A step towards sustainable path: The effect of globalization on China's carbon productivity from panel threshold approach

How informal environmental regulations constrain carbon dioxide emissions under pollution control and carbon reduction: Evidence from China

Exploring whether informal environmental regulations (INER) can achieve carbon reduction in the context of pollution reduction and carbon reduction, as well as how to achieve carbon reduction, can help solve the dual failures of the market and government in environmental protection. Based on the polycentric governance theory and considering the characteristics of social subject environmental participation, the Stackelberg game is used to demonstrate the impact mechanism of INER on CO2. In addition, using the panel data of China's 30 provinces from 2003 to 2018, this paper validates the effectiveness of INER by Pooled Ordinary Least Square (POLS) and threshold panel model. Then, the mediating effect model is used to test the mechanism of INER's effect on carbon reduction. The results show that corruption is not conducive to CO2 reduction. The reduction effect of INER on CO2 exhibits heterogeneity with changes in other non-greenhouse gas pollutants. While INER effectively reduces local corruption, its more substantial indirect impact on CO2 reduction is prominent when levels of other pollutants are lower. Comparative analysis reveals that there are still biased governance behaviors to cope with INER's pressure in some regions nowadays. The findings show that for countries facing the dual task of pollution control and carbon reduction, the key to leveraging the supervisory role of INER should be focused on mitigating information asymmetry caused by the characteristics of CO2. Therefore, in the process of environmental protection, the public environmental participation system should be improved, and the process of disclosing polluters' carbon information should be accelerated.

Economic globalization-energy diversification nexus and implications for environmental management in China

Every nation on earth has the responsibility to implement effective environmental management measures for sustainable environmental quality. In doing so, this study scrutinizes the relationship between economic globalisation and energy diversification in the Chinese economy from 1995 to 2022 for designing and implanting policies for environmental management. It uses industrialization, foreign direct investment, foreign remittances, and information & communication technology as supplementary factors into augmented energy diversification demand function. This empirical analysis shows cointegration between the variables, with economic globalisation positively impacting energy diversification. Factors such as foreign direct investment, foreign remittances, and information & communication technology contribute to energy diversity. However, industrialization has an adverse relationship with energy diversification. The relationship forms an inverted-U shaped between economic globalization and energy diversification. Our causality analysis indicates that economic globalization positively causes energy diversification. This study also reveals a reciprocal and beneficial cause-and-effect association between foreign direct investment and energy diversification. Lastly, foreign remittances and information & communication technologies positively cause energy diversification.

Evaluating the carbon total factor productivity of China: based on Cobb-Douglas production function

This paper introduces a novel methodology for estimating carbon total factor productivity based on the Cobb-Douglas production function. The research method introduced in this article expands upon the framework for assessing total factor productivity through the Solow residual method. It unifies the conceptual and methodological aspects of carbon total factor productivity with those of single factor productivity. Utilizing panel data from various provinces between 2010 and 2021, we computed carbon total factor productivity to understand its implications for China in combating global climate change. We demonstrate that (i) we have introduced a method to handle negative coefficients in the Cobb-Douglas production function by incorporating productivity in lieu of input factors during calculations. (ii) Carbon total factor productivity, encapsulating the geometric weighted mean of labor, capital, and carbon productivity, holds notable economic relevance. Further, it serves as an integrative metric comprising carbon productivity intertwined with the mean labor and capital carbon factors. And (iii) the influence of carbon total factor productivity growth on economic progression remains relatively subdued, with escalating labor force growth posing detrimental effects on several provincial economies. Enhancing carbon total factor productivity emerges as an imperative to harmonize robust economic growth with strategic carbon curtailment. Our analytical framework provides nuanced perspectives on productivity determinants, accentuating the thrust towards sustainable evolution amidst climatic challenges. This investigation bears profound significance for policymakers endeavoring to sculpt a carbon-conscious economic paradigm in consonance with global climatic ambitions.

