africa

This study empirically investigates the effects of poverty and urbanization on environmental degradation for a sample of 43 sub-Saharan African (SSA) economies from 1995 to 2018. The major contribution of the study lies in examining the existence of non-linear effects of poverty and urbanization on environmental degradation. We considered a set of institutional and demographic factors to explain the dynamics among poverty, urbanization, and environmental degradation. Findings suggest that an increase in the poverty gap significantly contributes towards intensifying environmental degradation in SSA countries. Results also show the existence of a non-linear relationship between poverty and environmental degradation. The findings purpose several crucial policy recommendations which necessitate the participation of different stakeholders such as government, institutions, researchers, non-profit organizations and citizens for the effective implementations of environment-friendly policies. A battery of robustness tests confirms the validity of the main findings of the study.

Evaluating the role of renewable energy and technology innovations in lowering CO2 emission: a wavelet coherence approach

Environmental sustainability is one of the most critical issues that require efficient environmental and economic policies in modern times. Advancements in renewables and green technologies contribute significantly to sustained long-term development without affecting environmental quality. Several studies focus on the association of carbon dioxide emissions (CO₂e) with economic variables. However, they ignored the impact of technological innovations and renewable energy consumption on CO₂e in developed countries. Therefore, this study examines the relationship between CO₂e, energy consumption, gross domestic product (GDP), renewable energy consumption, and technology innovations in G-7 countries by employing cross-sectionally augmented autoregressive distributed (CS-ARDL) lag and wavelet coherence techniques during 1990-2020. The results depict that GDP and renewable energy consumption are inversely related to CO₂e. A 1% increase in CO₂e will decrease GDP and renewable energy consumption by 0.459 and 0.172% in the long run and by 0.471 and 0.183% in the short run in G7 countries. Technology innovations negatively impact CO₂e in the short run while positively influencing it in the long run. Considering the advancements in green technologies in different energy-dependent and manufacturing sectors is crucial for a sustainable environment in the long run. Such initiatives ensure the effective use of energy sources by limiting CO₂e in the atmosphere. Moreover, the dynamic common correlated effects mean group model confirms the reliability and effectiveness of the CS-ARDL. The wavelet coherence approach revealed a causality relation between CO2e and technology innovation in Italy, Japan, the UK, and the USA during the study period.

Spatio-temporal characteristics and mechanism of ecological degradation in a hilly southern area-a case study of Dongting Lake Basin

Understanding the spatio-temporal characteristics of ecological degradation and its mechanism is the key to implementing national land space ecological restoration. Currently, there is a lack of knowledge about identifying ecologically degraded areas from a structure-function angle. This paper used the Dongting Lake Basin (DLB) as the research area, with the landscape pattern index and InVest model utilized to analyze the landscape distribution characteristics and ecosystem service functions in 2000 and 2018. Based on this, a fuzzy inference approach and geographic detectors were used to explore the characteristics and driving mechanism of ecological degradation in the DLB from 2000 to 2018. The results found are the following: (1) The overall landscape of the DLB was fragmented, the landscape shape tended to be complex, the degree of aggregation declined, and the landscape types were more discrete than before. In terms of the landscape-level index, the overall indicators of the landscape pattern in the DLB showed little change from 2000 to 2018, and the overall landscape pattern change was reasonably stable. (2) The three ecological services exhibited prominent spatial distribution features during the study period. In particular, food supply services showed a steady upward trend, while habitat quality and carbon storage services generally declined. (3) The ecological degradation in the DLB demonstrated striking spatial and temporal differences during the study period, and the ecological situation improved. The ecological degradation areas were mainly distributed in urban areas with denser populations and a higher level of urbanization, while the ecological restoration areas were mainly in the mountainous and hilly areas far away from the urban centers. (4) Among the influential factors, the production potential of urban land and farmland is the main factor that affects the ecological environment degradation and spatial distribution difference in the DLB. The interactive detection results indicate that the driving mechanism exhibits a two-factor enhancement or nonlinear increase.

