Dynamic relationship among agriculture-energy-forestry and carbon dioxide (CO2) emissions: empirical evidence from China

The relationship between energy and non-energy factors and CO2 emissions in New Zealand

The use of renewable energy as a fuel source and expansion of forest areas are the best ways for reducing CO2 emissions. This study aims to examine the effects of forest plantation area, renewable energies, real gross domestic product (GDP), and technological innovation on CO2 emissions in 9 regions of New Zealand between 2006 and 2019. For this purpose, it employs a pooled mean group methodology. Investigating the regional impacts of various variables, especially the forest area, on CO2 emissions is the main contribution of this study. The results suggest that planted forest areas can reduce CO2 emissions in the long run, but its impact in the short run is not significant. Non-renewable energy consumption is the major contributor to CO2 emissions in both the short and long run. While technological innovation and renewable energy consumption appear effective in reducing carbon emissions in the short term, they still contribute to increased CO2 emissions in the long term. At the regional level, we found that the forest plantation areas in Manawatu-Whanganui and Gisborne are important regions for reducing CO2 emissions. By taking account of these results, New Zealand should take swift action to properly manage and increase the current level of forest areas and if applicable expand them. It also needs to improve the current level of use of renewable energy to achieve its abatement goals.

Sectoral foreign direct investment and environmental degradation: new insights from diversification of energy mix containing fossil fuels and renewable energy

The objective of the study is to extend the existing literature by investigating the effects of foreign direct investment, gross domestic products and per capita and energy diversification on the nitrogen oxide emissions in Brazil, Russia, India, China and South Africa (BRICS) by using annual data during the period 1992-2019. As per our knowledge, the present study is a first of its kind to examine the impact of a new energy diversification index, based on Herfindahl-Hirschman framework on pollution. This study has adopted a new quantile regression augmented method of moments, which is capable of producing the total impacts of the independent variables across the entire distribution of nitrogen oxides emissions. The findings suggest that an increase in foreign direct investment leads to a decrease in nitrogen oxides emissions at the aggregate level and in both manufacturing and service sectors. We observe that foreign direct investment leads to an increase in nitrogen oxides emissions in the agricultural sector in most of the quantiles. Diversification towards renewable energy causes a decrease in nitrogen oxides emissions in most quantiles at aggregate level, agricultural and manufacturing sectors, whilst diversification leads to an increase in nitrogen oxides emissions in the service sector. The findings also suggest that GDP per capita leads to an increase in NOx emissions in all the quantiles. The study suggests the policy to use and attract more clean energy through foreign direct investment for towards the achievement of sustainable development.

The role of eco-innovation, renewable energy consumption, economic risks, globalization, and economic growth in achieving sustainable environment in emerging market economies

In the last two decades, environmental degradation has been a topic of concern. The rising level of CO2 emissions (CO2E) has adversely affected life in the E7 countries, which comprise of Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. The increased in CO2E is the cause of rising sea levels in the E7 countries. Visibly, E7 nations which are considered as the largest emitters of CO2 are facing the most severe environmental challenges. This study investigates the impact of eco-innovation, economic growth (EG), renewable energy consumption (REC), economic risk (ERI), and globalization on the CO2E, using the Feasible Generalized Lease Squares (FGLS) and Panel Corrected Standard Errors (PCSE) techniques for the period 1995 to 2018. The results indicate an inverted N-shaped relationship between eco-innovation and CO2E. Also, eco-innovation, REC, and economic risk are observed to be significant factors in abating CO2 emissions. On the contrary, globalization and GDP are responsible for rising CO2E in E7 countries. According to empirical estimates, eco-innovation improves the efficiency of carbon emissions, which lowers CO2E. In addition, because they are immune to changes in the price of oil and gas and disruptions brought about by geopolitical events, renewable energy sources can offer countries a more secure energy source than fossil fuels. Alternative energy sources can reasonably cut CO2E while offering a more reliable and secure energy source. Therefore, it is crucial that policies be put in place to cut CO2E by giving priority to environmental innovative policies.