The effects of green finance on enterprises' green innovation under the "dual carbon" goal: an exploratory study based on fsQCA

With increasing environmental degradation, green finance and green innovation have attracted the attention of policymakers and industries. However, the impact of green finance on corporate green innovation is still unexplored. Based on signal theory, this study analyzes the mixed effect of green finance on green innovation in enterprises. We use data from 31 provinces (333 cities in total) in China in 2021 and use a fuzzy set qualitative comparative analysis method. Green finance factors include green credit, green bond, green investment, green insurance, and green subsidy. Our research findings are as follows: Firstly, green innovation in businesses is not a product of a single antecedent situation but rather the interaction of several antecedent conditions. Green insurance and green subsidy are the core prerequisites for high green innovation in enterprises, and green credit plays an auxiliary role. Secondly, when there is a lack of green insurance, green bonds and green subsidies play a key role, leading to a high level of green innovation in businesses. Thirdly, the impact of various antecedents on the level of green innovation performance in enterprises is asymmetric. Policymakers should fully leverage the effect of green subsidy signals and minimize the risks of green innovation by expanding financing channels. Our findings enrich the literature on green innovation and finance and provide beneficial practical insights for green innovation in enterprises.

Spatial effects of trade, foreign direct investment (FDI), and natural resource rents on carbon productivity in the GCC region

Background

Natural resource rents (NRRs) may determine the environment and economic growth of the GCC countries due to their over-reliance on the natural resource sector. NRRs are the source of income in resource-abundant GCC countries. So, increasing income of these countries could pollute the environment by increasing overall economic activities. Consequently, NRRs could determine carbon productivity in the GCC region through increasing income and carbon emissions.

Methods

The effects of trade openness (TO), foreign direct investment (FDI), urbanization, and oil and natural gas rents on carbon productivity (CP) are examined in the GCC region from 1980-2021 using the spatial Durbin model.

Results

The CP of the GCC countries has spillovers in their neighboring countries. Oil rent reduces carbon productivity in domestic economies and the entire GCC region. Natural gas rent, TO, and FDI increase, and urbanization reduces carbon productivity in neighboring economies and the entire GCC region. Moreover, urbanization reduces carbon productivity in domestic economies as well. The study recommends the GCC countries to reduce reliance on oil rent and increase globalization in terms of TO and FDI in the region to promote carbon productivity. Moreover, GCC countries should also focus more on natural gas rent instead of oil rent to raise carbon productivity.

Regional common prosperity level and its spatial relationship with carbon emission intensity in China

The characteristics of common prosperity include harmonious relationships between humans and the environment, as well as sustainable economic and social growth. The process of achieving common prosperity will necessarily have an impact on carbon emissions. In this article, panel statistics collected from 30 Chinese provinces and cities between the years 2006 and 2020 are utilized to assess the level of common prosperity and the intensity of carbon emissions in China. Then the SDM model is applied to explore the effects of the common prosperity level on the intensity of carbon emissions. The findings reveal that: (i) The common prosperity level in China has shown an increasing tendency. Between 2006 and 2020, the mean level of common prosperity increased from 0.254 to 0.486. From the regional perspective, eastern China has seen greater levels of common prosperity than central China, while central China has experienced greater levels of common prosperity than western China; regional disparities in the degree of common prosperity are substantial among Chinese provinces from 2006 to 2020; the common prosperity level is relatively high in economically developed provinces and relatively low in economically backward provinces. (ii) China's carbon emission intensity shows a continuous downward tendency. The annual average intensity of China's carbon emissions decreased from 4.458 in 2006 to 2.234 in 2020. From the regional perspective, the three main regions' carbon emission intensity likewise exhibits a decline in tendency between 2006 and 2020; still, western China continues to have the greatest carbon emission intensity, following central China, while eastern China has the smallest; however, certain provinces, notably Inner Mongolia and Shanxi, continue to have high carbon emission intensity. (iii) China's common prosperity level and carbon emission intensity both exhibit positive spatial autocorrelation at a 1% significant level under the adjacency matrix. The spatial agglomeration effect is significant, and adjacent provinces can affect each other. (iv) The SDM (Spatial Durbin Model) model test with fixed effects finds that the increase in the level of common prosperity suppresses the intensity of carbon emissions in the local area and neighboring regions. (v) The mediating effects model indicates that the process of common prosperity suppresses carbon emission intensity through high-quality economic development, narrowing the income disparity, and the development of a sharing economy.