Environmental sustainability through renewable energy and banking sector development: policy implications for N-11 countries

Climate change has become an alarming condition for developed and developing countries. The main reason for this is the use of non-renewable energy (RE) in economic sectors. Therefore, the world economies are now replacing non-renewable with RE. The role of BANKs is fundamental for this transition because they can fund clean energy projects. Several studies probed the economic growth andCO2e association and ignored the role of BANK development. Therefore, this work investigates the influences of banking sector development on CO2 emissions (CO2e) in the next eleven countries. This work included other factors of GDP, clean energy, and non-RE in the model by taking annual data from 1990 to 2020. Robust econometric techniques are used to highlight the empirical outcomes. The cross-sectional autoregressive distributed lag approach shows that BANK development is a coproduction factor toward CO2 production in the presence of economic development and renewable and nonrenewable energy. More credits from banks to the private sector are enhancing economic activity and increasing energy consumption. This means that a 1% increase in BANK development will increase CO2e by 0.01%. A 1% increase in RE is lowering CO2e by 0.31%. Therefore, this work highlights the importance of BANK development in creating sustainable development. The BANK can fund clean energy projects. Policymakers can utilize the BANK to encourage green investments in household and corporate sectors. The use of green technologies will ultimately bring a cleaner environment and sustainable development to N-11 countries. This work is helpful for policymakers in that they can utilize the banking sector to launch greener projects to attain sustainable development goals.

Can economic growth and carbon emissions reduction be owned: evidence from the convergence of digital services and manufacturing in China

Under the background of the deep convergence of China's digital services and manufacturing, it is of great significance to investigate the effects of the convergence of digital services and manufacturing on economic growth and carbon emissions reduction to the application of digital technology in the whole world. This paper constructs a simultaneous equation model and uses three-stage least squares to estimate the effect and mechanism of industrial convergence on economic growth and carbon emissions. The results show that (i) industrial convergence improves the change of total factor productivity (TFP) and the change of technical efficiency, and the reduction of carbon emissions is the main factor driving the growth of TFP and technical efficiency; (ii) industrial convergence and carbon emissions show a significant U-shaped relationship; (iii) the heterogeneity analysis shows that the convergence of capital-intensive, technology-intensive and labor-intensive manufacturing with digital services will help to improve the growth of TFP, it can inhibit carbon emissions first and then promote it. Therefore, the government should take targeted measures to promote industrial convergence of digital services and manufacturing according to the economic development and industry characteristics, so as to give full play to its positive role in economic growth and emissions reduction.

Exploring the impacts of economic policy uncertainty, natural resources, and energy structure on ecological footprints: evidence from G-10 nations

The role of energy and natural resources rent has been studied in the literature but very few research works investigated the impacts of economic policy uncertainty and energy structure on ecological footprints (EFs) in the group of ten G-10 countries. Therefore, this research is designed to probe the impacts of economic policy uncertainty (EP), natural resources rent, energy structure, economic growth, and total factor productivity on EF. The annual data for 1995-2018 is analyzed by adopting second-generation methods. The empirical results from the CS-ARDL unveiled that EP is significantly and positively related to EF, indicating that EP is not environmentally friendly in these nations. A 1% increase in EP contributes to EF by 0.025% in the long run. In addition, the results show that natural resource rents and energy structure positively contribute to mitigating EF by 0.012% and 0.095% respectively, while economic growth increases EF by 0.237%. Based on the empirical results, this work suggests addressing the economic policy uncertainty and economic progress to lower ecological deprivation can be a viable solution to attain sustainable development goals. This work recommends adopting feasible economic policies with sound efforts. For this purpose, the economic sector has to be strong enough with sustainable production. They should ensure the supply of continuous renewable energy to the economic sector.

Testing the impact of sustainable environmental regulations on firm performance with mediating effect of product market competition: empirical evidence from Turkey