Renewable energy, forest cover, export diversification, and ecological footprint: a machine learning application in moderating eco-innovations on agriculture in the BRICS-T economies

The United Nations Climate Change Conference (COP26) recommended that the member nations enhance their technological progression and structural transformation to mitigate the problems of climate change. The BRICS-T countries consisting of Brazil, Russia, India, China, South Africa, and Turkey agreed to implement COP26's policy suggestions. These countries accounted for 40% of global greenhouse gas emissions in 2017, thus posing severe threats to the global environment. The current study explores the role of renewable energy, forest depletion, eco-innovations, and export diversification in impacting the ecological footprint for those BRICS-T countries. We further examine the moderating effect of eco-innovations on agriculture on the BRICS-T nations. The study contributes to the existing literature by providing newer empirical insights on how eco-innovations and export diversification, along with renewable energy, forest cover, and agriculture, affecting the ecological footprint in the BRICS-T nations. It utilizes novel empirical methods like parametric and non-parametric techniques to derive the short-run and long-run empirical results. The empirical findings based on the augmented mean group and the kernel regularized least square methods document that economic growth, agriculture value added, and forest depletion increase the ecological footprint. In contrast, renewable energy and eco-innovations decrease the level of ecological footprint. In the long run, a 1% rise in GDP leads to a rise in the ecological footprint by 0.64% using the augmented mean group (AMG) estimation. The mean marginal effects are - 0.27%, 0.29%, and 0.17% for renewable energy; agriculture and forest cover, respectively, using the kernel-based regularized least square methods. The study suggests that policies designed for controlling the ecological footprints focus on the use of energy efficient technologies, particularly in the agricultural sector.

How do carbon emissions, economic growth, population growth, trade openness and employment influence food security? Recent evidence from the East Africa

East Africa has a substantially greater rate of food insecurity than other regions of the world. Scenarios of climate change and other macroeconomic variables are important contributors to food insecurity in East Africa. Using data spanning from 1990 to 2020, this study looked into the influence of carbon dioxide (CO₂) emissions, economic growth, population growth, trade openness, and agricultural employment on food security in the East Africa. The fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models were used in this study. The heterogeneous panel cointegration test's findings indicated that the study variables have an equilibrium long-term connections. The estimation findings from the FMOLS and DOLS models showed that an increase in CO₂ emissions increases food security in the East Africa over the long term. According to other findings, long-term food security is positively impacted by economic expansion, population growth, trade openness, and employment in agriculture. However, trade openness has a detrimental long-lasting effect on food security. Future research directions, research limitations, and policy implications are discussed.

The asymmetric effect of agriculturalization toward climate neutrality targets

Agricultural activities immensely contribute to greenhouse gas emissions (GHGs). This study investigates the heterogeneous effect of agricultural production (AGRIP) on three major GHGs emissions, i.e., carbon dioxide (CO₂), nitrous oxide (N₂O), and methane (CH₄) under the Environmental Kuznets Curve (EKC) framework using a balanced panel data of 90 countries from the period 1991 to 2019. Second-generation panel unit root and cointegration tests are conducted to account for cross-sectional dependence. The findings suggest that there is a long run equilibrium among target variables. Evidence from panel quantile regression suggests that AGRIP significantly reduced CO₂ emissions, and the effect is stronger in lower quantiles (least carbon emitters). On the other hand, AGRIP increases N₂O and CH₄ emissions in all quantiles. However, AGRIP is homogeneously distributed across N₂O quantiles while the effect is stronger in higher quantiles (high methane emitters) in the case of CH₄ model. Concerning agricultural trade, exports impede CO₂ emissions but increase N₂O and methane emissions. Agricultural imports are positively associated with all GHGs emissions. The effect of agricultural trade is largely heterogeneous and varies across different quantile levels of GHGs emissions. The EKC is fully valid for CO₂ and N₂O but not for the methane emissions model. Based on the results, it is suggested that high GHGs emitter should shift their agricultural activities from traditional to sustainable approaches along with green trade policies to achieve climate neutrality targets.

Technology innovations impact on carbon emission in Chinese cities: exploring the mediating role of economic growth and industrial structure transformation

China seems ambitious to achieve a "carbon emissions peak" before 2030 and "carbon neutrality" before 2060. To deal with this emissions mitigation plan, technology innovations are regarded as a crucial factor. However, considering its rebound effect (CO₂ emissions driving effect) through economic growth, technology innovations might not prove a promising contributor to CO₂ reduction. Therefore, there is a need to investigate further the nexus between technology innovations and CO₂ emissions for conclusive debate. Based on the data of 215 cities in China, this paper uses mediating effects model to investigate the direct and indirect impacts (through economic growth and industrial structure transformation) of technology innovations on CO₂ emissions from a microeconomic perspective. The main results suggest that technology innovations generally increase CO₂ emissions in China both directly and indirectly. The impact of technology innovations and economic growth on CO₂ emissions indicated the EKC characteristics. Furthermore, the contributions of technology innovations to CO₂ emissions are distinguished in different regions. Thus, there is an urgent need for China to promote innovations in "clean technology" and to transform industrial structure to the tertiary industry to achieve the targets of carbon neutrality and emissions peaking.

