Urbanization, economic growth, and carbon dioxide emissions in China: A panel cointegration and causality analysis

It is globally acceptable that carbon dioxide (CO2) emissions are one of the greenhouse gases are considered the main factor influencing global warming and environmental degradation. The present study focuses on China, the world's largest carbon emitter. The study aims to capture the time-frequency dependency of economic growth and CO2 emissions in China for the time period 1950-2016 using a wavelet coherence approach, which allows us to investigate both the long-run and short-run causal links of the estimated variables. In order to capture the long-run and causal linkage between economic growth and CO2 emissions, the study employs Maki cointegration, wavelet coherence, Toda-Yamamoto causality, Fourier Toda-Yamamoto causality, and nonparametric Granger causality tests. The findings of this study reveal that (i) there is a significant vulnerability between economic growth and CO2 emissions throughout the 2000s both the short-term and medium-term; (ii) there is long-run cointegration linkage between economic growth and CO2 emissions in China; (iii) economic growth in China has an important power for predicting CO2 emissions over the selected study period, especially in the short-term and medium-term; and (iv) it was observed that there is positive correlation between economic growth during the 1980s and 1990s in the short-term only. The outcome of the Toda-Yamamoto causality, Fourier Toda-Yamamoto causality, and nonparametric Granger causality tests underlines that economic growth is a robust policy variable for predicting CO2 emissions in China.

Economic development has largely contributed to the increment of CO2 emission. This study uses spatial econometric models to investigate the relationship between economic growth and carbon emission in China with data of 30 provinces of China during the period of 2000 to 2012. Results show that the relationship between carbon emission and economic growth in China during the recent decade has the development tendency toward an inverse U-shaped curve, approximately confirming the carbon emission’s Kuznets curve hypothesis in China. There exists a significant spatial correlation between carbon emission and economic growth, implying that carbon emission in a province may be influenced by economic growth in adjacent provinces. When economic growth reaches 279.91 million Yuan/km2 GDP (at a comparable price in 2000), the contradiction between economic growth and carbon emission begins to be gradually alleviated. These findings provide new insights and valuable information for reducing carbon emissions in China.

Based on the use of the coupling coordination model to calculate the coupling coordination degree of carbon emission and pollutant control, the national, regional, and provincial spatiotemporal characteristics of the synergistic effect of pollution control and carbon emissions reduction in China were further analyzed, facilitating the crucial to identification of key areas. The fixed effects regression models and provincial panel data from 2006 to 2020 were used to explore factors contributing to better synergizing the reduction of pollution and carbon emissions in China. On this basis, the adjustment variable of R&D investment intensity was introduced, and the regulation effect model was constructed to further explore the influence mechanism of the synergistic effect of pollution reduction and carbon reduction. The results showed that： synergy exists between carbon emission reduction and the air pollution control system, the evolution of the synergistic effect of pollution reduction and carbon reduction in China presented an inverted "U"-shaped trend from 2006 to 2020, and there was spatial aggregation and a spatial spillover effect in pollution reduction and carbon reduction. The synergistic governance of carbon emission and pollutant control was still at a relatively low level. The carbon emission and air pollutant emission systems were still in an unstable and uncoordinated state. The results showed that： The degree of coordination of eastern China, central China, and western China decreased in turn. At the national level, energy consumption structure, per capita GDP, and the proportion of green investment were the main factors affecting the synergistic effect of pollution reduction and carbon. The heterogeneity of the influencing factors existed in the central, eastern, and western regions on industrial structure, energy consumption structure, energy utilization efficiency, per capita GDP, urbanization rate, the proportion of green investment, and transportation structure. The intensity of R&D played a significant moderating effect in the whole country, eastern, and central regions. However, no significant moderating effect was identified in the western region. In the eastern region, the urbanization rate, the proportion of green investment, and the transportation structure could not have a significant effect on the synergistic effect of pollution reduction and carbon reduction alone, and it must be coordinated with the intensity of R&D.

How does fossil energy abundance affect China's economic growth and CO2 emissions?

On the nexus of financial development, economic growth, and energy consumption in China: New perspective from a GMM panel VAR approach

This paper constructs a decoupling model for four major economic regions of China, based on the Tapio decoupling index method and VAR model for carbon emissions to compare and measure the impact of decoupling between carbon emissions and economic growth in China during 1997 to 2019. The results show that the degree of decoupling between economic growth and carbon emissions varies among different economic regions, and the decoupling status is better in all regions at the beginning of the 21st century. In general, the decoupling status in the eastern and western regions is more ideal than that in the central and northeastern regions. The impulse response and variance decomposition results show that renewable energy consumption could always reduce the growth of carbon emission intensity, and its effects are most significant in the western region. The above findings help to reveal the link between economic growth, renewable energy consumption and carbon emissions in China in recent years, and how to ensure a stable economic growth in China while increasing the share of clean energy consumption in each region to achieve carbon neutrality.