Environmental challenges are increasingly becoming global issues due to the negatively induced effect of carbon dioxide on the natural climate and the well-being of human beings. Industrialisation has intensified the energy demand which brought the surge in the consumption of conventional non-renewable energy resources, including fossil fuels. Despite the overwhelming evidence of negative effects of utilising conventional energy on the atmosphere, there has been a steady rise in industrial production which has encouraged firms to adopt technological innovation. In this sense, many countries have developed various strategies, frameworks and regulations to reduce industrial-driven environmental degradation. Environmental-friendly compliant production technology can be an important substitute model to improve economic development. This study examines the relationship between environmental regulation and firm performance with mediating the impact of product market competition in Turkey. The study uses multi-sectoral firm-level Turkish data covering from 2004 to 2020 which was analysed via numerous methods that control for endogeneity bias. The results of generalised method of moment indicate a strong positive effect of sustainable environmental regulation (SER) on firm performance (FP). Moreover, after mediating the effect of product market competition by decomposing the firms into low product market competition (LPMC) and high product market competition (HPMC), finding reveals a negative effect of SER on FP of LMPC whereas a positive impact was found in the HPMC firms. This finding shows that HPMC compels managers to form a differentiated profit maximisation strategy. In this sense, competition can play a dedicated role in enhancing firm performance in the context of government deliberate strategies and regulations for control of the industrial negative effect on the environment. The industrial sector needs to switch from conventional energy practices to sourcing green and renewable energy that would not jeopardise the environmental quality.

Measuring the macroeconomic determinants of agricultural price volatility: Implications for natural resource commodity prices for green recovery

With rapid growth, green economic recovery has been a key agenda for the globe. However, the price volatility for natural resources plays a significant role in reshaping the green recovery. Therefore, the current study investigates the impact of green recovery, hum, a capital index, GDP growth, foreign direct investment and inflation on natural resource volatility in China from 1995 to 2020. In order to investigate the long-term association among selected variables, this study employs the Autoregressive Distributive Lag (ARDL) model. In addition, the current research uses the Aikaik information (AIC) criteria for the model selections. Obtained outcomes show the significant contribution of green recovery, human capital, GDP growth, FDI and inflation increase the natural resource price volatility level. However, to validate the results of ARDL, this study also used the ECM approach and validated the prior findings. On behalf of outcomes, the current study implies some imperative policies to attain the desired objective for green growth.

The marginal effects of economic growth, financial development, and low-carbon energy use on carbon footprints in Oman: fresh evidence from autoregressive distributed lag model analysis

Oman is committed to turning carbon neutral by 2040 whereby identifying the environmental sustainability-stimulating factors has become a critically important agenda for the nation. Against this backdrop, this study attempts to evaluate the marginal effects of economic growth, financial development, and low-carbon energy use on Oman's carbon footprint levels using quarterly frequency data spanning from 1984Q1 to 2018Q4. Controlling for structural break concerns in the data, the results from the empirical analysis verify the carbon footprint-related environmental Kuznets curve hypothesis for Oman in the long-run. In this regard, the threshold level of per capita real GDP level of Oman is predicted at around US $23,500 which is below the average and maximum per capita real GDP level of Oman during the period considered in this study. Besides, the development of the financial sector and scaling up consumption of low-carbon energy resources are evidenced to boost and curb Oman's short- and long-run carbon footprint figures, respectively. More importantly, the joint carbon footprint-mitigating impact of financial development and low-carbon energy use is also unearthed from the findings. In line with these major findings, a couple of relevant policy interventions are suggested to help Oman accomplish its 2040 carbon-neutrality agenda.

Financial Institutional and Market Deepening, and Environmental Quality Nexus: A Case Study in G-11 Economies Using CS-ARDL

This study presents a new insight into the dynamic relationship between financial institutional deepening (FID), financial deepening, financial market deepening (FMD), foreign direct investment (FDI), economic growth (GDP), population, and carbon dioxide emissions (CO2e) in the G-11 economies by employing a cross-sectionally augmented autoregressive distributed lag (CS-ARDL) approach during 1990-2019. The outcomes from the CS-ARDL and dynamic common correlated effects mean group (DCCEMG) models shows that financial deepening, GDP, FDI, and population degraded environmental quality both in the short run and the long run. Contrary to this, FID and FMD improves environmental quality in these countries. The government should work to maximize financial institutions (access, depth, efficiency) and financial markets (access, depth, efficiency) to reduce the CO2e. A strong positive and in-phase correlation of CO2e with economic growth and population is observed for G-11 countries. These results suggest policy makers should further improve financial institutions by creating opportunities for their populations. Moreover, the governments of G-11 countries should revise their foreign direct investment policies and attention should be given to import efficient means of energy production.