Are globalization, urbanization, and energy consumption cause carbon emissions in SAARC region? New evidence from CS-ARDL approach

This study examines the impact of energy consumption, urbanization, and globalization on environmental degradation proxied by carbon emissions (CO₂) in the South Asian Association for Regional Cooperation (SAARC) countries, namely Sri Lanka, Pakistan, Maldives, Nepal, Bhutan, Bangladesh, and India using data over the period 1990-2018. The cross-sectional autoregressive distributed lag (CS-ARDL), pooled mean group (PMG), and Dumitrescu and Hurlin (D-H) Granger causality techniques are employed for the empirical analysis. First and second-generation panel unit root tests are used to determine the stationary level of all data series which reveals mixed order of integration. The empirical findings show that urbanization, gross domestic product (GDP) per capita income, energy consumption, industrial growth, globalization, and financial development cause CO₂ emissions, while the other variables, namely arable land and innovation, put negative effects on CO₂ emissions. Moreover, the D-H heterogeneous test results exhibit that bi-directional relationship exists between CO₂ and arable land, urbanization, industrial growth, and financial development, while a unidirectional causality exists between CO₂ emissions and GDP per head income. These findings suggest that planned urbanization, investment in renewable energy sources, and effective strategies regarding the economic and financial integration with the global economies are required for a clean and green environment.

Empirical analysis of the feasible solution to mitigate the CO2 emission: evidence from Next-11 countries

From the empirical findings, economic growth, energy consumption, fossil fuel use, and infrastructure all have a positive impact on CO₂ emissions. Forest rent and industrialization show a mix of results to explain CO₂ emissions in N-11 countries. Forest and agriculture have negative coefficients in most of the estimations which indicate the reduction of CO₂ emissions in 11 countries. Through the evidence of variance decomposition (VD) analysis, this study found an inverted U-shaped EKC hypothesis in the long run. Moreover, through the econometric analysis, it is clear that forest area is important to reduce CO₂ emissions in N-11 countries, where forest investment and planning would be effective for carbon reduction. Agricultural activities and production with green investment play an important role in mitigating CO₂ emissions in N-11 countries.

Analyzing dynamic impacts of deagriculturalization on CO2 emissions in selected Asian economies: a tale of two shocks

The study investigates the symmetric and asymmetric impact of agriculturalization on CO₂ emissions in a sample of selected Asian economies for time period 1985 to 2019. For empirical analysis, the study adopted panel linear and nonlinear autoregressive distributed lag (ARDL) approaches. The long-run findings of panel ARDL reveal that agriculturalization contributes to environmental quality by mitigating CO₂ emissions. The panel nonlinear results clearly indicate that the effects of agriculturalization on CO₂ emissions are asymmetric. The findings demonstrate that agriculturalization improves environmental quality and de-agriculturalization mitigates environmental quality. Our empirical results are also robust to alternative model specifications. Based on these findings, the study recommends that the relevant authorities should formulate reforms in the agriculture sector that controls and reduces carbon emissions in Asian economies.

Spatiotemporal variations and structural characteristics of carbon emissions at the county scale: a case study of Wu'an City

In China, the county is not only an important component of industrial areas and a large contributor of carbon emissions, but also a key administrative unit for the implementation of carbon peak and carbon neutrality goals and policies. The spatiotemporal variations and structural characteristics of carbon emissions at the county scale are of great significance to China's dual goals of regional carbon policy implementation and low carbon spatial planning. Thus, it is important and insightful to conduct an in-depth and detailed examination of these characteristics while focusing on a typical iron and steel industry county-level city in North China. This study systematically calculated the carbon emissions of the county-level city of Wu'an from 2008 to 2017, and explored their structural characteristics and spatiotemporal variations. The results showed that (1) under the influence of macroeconomic and national policies, the carbon emissions of county-level cities dominated by the iron and steel industry show obvious phased characteristics; (2) there is a significant negative correlation between industry carbon emission concentrations and industrial carbon emissions; (3) within the steel industry system, sintering, iron smelting, steelmaking, and metal product processing are the main sources of carbon emissions, and the coal-based production process of the iron and steel industry needs a fundamental reformation; and (4) the carbon emission of Wu'an City shows obvious spatial differentiation characteristics. The geographic distribution of carbon emissions in Wu'an City is very unbalanced and tended to cluster together in urban areas, industrial and mining areas, and major towns. Taking 2014 as the turning point, the spatial pattern of carbon emissions in Wu'an City presents different variation characteristics.