Study of the nonlinear relations between economic growth and carbon dioxide emissions in the Eastern, Central and Western regions of China

Geographical analysis of CO2 emissions in China's manufacturing industry: A geographically weighted regression model

This article takes the coordinated development of industry, academia and research as the entry point and systematically analyzes its impact on China's economic growth. By sorting out the relationship between industry-university-research collaboration and economic growth, a relevant theoretical analysis framework was constructed. Based on the panel data of 30 provinces in China from 2009 to 2022, this article empirically examines and analyzes the specific role and influence path of industry-university-research collaboration on economic growth by using the entropy weight method and the coupled coordination model. The results of the empirical analysis show that the coordinated development of industry, academia and research can effectively promote China's economic growth, and its influence is significantly regulated by the development level of the technology market and the government's investment level in science and technology. He heterogeneity analysis results of the eastern, central and western regions show that the synergy among industry, academia and research has the most obvious promoting effect on economic growth in the central region, followed by the eastern region, while the effect in the western region is not significant. The differences among the three regions are obvious and there is an urgent need for precise policy support. Based on this, this article puts forward relevant policy suggestions for promoting the coordinated development of industry, academia and research, including strengthening government policy support, improving the construction of the technology market, and implementing the regional differentiation strategy, etc. This study expands the analytical perspective on the relationship between industry-university-research collaboration and economic growth, providing new empirical evidence and policy implications for promoting high-quality economic development in China.

This article takes the coordinated development of industry, academia and research as the entry point and systematically analyzes its impact on China's economic growth. By sorting out the relationship between industry-university-research collaboration and economic growth, a relevant theoretical analysis framework was constructed. Based on the panel data of 30 provinces in China from 2009 to 2022, this article empirically examines and analyzes the specific role and influence path of industry-university-research collaboration on economic growth by using the entropy weight method and the coupled coordination model. The results of the empirical analysis show that the coordinated development of industry, academia and research can effectively promote China's economic growth, and its influence is significantly regulated by the development level of the technology market and the government's investment level in science and technology. He heterogeneity analysis results of the eastern, central and western regions show that the synergy among industry, academia and research has the most obvious promoting effect on economic growth in the central region, followed by the eastern region, while the effect in the western region is not significant. The differences among the three regions are obvious and there is an urgent need for precise policy support. Based on this, this article puts forward relevant policy suggestions for promoting the coordinated development of industry, academia and research, including strengthening government policy support, improving the construction of the technology market, and implementing the regional differentiation strategy, etc. This study expands the analytical perspective on the relationship between industry-university-research collaboration and economic growth, providing new empirical evidence and policy implications for promoting high-quality economic development in China.

The present study empirically investigates the impact of hydropower energy consumption on economic growth and CO2 emissions in China, spanning the period 1965-2016. Using the ARDL bounds testing approach to cointegration, this study confirms the existence of a long-run relationship among the variables. Moreover, hydropower energy consumption has a positive impact on economic growth, while CO2 emissions have a long-run negative impact on economic growth. However, economic growth and CO2 emissions have a positive impact on hydropower energy consumption. Further, the study failed to provide a support of the environmental Kuznets curve (EKC) hypothesis for China. The Granger causality test reveals that there is a unidirectional causality running from hydropower energy consumption to economic growth. Furthermore, there is a bidirectional causality among the hydropower energy consumption, economic growth, and CO2 emissions in the long run. Given these findings, we argue that hydropower energy consumption is considered as the driving force to enhance the economic growth in China.

An analysis of the driving forces of energy-related carbon dioxide emissions in China’s industrial sector

Most authors apply the Granger causality-VECM (vector error correction model), and Toda–Yamamoto procedures to investigate the relationships among fossil fuel consumption, emissions, and economic growth, though they ignore the group joint effects and nonlinear behaviour among the variables. In order to circumvent the limitations and bridge the gap in the literature, this paper combines cointegration and linear and nonlinear Granger causality in multivariate settings to investigate the long-run equilibrium, short-run impact, and dynamic causality relationships among economic growth, emissions, and fossil fuel consumption in China from 1965–2016. Using the combination of the newly developed econometric techniques, we obtain many novel empirical findings that are useful for policy makers. For example, cointegration and causality analysis imply that increasing emissions not only leads to immediate economic growth, but also future economic growth, both linearly and nonlinearly. In addition, the findings from cointegration and causality analysis in multivariate settings do not support the argument that reducing emissions and/or fossil fuel consumption does not lead to a slowdown in economic growth in China. The novel empirical findings are useful for policy makers in relation to fossil fuel consumption, emissions, and economic growth. Using the novel findings, governments can make better decisions regarding energy conservation and emission reductions policies without undermining the pace of economic growth in the long run.

Under the current climate change and economic fluctuations, studying the relationship between economic growth, energy consumption and carbon emissions has become a vital issue for the high-quality economic development of various countries. This paper selects the provincial data from 2004 to 2019, and constructs a dynamic simultaneous equation system. Based on the analysis of the impact of economic growth and energy consumption on carbon emissions, the system GMM estimation is used to empirically test the dynamic relationship between the three and analyze it. The heterogeneity of the relationship at the regional level was analyzed, and then a fixed-effects model was used to test the robustness. The results show that: (1) Under the full sample, energy consumption drives the increase of carbon emissions, and economic growth and industrial upgrading are conducive to realizing carbon emission reduction goals. (2) There is a two-way causal relationship between energy consumption and carbon emissions. (3) There is a two-way relationship between energy consumption, economic growth, and carbon emission in the middle and eastern regions. The economic growth in eastern China drives the increase in carbon emissions. In the central region, carbon emission has a certain restraint effect on economic growth. The model has a certain stability, and provides a useful reference for the coordinated development of China's economic growth, energy consumption, and carbon emissions.

Effects of rural–urban development transformation on energy consumption and CO2 emissions: A regional analysis in China