Examining the temporal impact of stock market development on carbon intensity: Evidence from South Asian countries

An environmental perspective of energy consumption, overpopulation, and human capital barriers in South Asia

Prior literature is substantive in highlighting the nexus between pollutant and socio-economic predictors; however, the role of human interaction has not been sufficiently explored. Thus, the present study examines the validity of the environmental Kuznets Curve (EKC) hypothesis in the presence of energy consumption, overpopulation, and human capital index in five South Asian countries. It employs fixed effects, random effects, and dynamic panel causality techniques with a set of panel data from 1972 to 2021. The baseline results validate the existence of the EKC hypothesis in the recipient panel. Nevertheless, the findings reveal that energy consumption and population density have positive effects, while human capital has negative impacts on CO2 emissions. Furthermore, the study observes that energy consumption and per capita GDP have a significant causal link with CO2 emissions, whereas CO2 emissions are evident to have causality with population density and human capital index. The results are robust and suggest that the consolidation of an effective regulatory framework and technological improvements are substantial measures to improve environmental quality in South Asia. Moreover, allocating sufficient resources to uplift contemporary educational and health status would be imperative to improving environmental quality as aspired to by the Paris Agreement.

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.

Investigating the Causality Between Financial Development and Carbon Emissions: A Quantile-Based Analysis

The relationship between financial development and environmental sustainability has received significant attention in academic discourse. This study explores the crucial role of financial development in addressing the challenge of increasing CO2 emissions. Using quantile-on-quantile and nonparametric causality-in-quantile methodologies, this research investigates the impacts and causal links between financial market and institution development and CO2 emissions levels in five major polluting countries from 1990 to 2019. The findings provide strong evidence regarding the impact of financial institutions and financial market development on CO2 emissions, demonstrating the presence of shocks and nonparametric causality from financial institutions and financial market development to CO2 emissions quantiles. However, the effects of financial institution shocks and nonparametric causality are diverse and asymmetric across the sample. Positive and negative shocks are observed in India, while only negative shocks are observed in China, the USA, Russia, and Japan. Moreover, the findings reveal that the influence of financial market development on CO2 emissions varies across countries, with both positive and negative shocks transmitted to CO2 emissions in the USA, Russia, and Japan, indicating higher volatility in these countries compared to China and India, where only negative shocks are observed. Therefore, our recommendation emphasizes the prioritization of environmentally conscious financial products and the enhancement of the financial system's capacity to mitigate positive shocks contributing to increased CO2 emissions. Implementing this strategy requires collective efforts to embrace sustainable financial practices that consider the environmental impact of financial activities.

Spatiotemporal differentiation of carbon emission efficiency and influencing factors: From the perspective of 136 countries

The severity of the global climate issue is rising, primarily as a result of excessive carbon dioxide emissions. Climate change is a global problem. How to reduce carbon dioxide emissions while promoting social and economic development is a problem that all countries need to face. This study examines global carbon emission efficiency in order to make recommendations for comprehensively improving global low-carbon development level. We extend the research scale of carbon emission efficiency from countries, regions, economic belts and sectors to the world, which can show the differences of countries and has theoretical guiding significance for global low-carbon development. This study calculates the carbon emission efficiency for 136 countries from 2000 to 2019 using the Super-EBM model. The discussion that follows examines the temporal and spatial characteristics of carbon emissions efficiency in 136 countries from the perspective of countries, developed and developing countries, and regions. Finally, the Tobit model is used to comprehensively analyze the factors that affect carbon emission efficiency. The results show that: (1) There are great differences in carbon emission efficiency among countries and regions. Only a few countries reach the production frontier, mainly in Europe, which are Switzerland, Luxembourg, Iraq, Norway, Denmark and the United Kingdom. The carbon emission efficiency of most countries is not ideal, being mainly concentrated in Asia and Africa, and has not achieved significant improvement over time. Asia has the lowest carbon emission efficiency. Mongolia, Ukraine, Iran, Angola, Belarus and Uzbekistan are the key governance areas for global energy conservation and carbon emissions reduction. (2) Developed countries have the much higher average carbon emission efficiency than developing countries. Combined with the industrial development stages of developed and developing countries, this is in line with the environmental Kuznets curve (EKC) hypothesis. The average carbon emission efficiency gap between developing and developed countries shows a trend of "first narrowing and then widening", which demonstrates that developing countries' reliance on energy input to boost their economies will improve carbon emission efficiency, but only temporarily. (3) Urbanization level, foreign trade and proportion of renewable energy effectively improve the carbon emission efficiency, while industrial structure and proportion of electricity users have an inhibitory effect on the carbon emission efficiency. Global low-carbon development should be hastened by strengthening international cooperation, optimizing industrial structure, promoting urbanization and foreign trade, and adjusting the energy structure.