Assessing the long- and short-run asymmetrical effects of climate change on rice production: empirical evidence from India

In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist's attention across the globe due to its long-term harmful effects on agricultural production, food supply, water supply, and livelihoods of rural households. The present study aims to explore the asymmetrical dynamic relationship between climate change and rice production with other explanatory variables. Based on the time series data of India, covering the period 1991-2018, the current study applied the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach. The results of the NARDL reveal that mean temperature negatively affects rice production in the long run while positively affecting it in the short run. Furthermore, positive shocks in rainfall and carbon emission have negative and significant impacts on rice production in the long and short run. In comparison, negative rainfall shocks significantly affect rice production in the long and short run. Wald test confirms the asymmetrical relationship between climate change and rice production. The Granger causality test shows feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production. While no causal relationship between increasing temperature and decreasing carbon emission. Based on the empirical investigations, some critical policy implications emerged. Toward sustainable rice production in India, there is a need to improve irrigation infrastructure through increasing public investment and to develop climate-resilient seeds varieties to cope with climate change. Along with, at the district level government should provide proper training to farmers regarding the usage of pesticides, the proper amount of fertilizers, and irrigation systems.

A change is gonna come: will traditional meat production end?

Recently, the world has faced environmental disasters mainly due to global warming. One of the main reasons for global temperature imbalances is the greenhouse gases (GHG) that soar the atmosphere's heat. The major aim of the current study is to explore whether the livestock population is the main contributor to GHG emission through econometric estimations. In this study, we examine the impact of livestock population with other explanatory variables-GDP per capita, Economic Complexity Index (ECI), ecological balance, and total patent applications-over GHG emission of 25 countries responsible for 76% of GHG emission between 1990 and 2017. To investigate the relationship of variables, Fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are used, as well as panel causality. Also, the relationship is examined by using the responsiveness scores (RS) approach. The empirical results reveal that all variables have a causal relationship with GHG emission. GDP per capita, ECI, and livestock population enhance the GHG emission whereas square of GDP per capita and ecological balance decline the environmental degradation. The paper demonstrates that the environmental Kuznets curve is valid and supports the literature. Lastly, the RS estimation results reveal that the livestock population is causing higher GHG emissions for all countries in the analysis, contrary to other independent variables. Governments should promote carbon-neutral meat production facilities instead of traditional beef farms to live in a more sustainable world. In the future, countries that invest in research and development (R&D) for less emission meat production will have a comparative advantage in the sustainable international meat market.

Impact of globalization, institutional quality, economic growth, electricity and renewable energy consumption on Carbon Dioxide Emission in OECD countries

This research for the first time examines the influence of the financial development, stock market, globalization, institutional quality, economic growth, electricity, and renewable energy consumption on carbon dioxide emission from 1985 to 2018 in thirty-six (OECD) countries. Cointegrations exist in the used variables based on the examined findings of the Kao, Westerlund, and Pedroni cointegration. Findings of the pooled mean group (PMG) indicate that renewable energy consumption, globalization, and institutional quality assist to reduce the carbon dioxide emission that improve the environment while financial development, stock market, electricity consumption, and economic growth cause to increase the carbon dioxide emission in OECD countries both in the long and in the short run. To reduce carbon dioxide emission, important policy implications are suggested for OECD countries.