Does globalization matter in the relationship between renewable energy consumption and economic growth, evidence from Asian emerging economies

The study aims to investigate the impact of social, economic and political globalization on the renewable energy-economic growth nexus in a panel of six Asian emerging economies over the period 1975-2020. The results of the CS-ARDL approach show that renewable energy consumption contributes significantly to long run economic growth. Economic and political globalization firmly hold back economic growth, while social globalization directly promotes economic growth. The nonlinear effects of political, social, and economic globalization on economic growth clearly demonstrate the validity of the inverted U-shaped relationship between political globalization, economic globalization, and economic growth, and the U-shaped relationship between social globalization and economic growth. The study also found that economic, social and political globalization moderated the impact of renewable energy on boosting economic growth. Based on the renewable energy consumption model, it is revealed that economic growth significantly promotes long run renewable energy consumption. Economic, social, and political globalization have significantly boosted long run renewable energy consumption. However, the nonlinear effect model reflects a U-shaped relationship between globalization indicators and renewable energy consumption. The interaction of political, economic, and social globalization with economic growth has also witnessed an increase in renewable energy consumption, which supports the scale effect hypothesis. The causality test concludes that there is a two-way causal relationship between renewable energy consumption and economic growth, thus supporting the feedback hypothesis. The policy implications for Asian emerging economies are discussed based on the empirical analysis of this study.

The evolutionary characteristics and influencing factors of total carbon productivity: evidence from China

In order to systematically understand the evolution of total factor carbon productivity and explore its influence mechanism, based on panel data of 30 Chinese provinces from 2005 to 2019, the slacks-based measure of directional distance functions model and the Luenberger index are used to estimate the evolution of total factor carbon productivity, and the SYS-GMM model is constructed to explore the drivers of total factor carbon productivity and its influence effect. The results show that from 2005 to 2019, the overall level of total factor carbon productivity was low, but its growth index and decomposition term both showed an increasing trend; the development of total factor carbon productivity has regional differences. Only the eastern, northern, and middle Yellow River economic regions experience positive growth in total factor carbon production. The downward trend of total factor carbon productivity is most significant in the northwest and southwest economic regions, with - 2.577% and - 1.463%, respectively; improvements in scale technology are the main reasons for improving total factor carbon productivity across time and regions; economic growth and environmental regulations contribute to total factor carbon productivity at 1% significance level, and industrial structure has a negative impact. Foreign direct investment inhibits total factor carbon productivity, but the effect is not significant. Based on these findings, this paper provides an effective reference for achieving the goal of low-carbon sustainable development and improving total factor carbon productivity.

Influence mechanisms and spatial spillover effects of industrial agglomeration on carbon productivity in China's Yellow River Basin

The ecological protection and high-quality development of the Yellow River Basin have become major national strategies in China. Therefore, reducing carbon emissions in the Yellow River Basin through efficient industrial agglomeration is necessary for achieving the goals of carbon peak by 2030 and carbon neutrality by 2060. The Yellow River Basin is an important base for energy, chemicals, raw materials, and industry in China, making it important to study the effects of different industrial agglomeration types on carbon productivity from the perspective of agglomeration externalities. Therefore, taking 2009-2019 panel data for prefecture-level cities in the Yellow River Basin, this study uses a spatial Durbin model to investigate the spatial spillover effects of industrial agglomeration (i.e., specialized, diversified, and competitive agglomeration) on carbon productivity. Furthermore, the moderating effects of urbanization level and environmental regulation are analyzed. The results reveal, first, the existence of spatial correlation in carbon productivity across different cities in the Yellow River Basin. Second, diversified and competitive agglomeration significantly increase carbon productivity, although competitive agglomeration has beggar-thy-neighbor spillover effects. Meanwhile, the effect of specialized agglomeration is not significant. Third, the effects of different types of industrial agglomeration differ significantly between cities in different locations and with different resource endowments. Fourth, urbanization level and environmental regulation have different moderating effects in the relationship between different types of industrial agglomeration and carbon productivity. These findings provide evidence for further developing rational industrial agglomeration patterns to enhance carbon productivity in the Yellow River Basin.