Measuring sustainable development of intelligent tourism service system: analysis on the user's intention

The intelligent tourism service system will help strengthen the management of scenic spots, improve tourism efficiency, and help improve the tourism ecological environment. At present, there are few researches on intelligent tourism service system. This paper attempts to sort out the literature and build structural equation model based on UTAUT2 model (UTAUT is short for Unified Theory of Acceptance and Use of Technology) to analyze the factors that affect the users' willingness of use the intelligent tourism service system (ITSS) in scenic spots. The results show that (1) the effects of the factors affecting the users' intention to use the ITSS of tourist attractions are facilitating conditions (FC), social influence (SI), performance expectation (PE), and effort expectation (EE), (2) Both PE and EE can directly affect the user's intention to use ITSS, while EE indirectly affects the user's intention through PE. (3) SI and FC have a direct impact on the UI of ITSS. The simplicity of use on intelligent tourism application system products can significantly affect the user satisfaction index and product loyalty of the users. In addition, the usefulness factor of perception system and the risk factor of user perception system coexist, with the synergistic effect positively affects the ITSS and use behavior of the whole scenic spot. The main results provide theoretical basis and empirical support for the sustainable and efficient development of ITSS.

Financial Development and Environmental Degradation: Promoting Low-Carbon Competitiveness in E7 Economies' Industries

Emerging countries are approaching economic prosperity. However, the development process has enhanced their ecological footprints, thus promoting low-carbon competitiveness among E7 countries' industries. Therefore, it is essential to identify the factors that affect a country's ecological footprint (EF) in order to safeguard the environment. This study explored the effect of financial development, human capital, and institutional quality on the EF of emerging countries. Furthermore, we explored the effect of financial development on the EF of emerging countries through the human capital channel. In addition, we investigated the role of institutional quality in the financial development-EF nexus. Using panel data from 1990 to 2018, we employed the cross-sectional autoregressive distributed lag (CS-ARDL) technique to conduct a short-term and long-term empirical analysis. The empirical outcomes revealed that financial development degrades ecological quality by raising the EF. The findings further demonstrated that human capital and institutional quality reduce the EF. Moreover, financial development fosters environmental sustainability through the channel of human capital. Additionally, institutional quality reduces the negative ecological impacts of financial development. The causality analysis suggested that any policy related to financial development, human capital, and institutional quality will affect the EF. However, the inverse conclusion was not sustained. Based on these findings, emerging economies should increase their environmental sustainability by promoting human capital and effectively using financial resources.

A nexus study of carbon emissions and financial development in China using the decoupling analysis

Investigating the linkage between financial development (FD) and carbon emissions is important for mitigating climate change. Nevertheless, there is a scarcity of studies investigating how carbon emissions decouple from FD. Here, we investigate the relationship between FD and carbon emissions by using the decoupling model based on cross-province data of China during 2000-2019. Then, we use the decomposition method to analyze the nine drivers of decoupling elasticity of FD and CO₂ emissions. We found that China experienced weak decoupling and strong negative decoupling in most years. Only the finance develops at a very high level; the FD had spare capacities to promote the reduction in the carbon emissions. For example, several developed provinces (e.g., Tianjin, Zhejiang, Guangdong) realized strong decoupling after 2012. The reduction in energy intensity and the increase of foreign direct investment promoted the decoupling of FD from carbon emissions. During the financial recession period, developing a bank-based financial market helped the emissions reduction. Once financial crisis is overcome, developing a market-based financial market promoted the decoupling of FD from emissions. This is because that with the fast FD, the development of stock market contributed to emission reductions through technological improvement, while the bank loans inhibited the decoupling process through the expansion of capital-labor inputs. Overall, these results help in the assessment of the emissions impacts of FD and in addressing climate change problems.

A tested method for assessing and predicting weather-crime associations

Few studies have focused on haze as a weather element and its correlation with crime. In this study, we examined haze as a weather variable to investigate its effects on criminal activity. We used both monthly crime data and weather records to build a regression model that contains a sequential statistical approach to reach the correlation coefficients between the variables. Also, we developed a prediction model to predict crime cases considering three weather factors: temperature, humidity, and haze. We applied this model in two different climate provinces in Saudi Arabia, namely, Riyadh and Makkah. Riyadh is a desert area and observes haze approximately 17 days per month on average, while Makkah is a coastal area observing haze an average of 4 days per month. We found a measurable relationship between each of these three variables and criminal activity. We found that a one-degree increase in temperature was associated with an increase in assault of 0.739, when humidity and haze were held constant. For other independent variables measured against the same crime in Riyadh, a one-degree increase in humidity was associated with a 0.164 increase in assault. An increase in the number of times that a haze phenomenon is observed was associated with an increase of 0.359 in assault cases. Haze had the most effect on theft, drug, and assault crimes in Riyadh compared to the other elements. Temperature and humidity have a significant relationship with crime in Makkah, while haze had no significant influence in that region.