The anthropogenic consequences of energy consumption in the presence of uncertainties and complexities: evidence from World Bank income clusters

In environmental management, many studies have examined the energy consumption-emission nexus in detail. However, for the first time in the literature, this study considers how the Economic Complexity Index (ECI) and economic policy uncertainty (EPU) moderate the contribution of energy consumption to emissions for the four World Bank Income clusters. The system generalised methods of moments are applied to data for 109 countries from 1996 to 2016. Based on the main model (grouped clusters) estimations, the result revealed the existence of the environmental Kuznets curve (EKC) hypothesis. Also, an increase in air transport and consumption of energy releases more carbon emissions to the climate. Interestingly, ECI decreases carbon emission significantly while EPU does not have a significant impact. Moreover, the study revealed that ECI moderated the impact of other variables on emission, but EPU is not a significant moderator. Furthermore, a comparative analysis among the four incomes suggests that the EKC hypothesis holds only in the high-income clusters; ECI is a significant predictor of carbon emission in the four clusters, but it only decreases the emission in high-income clusters. This corroborates the debate on climate change and the productive capacity of high-income countries. Given the foregoing, several policy measures were recommended.

Combined role of industrialization and urbanization in determining carbon neutrality: empirical story of Pakistan

A rapid process of industrialization, on the one hand, transformed the economies from agrarian to industrial societies to improve the living standards and welfare of people. On the other hand, the urbanized and industrialized economies have posed challenging threats to environmental sustainability. The query at hand is whether the growing environmental emissions are driven by industrialization and urbanization or not. This research aims to empirically examine the combined role of industrialization and urbanization in achieving carbon neutrality in Pakistan by considering foreign direct investment and economic growth as control variables in the model. The core empirical results are the following: firstly, industrialization and economic growth exhibit negative but statistically insignificant impacts on CO₂ emissions, imparting a neutral role in determining the environmental degradation in Pakistan. Secondly, urbanization and foreign direct investment disclose positive and statistically significant (at 1% level of significance) impacts on CO₂ emissions, manifesting an environmental degradation driving impact in the country. Thirdly, given the slope coefficients of urbanization and foreign direct investment (0.058 and 0.035), urbanization proved to be a stronger driver than foreign direct investment. Finally, foreign direct investment is revealed to make the Pakistani economy a "Pollution Haven" for the foreign enterprises in the country. Based on empirical results, none of the variables predicted the support for carbon neutrality in Pakistan.

The energy consumption-environmental quality nexus in BRICS countries: the role of outward foreign direct investment

This paper examines the role of outward foreign direct investment on energy consumption and environmental quality in BRICS from 1990 to 2019. Most of the previous research considered foreign direct investment mainly focused on the environmental impact on the host country effect and ignored the home country effect. Therefore, the current study examines the home country effect of environmental pollution. We use various methodologies like cross-sectional dependence and the Pesaran-Yamagata slope homogeneity for the diagnostic test. After confirming the diagnosis test, we employ second-generation panel unit root tests, which confirms that all elements are stationary at first difference. The pooled mean group (PMG), Westerlund cointegration, two-step generalised method of moments (GMM), panel fully modified ordinary least square (FMOLS), and dynamic ordinary least square (DOLS) model have been used to determine the short-term and long-term association among the variables. The cointegration and PMG results confirm that the short-run and long-run association exists among the considered variables. The results reveal that developing countries produced environmental pollution at the early stage of development and checked in the long run. The study used the STIRPAT model to build an extended carbon dioxide emissions model by incorporating outward FDI, GDP per capita, and technology to achieve our objectives. The empirical results hold up the environmental Kuznets curve hypothesis, implying that outward FDI and energy consumption help expand greener technology to host countries' environmental improvement in the long run and confirm that an inverted U-shaped linkage exists. Hence, the study suggests that developing countries should pay more attention to sustainable development and technological development that encourages more eco-friendly and environment-friendly technology.

Dual performance of environmental regulation on economic and environmental development: evidence from China

Based on the comparative perspective of environmental regulation performance, this paper uses the threshold effect model to analyze the nonlinear characteristics of the impact of environmental regulation on economic development and environmental pollution and explore the dual performance of environmental regulation on economic and environmental development. The results are fourfold: Firstly, the intensity of fiscal expenditure on energy conservation and environmental protection has a restraining effect on environmental pollution, but it has a crowding-out effect on economic growth. Therefore, it is impossible to achieve a win-win situation between ecological protection and economic development by increasing the intensity of financial expenditure on energy conservation and environmental protection. Secondly, giving more financial rights to local governments in eastern China may help to reverse the non-win-win situation of the economy and the environment. Thirdly, increasing the environmental protection awareness of local governments will help to achieve a win-win situation. It is more effective to achieve a win-win situation of ecology and economy using constraint regulation than incentive regulation. Finally, the economic development level of the last period has different threshold effects on the current environmental pollution in the eastern and western China. Thus, the impact of environmental regulation lags. We conclude that we should give full play to the role of the environmental regulation, stimulate the endogenous power of environmental system, accurately implement the key differentiation strategy, and promote the win-win situation of ecological protection and economic development.

