The positive role of trade openness in industrial green total factor productivity-provincial evidence from China

Analysis of the impact factors of industrial structure upgrading on green total factor productivity from the perspective of spatial spillover effects

Green development has already been a vital part of China's high-quality economic progress in the future, and accelerating the restructuring and improvement of the industrial structure plays a crucial roll in promoting a regional green economy. In this article, based on the data of 278 prefecture-level cities in China from 2011 to 2020, the SBM directional distance function and Malmquist-Luenberger (ML) index are used to gauge regional green total factor productivity (GTFP). The spatial Durbin model is also introduced to investigate the spatial spillover mechanism of GTFP and its influencing factors under the optimized and upgraded industrial structure. The study indicates that the optimization of the industrial structure have an important effect in promoting the growth of GTFP. Specifically, industrial structure integration has a greater bearing on the increase in GTFP, while there is a difference in the effectiveness of industrial structural advancement and rationalization of GTFP. Economic growth level inhibits the enhancement of GTFP, and urbanization level and industrial agglomeration have a significant negative impact on the enhancement of GTFP in the spatial dimension. On a different hand, foreign investment degree and government intervention level have a significant positive affect on regional GTFP. In addition, this study fills the research gap of the regional industrial structure upgrading influence on GTFP, which has great theory and practice value for promoting China's high quality growth of green economy.

Reduced Graphene Oxide/Cellulose Sodium Aerogel-Supported Eutectic Phase Change Material Gel Demonstrating Superior Energy Conversion and Storage Capacity toward High-Performance Personal Thermal Management

By virtue of their capacity to absorb and release energy during the phase change process, phase change materials (PCMs) are ideal for personal thermal management (PTM). The combination of reduced graphene oxide/cellulose sodium aerogel (rGCA) and lauric acid/myristic acid binary eutectic phase change gel (LMG) creates a composite phase change material that possesses outstanding photothermal conversion capabilities, electro-thermal conversion capabilities, energy storage capabilities, and shape-stable performance. The results showed that rGCA had a maximum adsorption efficiency of 99.7% with a melting latent heat of 124.6 J g-1. The high absorption rate of rGCA to LMG is a result of the capillary force, pore characteristics, hydrogen bonding, and the π-π interaction. Notably, rGCA and LMG composite material (rGCG) exhibited an excellent photothermal conversion efficiency of 96.5% and electro-thermal conversion of 82.3%. Results indicate that binary eutectic phase change materials are more suitable for temperature regulation than single phase change materials, making them more suitable for PTM. It is anticipated that the innovative thermal comfort solution, which provides thermal shielding, thermal energy storage, self-supporting characteristics, and wearability, will offer new possibilities for the next generation of wearable PTMs.

Influence of local governments on the greening of the manufacturing sector: A perspective on environmental governance objectives

The green development of manufacturing industries is significantly impacted by local governments. In this study, we focus on assessing the environmental governance effectiveness by examining the tasks assigned by the central government to each province under the Comprehensive Work Program for Energy Conservation and Emission Reduction. By utilizing panel data from 30 provinces and cities in China from 2011 to 2020, we employ the super-efficient SBM model to evaluate China's manufacturing industry's green total factor productivity. Through various models, including the double-fixed effect and the mediation effect, we investigate the influence of environmental governance targets on the green total factor productivity of the manufacturing industry. Our findings reveal a U-shaped relationship between the environmental governance target and the green total factor productivity of the manufacturing industry. When the pressure of environmental governance targets is below a certain critical value, the green total factor productivity decreases as the target pressure increases. However, once the target pressure surpasses this critical value, the green total factor productivity experiences a positive correlation with the target pressure. Further analysis demonstrates that this U-shaped relationship is observed in regions with low and medium marketization, while regions with high marketization remain unaffected. Moreover, the impact of environmental governance target pressure on green total factor productivity in manufacturing is facilitated by the promotion of green innovation. Furthermore, the relationship between environmental governance target pressure and green total factor productivity in manufacturing is moderated by local government fiscal expenditures. In regions where fiscal expenditures are higher, the influence of environmental governance target pressure on green total factor productivity in manufacturing is more pronounced.

China's pilot free trade zone and green high-quality development: an empirical study from the perspective of green finance

Achieving the integration of green and economic development has become the key to promoting high-quality economic development in China. In the context of dual-cycle development, a higher level of opening up will be an important prerequisite for achieving this goal. This article uses panel data from 30 provinces in China from 2008 to 2020 as the research sample and takes the establishment of the Pilot Free Trade Zone (PFTZ) as a quasi-natural experiment. By constructing the Green Dual-Cycle High-Quality Development (GDHD) indicator system, taking green finance as the starting point, industrial structure adjustment and technological innovation ability as the perspective of differentiation. This article uses the difference-in-differences method and the intermediary effect model to explore the impact of PFTZ on regional green high-quality development. The study found that establishing PFTZ has significantly promoted regional green high-quality development, and this effect remains valid under multiple robustness tests. Further research has found that, under the advantages of green finance in PFTZ, regional industrial restructuring and the improvement of green innovation capabilities are the main ways to achieve this goal. This study provides a new development path for China's PFTZ to promote high-quality regional development better.