Assessing the linkages of economic freedom and environmental quality in South Asian Countries: application of CS-ARDL

We examine the linkages of economic freedom (ECF), energy use, and CO₂ emissions in selected South Asian countries of Pakistan, India, Bangladesh, and Sri Lanka. Annual data from 1995 to 2018 are analyzed by employing second-generation methodologies. Cross-sectional autoregressive distributed lag (CS-ARDL) is used because this method incorporates the cross-sectional dependence among the data. This work uses three models, where the dependent variables are gross domestic product (GDP), CO₂ emissions, and energy use. The findings reveal that ECF and energy use contributes to more economic development. ECF is improving air quality by lowering CO₂ emissions. The findings suggest that these countries need to increase the percentage of renewable energy in their energy generation mix. At the same time, there is a need to integrate ECF with environmental awareness programs. This will not only increase air quality but also increase economic growth. GDP is found to be dependent on energy use; however, increased energy use from non-renewable also contaminates the environment. Therefore, South Asian countries need to invest more in research and development projects to promote renewable energy.

Investigating the linkages of female employer, education expenditures, renewable energy, and CO2 emissions: application of CS-ARDL

This work investigates the impacts of female employers, renewable energy, and education expenditures on CO2 emission in Pakistan, India, Bangladesh, and Sri Lanka. The annual data of 1990-2020 has been analyzed to present the empirical results. This work uses cross-sectional autoregressive distributed lag (CS-ARDL) approach to know long- and short-run coefficient values. The findings reveal that 1% increase in female employers, renewable energy, and education expenditures will decrease 0.04%, 0.64%, and 0.03% CO2 emissions, respectively, in the long run, which means female employers, renewable energy, and education spending are useful for South Asian countries to lower environmental pollution. This means that increasing female employers, ratio of renewable energy, and education expenditures are very important for South Asian countries to lower environmental pollution. This work recommends that education spending is providing environmental awareness, which is compulsory for cleaner environment.

Understanding the dynamics of natural resources rents, environmental sustainability, and sustainable economic growth: new insights from China

There is a close relationship between natural resources and production in many sectors, and production and consumption can also have an environmental impact. Low environmental quality affects economic growth and well-being. Environmental protection and economic growth cannot be maximized simultaneously. Choosing the right balance between the two aims is imperative for each country. By moderating the role of merchandise trade and manufacturing value-added from 1970 to 2016, we examine the dynamics of China's natural resource rents, environmental sustainability, and sustainable economic growth. Overall, the results of this study indicate that natural resources improve environmental sustainability at the expense of economic growth. In contrast, financial development, merchandise trade, and urban population growth promote environmental degradation. It is vital to understand governance mechanisms to sustain natural resource policies, considering environmental, social, and governance concerns to benefit society.

Does Tourism Induce Sustainable Human Capital Development in BRICS Through the Channel of Capital Formation and Financial Development? Evidence From Augmented ARDL With Structural Break and Fourier-TY Causality

The motivation of the study is to explore the nexus tourism-led sustainable human capital development (HCD) in Brazil, Russia, India, China, and South Africa (BRICS) for the period 1984-2019. The study applied several econometrical techniques for exposing the empirical association between tourism and HCD, such as the conventional and structural break unit root test, the combined cointegration test, long-run and short-run coefficients detected through implementing the Augmented Autoregressive Distributed Lagged (AARDL), and directional causality by following Toda-Yamamoto with Fourier function. The unit-roots test established variables are integrated in mixed order, wherein variables are stationary at a level or after the first difference. The estimated test statistics from the combined cointegration test and AARDL confirmed the long-run association between tourism, gross capital formation, financial development, and HCD. Tourism revealed a positive and statistically significant tie with HCD in the long run. Moreover, the joint effects of interactive terms TOR^*GCF and TOR^*FD (TOR, GCF, and FD denoting tourism development, gross capital formation, and financial development, respectively) established a positive and statistically significant relationship with HCD. In addition, the causality test revealed the feedback hypothesis available between tourism and HCD in all sample countries except India. In conclusion, the role of tourism development is critically important for sustainable HCD in BRICS. Therefore, in case of a policymaking concern, it is inevitable to address the tourism issues with care for capitalizing on the benefits for tourism development.