Role of trade openness, export diversification, and renewable electricity output in realizing carbon neutrality dream of China

Since climate change mitigation is the central debate of modern literature, the realization of carbon neutrality in response to diversified macroeconomic variables is the most crucial concern of international economies. However, the critical role of trade and renewable electricity output in export diversification-environmental nexus is missing. Therefore, this study investigates the combined influence of trade openness, exports diversification, and renewable electricity output on carbon dioxide emissions (CO₂) in China from 1989 through 2019. Applying novel time series econometric techniques robust to structural breaks, following new outcomes are obtained. Firstly, long-run equilibrium cointegration existed among the under-analysis variables. Secondly, export diversification and renewable electricity output are predicted to decelerate CO₂, supporting carbon neutrality in the long run. Thirdly, trade openness and gross domestic product accelerated the CO₂, delaying carbon neutrality accomplishment. Most importantly, significant structural break dummy interacting with trade openness implicated that during the post-2001 era, China's trade openness extensively deteriorated the environmental quality in the face of trade liberalization obtained after joining the World Trade Organization (WTO). Based on empirical results, export diversification and renewable electricity production policies should be mutually non-exclusive and closely coordinated. Further, to counter the carbon emission acceleration impact of trade openness, increasing the share of green tradable products is suggested. Finally, bilateral trade restructuring is recommended to realize the long-term dream of economic sustainability and carbon neutrality.

Towards long-term sustainable environment: does agriculture and renewable energy consumption matter?

This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO₂ emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO₂ emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO₂ emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the "Conclusions" section.

Impact of remittances on carbon emission: fresh evidence from a panel of five remittance-receiving countries

The present study aims to investigate the impact of remittances on CO2 emission by incorporating financial development, economic growth, industry value added, and agriculture value added in it. This research covers the 37 years of panel data of five countries, i.e., India, the Philippines, Egypt, Pakistan, and Bangladesh, from 1980 to 2016. The data were collected from the World Bank database. The panel cointegration technique and panel autoregressive distributive lag (ARDL) model have been employed to check long-run relationships. The estimated result of the panel cointegration approach confirms the existence of a long-run relationship among remittances received, financial development, economic growth, industry value added, agriculture value added, and CO2 emission. The findings of the study indicate that an increase in received remittances, economic growth, and value-added agriculture help in mitigating carbon emissions from the selected panel countries. However, improving the financial system and adding more industries result in the high emission of CO2. On the contrary, the short-run ARDL estimation shows that CO2 emission increases at a significant level with the increase of remittances inflow and agriculture value added, while in the case of financial development, economic growth, and industry value added, this increasing effect in CO2 is at an insignificant level. Moreover, dynamic ordinary least square (DOLS) is used in this study for robust analysis and found the same long run result like ARDL. Additionally, this study also provides some important recommendations to economic policymakers to reduce CO2 emission in the selected remittance-receiving countries.

What drives the decoupling between economic growth and energy-related CO2 emissions in China's agricultural sector?

Many studies have shown that the rapid agricultural mechanization development in China led to substantial energy consumption and CO₂ emission growth. To better explain the mechanism behind the decoupling between economic growth and CO₂ emissions, this paper extends the logarithmic mean Divisia index (LMDI) and production-theoretical decomposition (PDA) considering agricultural decoupling from both structural and technical perspectives. The results reveal that (1) China's agricultural decoupling performance was not ideal. Investment and investment efficiency were the most important factors influencing the decoupling status. The main decoupling obstacle was a higher investment in productivity rather than in energy conservation and carbon reduction. (2) The decoupling status and investment orientation of decoupling efforts among regions were different. Strong negative decoupling statuses frequently occurred in the eastern region, whose main disadvantage was high potential energy intensity. The decoupling status of the central region exhibited expansive features. The decoupling key is to invest more in energy-saving technology rather than in production. The western region changed from weak decoupling to expansive negative decoupling. Both output technology and energy-related factors should be the main investment targets. (3) Weak decoupling and expansive negative decoupling were the most common statuses among provinces. The influence mechanism of drivers exhibited a high spatial heterogeneity at the provincial level. Therefore, the study offered a convincing basis for local governments to formulate low-carbon agricultural development policies by identifying the main decoupling drivers.