Spatial Association Network Evolution and Variance Decomposition of Economic Sustainability Development Efficiency in China

The economy's sustainable development has become a national strategic deployment in China. Research on the difference between the economic sustainable development efficiency (ESDE) and the spatial network will assist the government with the deployment of sustainable development strategies and the achievement of the "peak carbon dioxide emissions". This paper designs the input-output indicator system of sustainable economic development efficiency and builds an unexpected output super-EBM-Malmquist model to measure the ESDE of 30 provinces in China from 2008-2020. According to the ranking of ESDE, the 30 provinces in China are classified into four groups by applying the quartile method, and the difference in the ESDE in different regions and the temporal variation of different provinces are studied by using the Dagum Gini coefficient and Gaussian Kernel density. Moreover, the relationship between ESDE in different provinces is studied based on the revised gravity model and social network analysis method. The connections between provinces with related relations constitute the ESDE network. Results show that (1) the average ESDE in China shows an upward trend, the eastern region is in a leading position, the central and western regions are trying to catch up with the eastern region, and the development of the northeast region is lagging behind. (2) The level of ESDE in different provinces is clearly arranged from high to low, illuminating a distinct pattern. Moreover, provinces with high levels of development are much higher than provinces with low levels of development, presenting a phenomenon of polarization. (3) The regional ESDE development imbalance is prominent, and the ESDE in the eastern region is closely related, while the connection in the western region is lower. (4) Beijing-Tianjin Urban Agglomeration and the Yangtze River Delta have significant spatial spillover effects in the association network, while the northeast, northwest, southwest and central regions have significant spatial benefit relationships. These findings provide important enlightenment for promoting the sustainable and balanced development of China's economy.

Spatial-temporal evolution and convergence analysis of agricultural green total factor productivity-evidence from the Yangtze River Delta Region of China

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist-Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use.

How does export composition improvement affect carbon dioxide emissions in BRI countries? The mediating role of industrial structure upgrading and the moderating role of intellectual property protection

Climate change, caused by carbon dioxide (CO₂) emissions, has become increasingly severe and is a serious constraint on the sustainable development of the global economy. Economists are aware of the close relationship between export trade and the growth of CO₂ emissions, especially for the Belt and Road Initiative countries that are experiencing economic growth and transformation. Extant literature also agrees that the composition of the export basket is one of the crucial factors influencing CO₂ emissions, but the mechanisms by which changes in the export basket affect carbon emissions from a sustainable production perspective remain unexplored. Based on international trade theory, this study examines how shifts in production patterns affect subsequent CO₂ emissions through the lens of exogenously driven changes in the composition of a country's exports, with the consideration of the mediating role of industrial structure upgrading and the moderating role of intellectual property protection simultaneously. The results reveal that export composition improvement contributes to carbon reduction, and industrial structure upgrading plays a significant mediating role in the export composition improvement for carbon reduction. Intellectual property protection moderates the relationship between export composition improvement and industrial structure upgrading. The mediating effect of export composition improvement affecting carbon emissions reduction through industrial structure upgrading is also moderated by intellectual property protection.

Analysis on the Spatio-Temporal Evolution Characteristics of the Impact of China's Digitalization Process on Green Total Factor Productivity

Green production is an inevitable choice for China's high-quality economic development. With the rise of the digital technology revolution, China's digital transformation may play an integral and important role in increasing green total factor productivity (GTFP). Based on the panel data of 30 Chinese provinces from 2014-2020, the impact of digitization on GTFP was explored using the model of geographically and temporally weighted regression (GTWR), and the spatial and temporal distribution characteristics and development trends of such effects were further explored. The main findings are as follows: (1) China's digitalization level and GTFP has significant spatial autocorrelation and similar spatial distribution characteristics. (2) Digitalization has a significant positive impact on GTFP, but this impact decreases yearly, and there are noticeable regional differences. Digitalization in the eastern and central regions has a more significant impact on GTFP than in the west. (3) The region where China's digital development has extensively promoted GTFP has shifted from China's southern coastal region to the northwest and northeast regions. (4) The time-series fluctuations of the regression coefficients of the digitization level in each province in China also show agglomeration characteristics. That is, the regression coefficients of neighboring provinces have similar time-series fluctuations.