The impact of economic uncertainty, economic growth and energy consumption on environmental degradation in MENA countries: Fresh insights from multiple thresholds NARDL approach

This paper explores the influence of economic policy uncertainty on environmental quality in selected MENA countries depending on an augmented STIRPAT model over the period 1970-2020. ARDL model and its extensions like augmented ARDL, augmented NARDL, and MTNARDL models are applied to detect any possible effect from uncertainty index to carbon dioxide (CO₂) emissions. The empirical results reveal the validity of environmental Kuznet curve (EKC) curve in all the countries. Moreover, the results show that the uncertainty index enhances environmental degradation, especially in extremely large changes in Morocco, Turkey, and Iran. Besides, the findings reveal that energy consumption and population in the entire sample escalates CO₂ emissions over the study period. Consequently, policymakers in MENA countries should consider the economic uncertainty index, particularly in light of its recent rise, when developing any strategies and plans aimed at improving environmental standards, as well as the need to encourage the use of renewable energies in order to increase the percentage of their contribution to total energy consumption.

Does technology innovation matter for environmental pollution? Testing the pollution halo/haven hypothesis for Asian countries

China's GDP grew 9% annually during the end of the twentieth century. This economic growth degrades China's ecology, making it the world's greatest polluter. This position forced China to invest in developing nations and to take advantage of low-cost labor and increased pollution quotas from the World Trade Organization (WTO) to meet sustainable development objectives without environmental harm. The significance of this study is, first, this study examines the influence of Chinese outward foreign direct investment, gross domestic product, trade openness, technological innovation, and energy consumption on carbon emissions in Asian countries (Turkey, Pakistan, the Philippines, Singapore, India, Indonesia, and Cambodia). Secondly, the panel autoregressive distributed lag cointegration (ARDL) technique was used on data from 2000 to 2020 to investigate the pollution halo/haven hypothesis and environmental Kuznets curve hypothesis for south Asian nations. This analysis demonstrated that Chinese outbound foreign direct investment increases carbon emissions and confirms the pollution halo concept. Except for India and Pakistan, these nations show a U-shaped link between Chinese foreign direct investment and carbon emissions. So, policy implications recommended by the results of this study are foreign direct investment inflows with modern and ecofriendly technological transfer and enhancement in labor, and conservational management practices will benefit emerging countries to attain their sustainable development goals.

Exploring the mediating role of environmental strategy, green innovations, and transformational leadership: the impact of corporate social responsibility on environmental performance

This study examines the impact of corporate social responsibility (CSR) on environmental performance by utilizing data collected from ten big industrial organizations operating in Lahore, Pakistan. The research data was organized using the cross-sectional process. Of the 316 questionnaires completed by employees, 226 were considered valid, and these responses were used for further PLS analysis. The findings of the research indicate CSR has a moderate impact on environmental performance. Furthermore, the result revealed that green innovation, green capability, environmental strategy, and green transformational leadership are a better ecological performance example that could mediate CSR and environmental performance. This research study postulates the existing resource-based view (RBV) theory for overall directors of industrial organizations and representatives to achieve and manage CSR, green innovation, green capability, environmental strategy, and green transformational leadership to find optimal environmental performance. Thorough study will provide valuable inputs to the overall directors and managers of the enormous industrial sector to support their internal strategies such as CSR, green innovation, green capability, environmental strategy, and green transformational leadership to expand the environmental performance (to help directors, managers, policymakers, and executives to take appropriate/profitable decisions in the future).

Analysis of the dynamics of environmental degradation for 18 upper middle-income countries: the role of financial development

This study aims at investigating the dynamics of environmental degradation by focusing on the financial development-CO₂ emissions link. In this purpose, economic growth, renewable energy consumption, trade openness and urbanization are integrated into the CO₂ emissions model as other explanatory variables. In this study, 18 upper-middle-income countries with the highest growth rate in the world are examined for the period 1990-2018 by AMG method, which considers the cross-sectional dependence and slope heterogeneity. In addition, the causal linkages between variables are explored by Dumitrescu-Hurlin panel bootstrap causality technique. As a result of the study, it is found that financial development and renewable energy consumption reduce CO₂ emissions. In addition, it is determined that economic growth, urbanization, and trade openness deteriorate the environmental quality. As a result of causality analysis, while one-way is found from renewable energy consumption to CO₂ emissions, a bidirectional causality is observed between financial development and CO₂ emissions. Empirical findings provide several policy suggestions that decrease CO₂ emissions in these countries.