Research on the Relationship between Prices of Agricultural Production Factors, Food Consumption Prices, and Agricultural Carbon Emissions: Evidence from China’s Provincial Panel Data

China is a large agricultural country with a high level of agricultural carbon emissions. Whether market prices can be used in agricultural production as a means of agricultural carbon emissions reduction is of great significance to improve the allocation of agricultural production factors and expand large-scale production. This paper applies an autoregressive distributed lag–pooled mean group(ARDL–PMG) model to evaluate the relationship between agricultural production factor prices, food consumption prices, and agricultural carbon emissions, using Chinese provincial panel data from 1994 to 2018. The results show that agricultural carbon emissions and agricultural production factor prices show environmental Kuznets curve (EKC) characteristics; agricultural carbon emissions and food prices show a U-shaped curve; and agricultural production factors are positively correlated with food price in both directions in the long-term. The results of Granger causality tests show that price is the cause of agricultural carbon emissions; the price of agricultural production factors and the price of food consumption are mutually causal. Such results have implications for price, agriculture, and environmental policies. The analysis implies that the market price can be applied to agricultural carbon reduction, which will help policymakers to implement effective price policies in order to reduce agricultural carbon emissions. One implication is that promoting the marketization of agricultural production factors and reducing price distortions will be conducive to carbon emissions reduction in agriculture, which in turn will increase food consumption prices. Therefore, subsidies are needed at the consumption end, which will eventually achieve further carbon emissions reduction at the production and consumption ends.

Does economic prosperity lead to environmental sustainability in developing economies? Environmental Kuznets curve theory

Since developing countries experience economic and environmental sustainability challenges, it is desirable digging into the linkages between economic and environmental parameters. The purpose of this work is to evaluate the existence of the environmental Kuznets curve (EKC) theory (i.e., the inverse U-shape connection between real GDP per capita and per capita carbon dioxide emissions) in the sample of 11 developing countries. By using balanced annual panel data in the period between 1992 and 2014 and two alternative estimation techniques, we explored the potential inverted U-shaped linkage between carbon dioxide emissions and real GDP per capita in the sample of interest. For analysis purposes, Pedroni and Westerlund co-integration techniques are employed. Then, fully modified ordinary least squares, pooled mean group methods are applied for long-run parameter estimations. And, the Dumitrescu-Hurlin causality approach is employed for causal directions. Firstly, this work's findings provide the supportive evidence to the inverse U-shaped linkage in the long-run, indicating that an increase in real GDP per capita and electricity consumption tends to mitigate long-run carbon dioxide emissions in the developing countries, for the whole sample. Secondly, the country-specific findings suggested the presence of EKC theory for Brazil, China, India, Malaysia, the Russian Federation, Thailand, and Turkey. It implicated that these countries are on the path of attaining environmental sustainability in the long-run. However, Mexico, Philippines, Indonesia, and South Africa failed to lend credence to the EKC theory. It manifested that these countries need to design strategies directed to reduce carbon dioxide emissions from economic activity and electricity generation through efficiency improvement or promotion of renewables. Finally, bidirectional causal links are observed among all the variables of interest. The findings suggest that country-specific targeted action plans should be implemented to ensure the environmental sustainability in the developing world.

Does agricultural value-added induce environmental degradation? Evidence from Azerbaijan

This study empirically analyzes the long-term relationship between agricultural production and carbon dioxide (CO₂) emissions in Azerbaijan using annual data covering the period of 1992-2014. Additionally, real income and energy consumption variables were included in the model in testing the existence of the environmental Kuznets curve (EKC) hypothesis. Autoregressive distributed lag (ARDL) method is undertaken to reveal the existence of the long-term relationship between the CO₂ and its determinants. The ARDL mechanism shows that gross domestic product (GDP) and energy consumption have a positive and statistically significant effect on carbon dioxide emissions. However, agricultural production and the square of GDP have a negative impact on air pollution. Furthermore, when the coefficients of real GDP and squared GDP included in the model were examined to analyze the inverted-U-shaped relationship between economic growth and environmental pollution, the EKC hypothesis was confirmed to be valid. According to Toda-Yamamoto causality test results, there is a bidirectional relationship between GDP, the square of GDP, and carbon emissions. From energy consumption and agricultural value-added to CO₂ emissions, a unidirectional Granger causality relationship was found. Ultimately, the findings suggest that policies and reforms that increase or support agricultural production will help lower the country's CO₂ emissions level.