Impact of Artificial Intelligence on Regional Green Development under China's Environmental Decentralization System-Based on Spatial Durbin Model and Threshold Effect

Artificial intelligence (AI) is the core technology of digital economy, which leads the transition to a sustainable economic growth approach under the Chinese-style environmentally decentralized system. In this paper, we first measured the green total factor productivity (GTFP) of 30 Chinese provinces from 2011 to 2020 using the super-efficiency slacks-based measure (SBM) model, analyzed the mechanism of the effect of AI on GTFP under the environmental decentralization regime, and secondly, empirically investigated the spatial evolution characteristics and the constraining effect of the impact of AI on GTFP using the spatial Durbin model (SDM) and the threshold regression model. The findings reveal: a U shape of the correlation of AI with GTFP; environmental decentralization acts as a positive moderator linking AI and GTFP; the Moran index demonstrates the spatial correlation of GTFP; under the constraint of technological innovation and regional absorptive capacity as threshold variables, the effect of AI over GTFP is U-shaped. This paper provides a useful reference for China to accelerate the formation of a digital-driven green economy development model.

Measurement of China's Green Total Factor Productivity Introducing Human Capital Composition

In the face of resource and environmental problems caused by extensive economic development, China has put forward a green development strategy. Scientific measurement and analysis of green total factor productivity (GTFP) is of great significance for achieving high-quality economic development. By introducing the human capital composition, including education, health, scientific research, and training, this paper study adopts the Slack Based Measure-Global Malmquist-Luenberger (SBM-GML) index to re-measure the GTFP and its decomposition of 30 provinces, municipalities, and autonomous regions in China from 2000 to 2019. The results show that: (1) China's GTFP has a fluctuating growth trend, with an average annual growth rate of 2.31%. (2) In terms of its decomposition, technical progress is the main force driving GTFP growth, with a contribution rate of 1.59%; the improvement of technical efficiency is a secondary driving force, with a contribution rate of 0.71%. (3) The measurement results of GTFP, considering the human capital composition, are generally higher than those without consideration, and the GTFP growth under the two modes shows a trend of "high in the east and low in the west". The conclusions have enlightening significance for improving GTFP and the growth potential of the economy in China.

Do pilot free trade zones improve the green total factor productivity? Evidence from a quasi-natural experiment in China

China's pilot free trade zone (PFTZ) is an important national strategy to achieve high-quality development, so it is necessary to discuss the effect of PFTZ implementation on green total factor productivity (GTFP). Based on the data from 279 cities in China from 2004 to 2018, this study takes the establishment of PFTZ as a quasi-natural experiment and uses the difference-in-differences (DID) method to systematically evaluate the effect of PFTZ on urban GTFP. The empirical results of this paper are shown as follows: Firstly, the construction of PFTZ has a significant effect on urban GTFP, and this effect has increased gradually over time. Secondly, the construction of PFTZ mainly promotes the urban GTFP by increasing the level of science and technology innovation, reducing government intervention and improving the level of human capital. Thirdly, the effect of PFTZ construction on GTFP is more pronounced in regions with earlier waves of PFTZ and in western regions where environmental concerns are higher. In addition, there is a significant positive linkage between the construction of the PFTZ and the Belt and Road Initiative to improve the urban GTFP. The findings of this paper enrich the relevant literature on PFTAs and sustainable development and provide a theoretical basis for further promotion of PFTZ construction.

Space–Time Effect of Green Total Factor Productivity in Mineral Resources Industry in China: Based on Space–Time Semivariogram and SPVAR Model

Improving green total factor productivity (GTFP) is the key for China’s mineral resources industry to get out of the dilemma of resource depletion and environmental degradation. The Super Slacks-Based Measure (Super-SBM) model with undesirable output is used to calculate the GTFP of China’s mineral resources industry between 2004 and 2019, and the space–time correlation threshold is quantitatively determined by the space–time semivariogram. On this basis, the spatial weight matrix is constructed, and the spatial panel vector autoregression (SPVAR) model is used to quantitatively estimate the space–time impact response among GTFP, import dependence, and R&D investment. The results show that: (1) The maximum range of mineral resources industry GTFP in time and space are 12.28 years and 635.28 km, respectively. Taking the space range as the correlation distance threshold to construct spatial weight matrix improves the accuracy of spatial analysis. (2) The increase in import dependence and R&D investment can effectively improve the GTFP of local and its neighboring provinces. In the long term, an increase in import dependence has a positive impact on R&D investment, and an increase in R&D investment can reduce the import dependence. (3) In the response to impact, the eastern region is greater than the western region, the coastal provinces are greater than the inland provinces, and the provinces close to the impact source are greater than the provinces far away. Therefore, policies to limit resource and energy consumption, pollution, and carbon emissions should be strengthened. The incentive policies should be emphasized differently and adopted for the impact sources and response areas. The R&D investment in the full mineral industry process should be increased to improve the GTFP.