Hydropower, human capital, urbanization and ecological footprints nexus in China and Brazil: evidence from quantile ARDL

The relations among ecological footprints, biocapacity per capita, gross domestic product per capita, natural resources, urbanization, human capital, and hydroelectric consumption are analyzed from 1971Q1 to 2017Q4 for Brazil and China. The novel quantile autoregressive distributive lag method was employed to analyze the long-run and short-run dynamics of environmental degradation. The findings revealed that economic growth has a positive role in the environmental degradation of both countries. However, human capital, natural resources, and hydropower have heterogeneous effects across quantile distribution and between the two countries. Based on the quantile dynamics of environmental degradation, the present study mentions policy implications for sustainable development.

Linking shadow economy and CO2 emissions in Nigeria: Exploring the role of financial development and stock market performance. Fresh insight from the novel dynamic ARDL simulation and spectral causality approach

First and foremost, the present study seeks to traverse the informal sector characterized by a shadow economy in the presence of financial development, economic growth, and stock market performance on environmental pollution in Nigeria from 1981 to 2019. The dynamic autoregressive distributed lag (DARDL) approach was used to measure the short- and long-run elasticities, while spectral causality is applied to categorize the causal directions. Findings from the study revealed that the structural break unit root test revealed that all variables are stationary at first difference. The ARDL bound test confirmed the existence of long-run association among the used variables. The ARDL long-run results reveal that economic growth, financial development, and stock market performance are significantly responsible for carbon emission in Nigeria, while the shadow economy significantly improves environmental quality in Nigeria. Findings from the spectral causality results show a unidirectional causal relationship between financial development, economic growth, trade, stock market performance, and shadow economy to carbon emission in Nigeria. The empirical findings of this study provide some perceptive policy recommendations to overcome the adverse effect of carbon emissions in the environment.

Analysis of coordination between urban compactness and green total factor energy efficiency: a case study of 35 cities in China

Rapid urban expansion and energy transformation are two major challenges facing China. Many researchers have explored urban compactness and energy efficiency, but there is little literature on the coordinated development of the two. Therefore, this paper takes 35 cities in China as research object: The urban compactness evaluation index system is established, and the score is calculated using the entropy weight method; considering the bad output, SBM is used to calculate the green total factor energy efficiency (GTFEE); and the coupling coordination degree model is used to calculate their coordinated degree. The following conclusions can be inferred: (1) Although China's urban compactness has increased, it has not maintained a steady upward trend. Some more developed cities have the phenomenon of compactness rising first and then falling; (2) The overall GTFEE shows a continuous upward trend, but there is still much room for improvement, and regional disparities are significant; (3) The degree of coordination between the two maintains a steady upward trend, and the city's compactness lags behind GTFEE. Based on the findings of the study, this paper proposes policy recommendations that can serve as a reference for key decision-makers and are critical in promoting China's urbanization and energy transformation.

Research on carbon productivity and its spatial convergence of steel industry in China