Projections in Various Scenarios and the Impact of Economy, Population, and Technology for Regional Emission Peak and Carbon Neutrality in China

Owing to the surge in greenhouse gas emissions, climate change is attracting increasing attention worldwide. As the world's largest carbon emitter, the achievement of emission peak and carbon neutrality by China is seen as a milestone in the global response to the threat. By setting different "emission peak" and "carbon neutrality" paths, this study compares the different pathways taken by China towards regional emission reduction to illustrate China's possible contribution to global emission reduction, and analyzes the role that China's economy, population, and technology need to play in this process through the Stochastic Impacts by Regression on Population, Affluence, and Technology model. In terms of path setting, based on actual carbon emissions in various regions from 2000 to 2019 and grid data on land use from 2000 to 2020, the model simulates three emission peak paths to 2030 and two carbon neutrality paths to 2060, thus setting six possible carbon emission trends from 2000 to 2060 in different regions. It is found that the higher the unity of policy objectives at the emission peak stage, the lower the heterogeneity of the inter-regional carbon emission trends. In the carbon neutrality stage, the carbon emissions in the unconstrained symmetrical extension decline state scenario causes the greatest environmental harm. Certain regions must shoulder heavier responsibilities in the realization of carbon neutrality. The economic development level can lead to a rise in carbon emissions at the emission peak stage and inhibit it at the carbon neutrality stage. Furthermore, the dual effects of population scale and its quality level will increase carbon emissions at the emission peak stage and decrease it at the carbon neutrality stage. There will be a time lag between the output of science and technology innovation and its industrialization, while green innovation is a key factor in carbon neutrality. Based on the results, this study puts forward policy suggestions from a macro perspective to better realize China's carbon emission goals.

Can sustainable development policy reduce carbon emissions? Empirical evidence from resource-based cities in China

Resource-based cities (RBCs) have made outstanding contributions to China's social and economic development over recent decades. Nevertheless, with the worsening climate change and the exhausted resources, how to curb carbon emissions of RBCs to deliver their low-carbon transformation is becoming a problem plaguing the world. To facilitate the low-carbon transformation of RBCs, the Chinese government has formulated many policies, including the Sustainable Development Policy of National Resource-based Cities, 2013-2020 (SDPRC). However, the implementation of SDPRC has not yielded a clear environmental influence. Therefore, this study employs the Propensity Score Matching-Difference in Difference to investigate this influence based on the panel data of 285 prefecture-level cities from 2006 to 2017 while exploring the related heterogeneity and impact mechanisms. It is found that: (1) the implementation of SDPRC has significantly reduced carbon emissions and intensities of RBCs, with this effect becoming more conspicuous with the advancement of the policy. A robust test also verifies these findings. (2) Results from the heterogeneity test demonstrate that the implementation of SDPRC has imposed a suppressive effect on CO₂ emissions in eastern, central, and western Chinese regions, especially pronounced in the latter two regions. Except for the growing cities, which are not significantly affected by the policy, the other three types of cities have seen a catalytic effect on CO₂ emission reduction from the implementation of the policy, with the most significant impact observed in the declining cities. (3) Analyses of related mechanisms reveal that thanks to the implementation of SDPRC, RBCs suppress CO₂ emissions mainly by optimizing their industrial structures and relieving their energy intensities. Finally, some policy recommendations are proposed based on the findings of this study to facilitate the low-carbon transformation of RBCs.

Do bureaucratic policy and socioeconomic factors moderate energy utilization effect of net zero target in the EU?