Impact of environmental regulation on green total factor productivity: a new perspective of green technological innovation

Green total factor productivity (GTFP) is an essential indicator to measure economic and environmental efficiency. Moreover, formulating a reasonable environmental regulation system and promoting green technological innovation is a systematic way to improve GTFP. However, previous related studies lack to investigate the impact of environmental regulation on GTFP from the perspective of green technological innovation. For this purpose, this paper aims to examine the specific impact of environmental regulation on GTFP based on the perspective of green technology innovation, so as to provide some policy insights for the formulation of more effective implementation of environmental regulation, improve green technology innovation level, and achieve a win-win situation for both economic growth and environmental protection. Furthermore, epsilon-based measure (EBM), which includes both radial and non-radial distance functions, is used to measure the GTFP. The spatial autoregressive method is also employed to quantify the impact of environmental regulation on GTFP from the perspective of green technological innovation using panel data of 269 prefecture-level cities in China from 2004 to 2018. The main findings indicate that there is a significant spatial autocorrelation between environmental regulation and GTFP. Environmental regulation has a significant positive effect on GTFP. Environmental regulation in the local regions also significantly contributes to GTFP in neighboring regions. Besides, environmental regulation indirectly promotes GTFP by enhancing green technological innovation level. Regional heterogeneity results show that environmental regulation can not only directly promote GTFP but also indirectly significantly promote GTFP through green technological innovation in the eastern and central regions, but insignificant in the western region. Based on the above findings, we conclude that policymakers should not only develop differentiated environmental regulation standards and steadily improving the intensity and rationality of environmental regulation but also add green innovation funds supply, enhance green innovation factor allocation efficiency, and strengthen R&D talents, funds, and policies to green technology innovation, so as to drive GTFP improvement.

Impact of Environmental Regulation on the Green Total Factor Productivity of Dairy Farming: Evidence from China

Environmental regulation is essential to promote green and sustainable development in dairy farming. Nevertheless, limited studies have focused on the impact of environmental regulation on the green total factor productivity (GTFP) of dairy farming. This study measures the GTFP of dairy farming in 27 provinces in China during 2009–2020 using the Slack Based Measure (SBM) model and the Malmquist–Luenberger (ML) productivity index. In addition, random effects and threshold regression models are used to measure the impact of environmental regulations on the GTFP of dairy farming. The results demonstrate the fluctuating growth of the GTFP of dairy farming and that technical efficiency is the primary driver of the GTFP growth. The annual growth rate of GTFP is the highest in large-scale dairy farming (3.27%), followed by medium-scale dairy farming (2.73%) and small-scale dairy farming (1.98%). Furthermore, environmental regulation positively affects the GTFP and has a threshold effect on the GTFP, with the urban–rural income gap as the threshold variable in medium-scale dairy farming and small-scale dairy farming. The impact on the GTFP can be significantly negative if the urban–rural income gap crosses the threshold value. Overall, this study provides some policy recommendations for attaining green and sustainable dairy farming development in China.

Spatial correlation among cultivated land intensive use and carbon emission efficiency: A case study in the Yellow River Basin, China

Considering the current global goal of carbon neutrality, the relationship between cultivated land intensive use (CLIU) and carbon emission efficiency (CEE) should be explored to address the global climate crisis and move toward a low-carbon future. However, previous work in this has been conducted at provincial/regional scales and few have identified the spatial correlation between CLIU and CEE at the scale of large river basins. Therefore, this study explored the spatiotemporal characteristics of CLIU, cultivated land carbon emissions (CLCE), and CEE, as well as the spatial correlation between CLIU and CEE in the Yellow River Basin (YRB), China. A comprehensive evaluation model, the Intergovernmental Panel on Climate Change (IPCC) coefficient methodology, existing data envelopment analysis model, and bivariate spatial autocorrelation models were used to analyze statistical data from 2005 to 2017. We found that the overall CLIU and CLCE values in the YRB exhibited a continuous increase; the average carbon emission total efficiency and carbon emission scale efficiency first decreased and then increased, and the average carbon emission pure technical efficiency gradually decreased. Areas of high CLCE were concentrated in eastern areas of the YRB, whereas those of high CLIU, carbon emission total efficiency, carbon emission scale efficiency, and carbon emission pure technical efficiency predominantly appeared in the eastern areas, followed by central and western areas of the YRB. Spatial analysis revealed a significant spatial dependence of CLIU on CEE. From a global perspective, the spatial correlations between CLIU and CEE changed from positive to negative with time. Moreover, the aggregation degree between CLIU and CEE gradually decreases with time, while the dispersion degree increases with time, and the spatial correlation gradually weakens. The local spatial autocorrelation further demonstrates that the number of high-low and low-high clusters between CLIU and CEE gradually increases over time, while the number of high-high and low-low clusters gradually decreased over time. Collectively, these findings can help policymakers formulate feasible low-carbon and efficient CLIU policies to promote win-win cooperation among regions.