The Global-Malmquist-Luenberger (GML) index was applied to analyze the carbon productivity in steel industry (SICP) of 29 provinces in China from 2006 to 2019, and then, the SICP was decomposed into technical efficiency change index (TC) and technical progress index (EC). On this basis, the spatial effect is introduced into the traditional convergence model to investigate the spatial convergence of SICP. The empirical results show that: (1) the overall carbon productivity of China's steel industry is at a relatively low level, showing a slow growth trend. (2) The average value of the GML index of SICP is higher than 1, showing obvious inter-provincial and regional heterogeneity. Compared with TC, EC is the leading factor that promotes the increase of SICP. (3) The spatial absolute and condition β convergence of SICP exist in the whole country and the three major regions, but the σ convergence feature is not significant. The addition of spatial factors speeds up the convergence trend, and the speed of spatial absolute β convergence is about 3 times that of the classical convergence model. At the same time, the conditional convergence rate is significantly faster than the absolute convergence, which is closely related to the differences in influencing factors such as the industrial structure, economic development level, human capital, energy consumption intensity, and R&D investment among regions. There is still much room for improvement in carbon productivity in China's steel industry, and investment in scientific research must be increased in order to achieve the upgrading of the industrial structure and technological innovation. The existence of spatial convergence requires strengthening the joint reorganization of steel enterprises between provinces and regions, making full use of the spatial spillover effects of production technology, and realizing regional green and coordinated development.

Do Nuclear Energy, Renewable Energy, and Environmental-Related Technologies Asymmetrically Reduce Ecological Footprint? Evidence from Pakistan

Can Pakistan’s environmental-related technologies (ERT) and nuclear and renewable energy mitigate environmental pollution? As global warming and climate change rise dramatically, economies shift to friendly energy substitutions and eco-friendly technologies, contributing to the mitigation of environmental contamination. In this scenario, policy and academic analysts have paid more concentration to renewable and nuclear energy deployment with ERT installation. To achieve this goal, the present study scrutinizes the asymmetric effects of nuclear energy, renewable energy, and ERT on the ecological footprint of Pakistan. The current research applies a novel non-linear autoregressive distributive lag method from 1991 to 2020. The results of the current analysis show that negative changes in nuclear energy increase emissions levels in the long run, while positive and negative changes in renewable energy deployment significantly overcome the burden on the environment. Similarly, positive and negative changes in ERT reduce pollution levels in the long run. Moreover, these long-run outcomes are analogous to short-run findings for Pakistan. Therefore, there is a dire requirement to increase the consumption of renewable and nuclear energy sources and take advantage of the noteworthy impact of an uncontaminated atmosphere through clean ERT potentials.

Determinants of renewable energy sources in Pakistan: An overview

For successive economic growth of any society, sustainable energy plays a pivotal role. Considering this view, developing countries are facing serious challenges of energy at the present time. However, policymakers have outlined numerous policies to satisfy energy demand but still remain incapable to fill the gap between demand and supply. At a halt, 11% of the world population lacks access to different formulae of energy supply and access. Additionally, in different time periods, distinct policies have erupted for the progress of renewable energy. It includes especially those households of the far-flung areas having no gas and electricity availability. However, the basis of this research study is to determine the significant renewable energy source for Pakistan's economy with the economic benefits such as job creation in energy sector. This research study aims in finding ways to secure energy supplies and achieving economic benefits. The research study concludes by engaging renewable energy technologies with the least operational and externality cost that is the utmost choice in the future. In policy perspective, Pakistani government should take actions in favor of renewable energy and technological innovation that necessitates biomass resources to be tied to non-sustainable prolonged investments.

Fresh insight through the VAR approach to investigate the effects of fiscal policy on environmental pollution in Pakistan

This study explores the impact of fiscal policy on environmental pollution, employing the vector autoregressive (VAR) model on annual data from 1976 to 2018 in Pakistan. We estimate the effect of total expenditure, total revenue, education expenditures, health expenditures, and other dynamic determinants such as gross domestic product (GDP), private investment, market rate, and crude oil price on carbon dioxide (CO₂) emissions in particular. Further, this study creates impulse response functions to check the fiscal shocks, coordinating with five scenarios of public expenditures, segregated into government revenue, and education and health expenditures. The outcomes indicate that government spending in the public sectors (education and health) had a diminishing effect on CO₂ emissions, whereas government revenue that was collected from taxes improved economic growth but at a cost of environmental pollution. In Pakistan, a fiscal policy scenario has been implemented that increases government expenditures to alleviate the effects of CO₂ emissions. Therefore, policymakers should provide the right direction for the feasible distribution of resources in every public sector through a powerful structure, which will ultimately reduce the overall level of environmental deficit.