Based on the commitment to improve environmental quality across European Union under the United Nations' Sustainable Development Goals and varying national goals, this study investigates the dynamic linkages between bureaucracy, socioeconomic factors, conventional fossil fuel energy consumption vis-à-vis aggregate fossil and disaggregate fossil (oil, coal, and gas) fuels and environmental quality in the panel of selected 25-EU nations for the period 1990-2017. The study employs relevant second-generation empirical method and unearth the following results: (1) inverted environmental Kuznets curve was validated while fossil fuel consumption has a deteriorating impact on environmental performance due to its positive effect on carbon emission; (2) fossil fuel energy consumption (both aggregate and it components) exerts a dampening impact on environmental performance due to its positive effect on carbon emission; (3) that direct effect of bureaucracy and socioeconomic factors promote environmental quality but the degree or magnitude of influence is significantly different between bureaucratic system and socioeconomic factor, and (4) the moderating or indirect impact of bureaucracy, socioeconomic on the environment via fossil fuel energy consumption is observed and significantly different across the model specification. Moreover, the result reveals a unidirectional causal relationship flows from GDP per capita, bureaucracy and socioeconomic factors to carbon emission, while bi-directional relationships between oil, gas and carbon emission are established. In policy direction, the study therefore recommend that the European Union member countries should further explore the opportunities in clean energy development in order to ameliorate the continent's environmental concerns. Furthermore, in the quest to scale up the bloc's energy transition, significant improvement in the countries' bureaucracy establishment and socioeconomic conditions could hasten the energy transition and efficiency policy while improving the environmental sustainability drive.

Green investments, financial development, and environmental quality in Ghana: evidence from the novel dynamic ARDL simulations approach

Numerous studies have examined the influence of macroeconomic factors on environmental quality in Ghana. However, to the best of our knowledge, there has been no study on the connection between green investments, financial development, and environmental quality in the context of this Sub-Saharan African country. This study was therefore conducted to help fill this gap using annual frequency time series data ranging from 1970 to 2018. In attaining the objectives of this study, robust econometric techniques were employed. From the results, all the variables were first differenced stationary and cointegrated in the long run. The dynamic ARDL simulations technique with the support of the ARDL estimator was employed to examine the elastic effects of the predictors on the response variable, and from the discoveries, green investments improved environmental quality in Ghana both in the long and the short run via carbon dioxide mitigations. However, in both the long and the short run, financial development and energy utilization had a detrimental influence on environmental quality due to their positive influence on carbon dioxide emissions. Moreover, the N-shaped association between national income and environmental pollution was validated for Ghana. On the causal directions amidst the variables, there was no causality between green investments and environmental degradation was evidenced; however, a bidirectional causality between financial development and environmental pollution was also discovered. Also, unidirectional causalities running from national income and energy consumption to environmental degradation were discovered. Based on the findings, the study recommend that investments in green sources should be intensified to help improve environmental quality in Ghana. Furthermore, improving developments in the financial sector is a vital means through which the country could attain its sustainable development goals.

What drives low-carbon agriculture? The experience of farms from the Wielkopolska region in Poland

Because of global environmental problems, low-carbon agriculture has gained increasing importance both in developed and developing countries. Hence, there is a need to find ways to develop more efficient agricultural systems. The purpose of this article is to identify the drivers of low-carbon agriculture on farms in the Wielkopolska region (in Poland). We aimed to take an original approach to investigate low-carbon agriculture with a unique set of different economic and environmental variables and contribute to the literature, which is not very extensive in terms of microeconomic research, including research on farmers in the Wielkopolska region. Therefore, we employed a multiple-factor measurement model for structural equation modeling (SEM) of data collected individually from 120 farms in 2020. As a result, we formulated the following conclusions: the increasing productivity of factors (land, labor, and capital) have a positive effect on low-carbon farming, just as increasing fertilizer and energy efficiency. Moreover, thermal insulation is also important for low-carbon agriculture, with efficiency of fertilizer use being the most important factor. We believe that the issues of farm use of fertilizers and thermal insulation of buildings should be more broadly included in energy policy, both at the national and the European Union (EU) levels. Some of these factors however are already present in the common agricultural policy (CAP) for 2021-2027.

Does the Real Estate Market and Renewable Energy Induce Carbon Dioxide Emissions? Novel Evidence from Turkey

In the literature, the linkage between income, energy, and carbon emissions has been widely examined and most of the empirical studies have not investigated the impact of the real estate market on their empirical models. Our study endeavors to present a novel topic by investigating the influence of the real estate market on Turkey’s environmental quality, using an advanced method of the Bootstrap Autoregressive Distributed Lag (BARDL). We estimate that consumption of renewable energy contributes significantly to CO2 emissions, while real income increases the environmental degradation in both the short and long run. Furthermore, our study demonstrates that the real estate market contributes negatively to the deduction of carbon emissions in Turkey. A one percent increase in the real estate market will cause a rise in Turkey’s carbon level by 0.010% and 0.009% in the short and long term, respectively. Our research suggests that Turkey should design new strategies for sustainable real estate markets to improve the environmental quality by supporting green investment projects.