Environmental convergence and environmental Kuznets curve: A unified empirical framework

An empirical investigation of the relationships between nuclear energy, economic growth, trade openness, fossil fuels, and carbon emissions in France: fresh evidence using asymmetric cointegration

The intention behind the current analysis is to join the debate over the main factors to consider in the global fight against climate change. Thereby, the Non-linear Autoregressive Distributed Lag (NARDL) approach is applied to assess the impacts of nuclear energy, fossil fuels, income, and trade on carbon emissions in France from 1980 to 2020. In addition, the relevance of the Environmental Kuznets Curve (EKC) presumption is tested. The main results stipulate that nuclear energy lessens CO₂ emissions in France. However, fossil fuels and trade openness enhance these emissions. On the other hand, the current analysis confirms the presence of an inverted U-shaped curve relating economic growth to carbon emissions. Therefore, the EKC hypothesis is supported in our case. Indeed, by calculating the turning point, it is possible to extract the turning year corresponding to 2008. Furthermore, an asymmetric causality test is performed in order to identify the possible non-linear causal links between the potential drivers of carbon emissions. First, the causal linkage between CO₂ emissions and GDP is bidirectional. Furthermore, a unidirectional causal link between CO₂ emissions and non-renewable energies and a dual directional causal link between pollutant emissions and trade are identified. These empirical results are intended to guide the French government in the implementation of relevant energy and trade-related strategies in order to attain the ambitious targets of carbon emissions reduction. In fact, France should reduce imports of fossil fuels to curtail the positive effect of trade on carbon emissions. In addition, it is recommended to substitute fossil energies with renewable energies gradually by using adequate instruments and boosting research and innovation to mitigate the adverse influences of non-renewable energies on environmental quality. Finally, our findings confirm the positive role played by nuclear energy in the fight against climate change.

Environmental quality and its nexus with informal economy, corruption control, energy use, and socioeconomic aspects: the perspective of emerging economies

This paper explores the impacts of informal economic activities and institutional capacity, particularly, corruption control on the environmental quality degradation of emerging economies under the prevailing socio-economic conditions and energy use patterns of the countries. The study utilizes key environmental degradation indicators: Carbon dioxide (CO₂) emissions, ecological footprints (EFs), and Nitrous Oxide (NO) emissions, and a panel dataset of 15 emerging countries for the period 2002–2019 to undertake an empirical investigation. The pooled mean group (PMG)-ARDL estimator, Fully Modified OLS (FMOLS), Dynamic OLS (DOLS) and Augmented Mean Group (AMG) methods have been applied as empirical investigation techniques. The empirical findings reveal that in the long-run informal economic activities positively affect the environmental quality with fewer recorded emissions of CO₂ and EFs while these activities affect negatively to NO emissions. This study has also found that corruption control improves environmental quality by reducing EFs and NO emissions but works to the opposite by increasing recorded CO₂ emissions. An increase in economic growth and renewable energy consumption improves environmental quality in emerging countries, while consumption of non-renewable energy degrades the environmental quality. The robust empirical findings advocate policy initiatives for intense monitoring of informal activities and implementation of indirect tax policy to regulate informal activities and the pollution they cause. Careful measures of corruption control and initiatives to bring the informal economic activities into a formal framework are suggested to reduce CO₂ and NO emissions. An increase in economic growth with more focus on renewables and phasing out non-renewables can ensure green growth in emerging countries.

Spatial Convergence of Carbon Productivity: Theoretical Analysis and Chinese Experience

Based on the neoclassical framework, we propose the convergence hypothesis of carbon productivity under sustainable growth and prove the different effects of knowledge spillover and technology diffusion on convergence. The convergence hypothesis is tested using China’s provincial spatial dynamic panel data from 1995 to 2019. The results show that China’s provincial carbon productivity has conditional convergence and club convergence characteristics. The convergence speed of dynamic panel regression estimation is greater than that of cross-sectional regression. The convergence rate of dynamic spatial panel regression estimation is faster depending on the spatial spillover difference between the two technologies. In the early stage, the provincial spatial dependence of China’s carbon productivity is mainly knowledge spillover, and the convergence rate is lower than that of the closed economy. Over the past decade, the spatial spillover, dominated by low-carbon technology diffusion, has become the dominant force. The convergence rate is significantly faster than that of a non-spatial-dependent economy. In addition, the mechanism test found that the development of energy efficiency dominates the spatial transfer of technology, so the overall convergence of carbon productivity in China mainly comes from the apparent convergence of energy efficiency in provinces and cities. Our conclusion provides a new reference for the emission reduction actions of countries worldwide because the spatial knowledge spillover carried by capital flows is not conducive to the pursuit of carbon productivity in less developed regions. On the contrary, the dissemination and diffusion of low-carbon technologies can significantly reduce carbon equivalent input in the production process, accelerating the pursuit of developing countries or regions.