The impact of environmental regulations on export trade at provincial level in China: evidence from panel quantile regression

Based on panel data from 30 provinces in China from 2008 to 2017, this paper constructs a quantile regression econometric model to analyze whether China's environmental regulation has an impact on export trade and to verify whether the Porter hypothesis has been valid in China in recent years. The results show that in the short term, environmental regulations have a restraining effect on export trade, while in the long run, due to the existence of innovation efficiency, environmental regulations will change from having a restraining effect to a promoting effect on export trade. Strict environmental regulations will reduce the production cost of Chinese products, further improve the export competitiveness of Chinese enterprises, and promote export trade. The empirical results verify the conclusion that the Porter hypothesis is confirmed in China. The following three suggestions are proposed for China's exports to promote the win-win of China's green development and export trade: promote the realization of international and domestic double circulation, avoid becoming "pollution shelters" and support technological innovation in environmental protection industries.

Environmental pollution and agricultural productivity in Pakistan: new insights from ARDL and wavelet coherence approaches

The most serious challenge to the global facade is figuring out how to mitigate pollution levels without compromising agricultural productivity. The spillover effect of environmental change is predicted to be very high, although it will differ by region and crop. Considering this view, this study tries to address this issue by adopting comprehensive methodologies to assess the influence of carbon dioxide (CO₂) emissions, agricultural labor, land, feeds, and fertilizers on agricultural productivity in Pakistan from 1961 to 2018. The autoregressive distributive lag (ARDL) and wavelet transform coherence (WTC) approaches are applied to estimate the long-run and short-run elasticity estimates. The empirical findings discover that CO₂ emissions, agricultural land, labor, feed, and fertilizers exert high pressure on agricultural productivity which is backed up by the WTC findings. Furthermore, the gradual shift causality test results reveal the presence of a unidirectional causality relationship between all regressors and agriculture productivity, demonstrating that all the factors significantly influence agriculture productivity. Moreover, these findings are robust to different robustness tests that we perform to test the reliability/accuracy of our core results. From policy perspectives, regulations must be developed to explore a practicable expansion strategy that includes the use of efficient fertilizers and feed at optimal levels, as well as environmental protection through public-private investment in the agricultural sector.

Forecasting carbon emissions due to electricity power generation in Bahrain

Global warming and climate change have become one of the most embarrassing and explosive problems/challenges all over the world, especially in third-world countries. It is due to a rapid increase in industrialization and urbanization process that has given the boost to the volume of greenhouse gases (GHGs) emissions. In this regard, carbon dioxide (CO2) is considered a significant driver of GHGs and is the major contributing factor for global warming. Considering the goal of mitigating environmental pollution, this research has applied multiple methods such as neural network time series nonlinear autoregressive, Gaussian Process Regression, and Holt's methods for forecasting CO2 emission. It attempts to forecast the CO2 emission of Bahrain. These methods are evaluated for performance. The neural network model has the root mean square errors (RMSE) of merely 0.206, while the Gaussian Process Regression Rational Quadratic (GPR-RQ) Model has RMSE of 1.0171, and Holt's method has RMSE of 1.4096. Therefore, it can be concluded that the neural network time series nonlinear autoregressive model has performed better for forecasting the CO2 emission in the case of Bahrain.

Impact of globalization on CO2 emissions based on EKC hypothesis in developing world: the moderating role of human capital

In the last 3 decades, developing economies continuously have increased their manufacturing industries with an impressive growth rate. Rising the trend of globalization, these underdeveloped economies are receiving economic growth at the cost of environmental degradation. In this context, this study investigates the impact of globalization and human capital on carbon emissions (CO₂) in the 78 developing economies from 1990 to 2016. Our findings based on robust system generalized method of moments (GMM) indicate that human capital and political globalization significantly reduce environmental degradation while economic, social, and overall globalization decrease the environmental quality. Furthermore, our empirical results support the inverted U-shaped environmental Kuznets curve (EKC) hypothesis. However, globalization (without interactive term with human capital) appears to have no significant association with CO₂ emissions, while (with an interactive term) it appears to have a significant negative influence on environmental quality. Moreover, our results are robust to various robustness checks; I have performed for scrutiny the consistency of our findings. This study also offers useful policy implications for stakeholders, policymakers, and governments for promoting environmental sustainability.