The objects, agents, and tools of Chinese co-governance on air pollution: a review

The social and economic development in China has not only made a series of great achievements but also suffered from increasingly serious air pollution. It is of great significance to explore the co-governance mechanism of air pollution in order to promote high-quality development and the construction of "beautiful China." Based on an analysis using the concept of co-governance, this paper reviews the research from four aspects: the multi-object relationships, multi-agent framework, and the co-governance technical tools and policy tools. The results show that the current research has many deficiencies: a lack of research on the size, direction, and driving factors of the correlation of objects; the construction of the multi-agent framework focused only on concepts and lacking the design of core mechanisms; evaluating only the effect of tools but ignoring the optimal combination of governance tools, and paying attention only to the traditional pollutants and disregarding the latest air pollution. Accordingly, this paper finds that the research should be expanded from four aspects, which include taking into account the co-governance of new air pollution, clarifying the relationship between the various types of air pollutants and the driving factors, building a multi-disciplinary research framework for co-governance, and optimizing the combination of governance policies and technical tools in order to realize high-quality development of China.

Heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions across regional development levels

This study examined the long-run and short-run heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions index across the regional development levels of 31 Chinese provinces. By employing the augmented mean group method and Dumitrescu-Hurlin causality, the following results are drawn: Firstly, a bidirectional positive linkage was existent between the economic development and urban concentration in both the long-run and short-run across regional development levels. Secondly, a unidirectional positive linkage emerged from non-renewable energy use intensity to environmental emissions index, with the most influential effect in EER China (highest development level). Thirdly, bidirectional mixed linkages prevailed between economic development and non-renewable energy use intensity. Economic development mitigated the non-renewable energy use intensity (inverted U-shaped curve) in the national data set and EER China (highest development level); nevertheless, the linear linkage was observed in IER China (medium development level) and WER China (lowest development level). Fourthly, unidirectional mixed linkages were found from urban concentration to non-renewable energy use intensity and environmental emissions index. Urban concentration demonstrated a U-shaped linkage with non-renewable energy use intensity and environmental emissions index in the national data set and EER China. But it unveiled a linear linkage with both variables in IER China and WER China. Fifthly, economic development showed an environmental Kuznets curve with environmental emissions index in the national data set and EER China. Conversely, it showed a linear linkage with the environmental emissions index in IER China and WER China. In turn, the environmental emissions index linearly hampered the economic development in the national data set as well as regional samples. Finally, the long-run and short-run effects showed homogeneity of the linkages' nature; yet, the degree of effects in the long-run surpassed those in the short-run for all development levels.

Dynamic relationship between technological innovations, financial development, renewable energy, and ecological footprint: fresh insights based on the STIRPAT model for Asia Pacific Economic Cooperation countries

This article seeks to analyze the impact of technological innovations, financial development, renewable energy consumption, economic growth, and population on the ecological footprint in Asia Pacific Economic Cooperation (APEC) countries by utilizing the balanced longitudinal data set during the period from 1990 to 2017. This study creates a new technological innovation index through principle component analysis including three important indicators that represent the technology and employs a consistent environmental framework identified as Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. The second generation panel estimation technique is employed to calculate robust and reliable outcomes. After confirming the cross-sectional dependency among series, panel unit root tests confirm that all variables are stationary at their first integrated order. Furthermore, Westerlund cointegration test confirms the presence of long-run association among variables. The outcomes explore that financial development and renewable energy utilization significantly accelerate the environmental quality by 0.0927% and 0.4274%, respectively. While, the increase in technological innovation activities, economic growth, and population size has a detrimental effect on environmental quality in the long run by 0.099%, 0.517%, and 0.458%, respectively. Moreover, the results of panel Dumitrescu and Hurlin (D-H) non-causality test discovered the bidirectional causality relationship between financial development, technological innovations, renewable energy consumption, economic growth, and population size with the ecological footprint. These empirical findings provide some vital policy implications for central authority and policymakers to overcome the detrimental impact on environmental quality in the APEC region.