Convergence or Divergence? Emission Performance in the Regional Comprehensive Economic Partnership Countries

Emission convergence is a fundamental ground for cooperative CO2 emission mitigation. We investigate the emission convergence in the Regional Comprehensive Economic Partnership (RCEP) countries using a modified dynamic β-convergence model. From 2000 to 2017, the per capita emissions of the RCEP countries and its subgroups show a statistically significant diverging pattern. Nonetheless, upon accounting for multiple inputs and outputs using data envelopment analysis, we find that two out of the three emission performance indicators show statistically significant absolute convergence. The carbon emission efficiency (CEE) of the 15 RCEP countries grew from 0.5719 in 2000 to 0.6725 in 2017 and will converge at a value of 0.8187, while the carbon–population performance (CPP) increases from 0.4534 to 0.5690 and will converge at 0.7831. Furthermore, using a conditional β-convergence model, we find that trade volume has no significant effect on the growth rates of CEE and CPP, but can accelerate their speed of convergence, which indicates that the establishment of the RCEP may facilitate the convergence of its 15 member countries on CEE and CPP. Our findings suggest that emission mitigation agreement in the RCEP countries is feasible. CEE- or CPP-based indicators can be used for emission budget allocation.

Environmental kuznets curve and causal links between environmental degradation and selected socioeconomic indicators in Bangladesh

This study has investigated the Environmental Kuznets Curve (EKC) hypothesis and focuses on the resource stock of the country in relation to the selection of environmental degradation indicators. Acknowledging the critical role of the EKC for policy formulation and development strategies, this study has examined the validity of the EKC hypothesis by exploring the relationship between economic growth, urbanization, energy consumption, trade openness, human capital and ecological footprints for the period 1972-2018 in Bangladesh. The autoregressive distributive lag bounds testing approach is applied for this purpose, taking into account the structural break in the time series. A fully modified OLS estimation has also been applied as the robustness check of the results. Results from the empirical analysis confirm the existence of the EKC in Bangladesh in both the long run and short run. The causal nexus among the variables is examined by applying the Vector Error Correction Granger causality test. The causality test result shows that economic growth and urbanization cause ecological footprints in both the short run and the long run. Based on this result, it can be inferred that economic growth activities in Bangladesh can be continued and extended with minimal ecological cost through structural economic change and proper environmental management.

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.

Spatiotemporal Evolution of Lakes under Rapid Urbanization: A Case Study in Wuhan, China

The impact of urbanization on lakes in the urban context has aroused continuous attention from the public. However, the long-term evolution of lakes in a certain megacity and the heterogeneity of the spatial relationship between related influencing factors and lake changes are rarely discussed. The evolution of 58 lakes in Wuhan, China from 1990 to 2019 was analyzed from three aspects of lake area, lake landscape, and lakefront ecology, respectively. The Multi-Scale Geographic Weighted Regression model (MGWR) was then used to analyze the impact of related influencing factors on lake area change. The investigation found that the total area of 58 lakes decreased by 15.3%. A worsening trend was found regarding lake landscape with the five landscape indexes of lakes dropping; in contrast, lakefront ecology saw a gradual recovery with variations in the remote sensing ecological index (RSEI) in the lakefront area. The MGWR regression results showed that, on the whole, the increase in Gross Domestic Product (GDP), RSEI in the lakefront area, precipitation, and humidity contributed to lake restoration. The growth of population and the proportion of impervious surface (IS) in the lakefront area had different effects on different lakes. Specifically, the increase in GDP and population in all downtown districts and two suburb districts promoted lake restoration (e.g., Wu Lake), while the increase in population in Jiangxia led to lake loss. The growth of RSEI in lakefront area promoted the restoration of most lakes. A higher proportion of IS in lakefront area normally resulted in more lake loss. However, in some cases, the growth of IS was caused by lake conservation, which contributed to lake restoration (e.g., Tangxun Lake). The study reveals the spatiotemporal evolution of multiple lakes in Wuhan and provides a useful reference for the government to formulate differentiated protection policies.