The role of remittance inflow and renewable and non-renewable energy consumption in the environment: Accounting ecological footprint indicator for top remittance-receiving countries

This study examines the impact of remittance inflow and foreign direct investment on ecological footprint in top ten remittance-receiving counties in the presence of economic growth and renewable and non-renewable energy under the framework of environmental Kuznets curve (EKC) hypothesis over the period of 1990-2018 by employing the continuously updated fully modified (CUP-FM) and the continuously updated bias-corrected (CUP-BC) estimators. The results show that remittance inflow, foreign direct investment, and non-renewable energy utilization affect the ecological footprint positively while renewable energy utilization negatively impacts on ecological footprint. This study also supports the pollution haven hypothesis and inverted U-shaped EKC hypothesis. The turning point obtained from long-run regression was found to be approximately $1368.65 outside of the sample period. Besides, the results are robust to various robustness analyses that we have executed for inspection of the reliability of our main findings. Finally, this study presents important policy implications with respect to the top remittance-receiving countries.

Green Technology Innovation, Globalization, and CO2 Emissions: Recent Insights from the OBOR Economies

This study explores the connection between technological innovation, globalization, and CO2 emissions by controlling the critical influence of information and communication technology (ICT) and economic growth in a panel of One Belt One Road (OBOR) countries from 1991 to 2019, utilizing advanced and robust econometric strategies (second generation). In addition, this study also uses an interaction variable (TI*GLOB) to check the interaction role of technological innovation on the linkage between globalization and CO2 emission, besides their direct effect on CO2 emissions in OBOR countries. The outcomes revealed that the linkage between technological innovation and CO2 emissions is negative, and statically significant in all the regions (e.g., OBOR, South Asia, East and Southeast Asia, MENA, Europe, and Central Asia). Moreover, the results of globalization show a significant positive relationship with CO2 emissions in OBOR and South Asia region. Nevertheless, it significantly negatively affects environmental pollution in East and Southeast Asia, MENA, Europe, and Central Asia. The results of TI*GLOB indicate that, for the OBOR sample, East and Southeast Asia, and Central Asia, the moderation effects of technological innovation with globalization are significantly negatively associated with CO2 emissions. However, in MENA and Europe, the interaction effect is a significant positive. The coefficient of ICT for OBOR, Europe, and Central Asia are positive and statistically significant; however, for East, Southeast Asia, and MENA regions, these results are statistically negative. Furthermore, the findings are robust, according to various robustness checks that we have performed for checking the reliability of our main findings. The study establishes numerous polities and makes various recommendations, in light of relevant conclusions.

Revisiting the Role of Fiscal Policy, Financial Development, and Foreign Direct Investment in Reducing Environmental Pollution during Globalization Mode: Evidence from Linear and Nonlinear Panel Data Approaches

Fiscal policy is a crucial government tool for influencing and managing the national economy and creating a strong incentive for low carbon investment. Previous literature has reputable evidence that improving fiscal policy enhances environmental quality. However, the literature fails to classify the exact turning level (threshold point) below/above which the association may be negative or positive. In this regard, this research investigates the nexus between fiscal policy, foreign direct investment, financial development, trade openness, urban population, gross capital formation, labour force, and CO2 emissions in the era of globalization. The panel data set contained 105 countries over the period from 1990 to 2016. The empirical findings are estimated through linear and nonlinear panel data approaches such as fully modified ordinary least square and panel threshold regression. The subsequent findings are established: first, fiscal policy and globalization significantly increase environmental pollution. Second, the empirical results confirm the existence of the pollution haven hypothesis (PHV). Third, financial development and gross fixed capital formation are also considered some of the most crucial indicators to increase pollution levels. Fourth, trade openness, urban population, and labour force improve environmental quality. Fifth, panel threshold regression discovers that countries maintain a minimum level of fiscal policy at −1.2889. Based on these empirical findings, this study suggests that policymakers and governments of these countries should take steps to restructure their industrial sector and design macroeconomic-level carbon-free policies to support the implementation of low-energy-intensive and lower carbon production technologies.