Direct and indirect impacts of high-tech industry development on CO2 emissions: empirical evidence from China

Dynamic role of medium- and high-tech industries and environmental policy stringency in environmental sustainability: fresh insights from Dynamic Seemingly Unrelated Regression (DSUR) analysis

Since the last two decades, carbon neutrality has become a primary target of all economies. Governmental environmental policies stand as the most potent tools in the arsenal when it comes to tempering the effects of climate change. Fostering the adoption of green energy sources and embracing energy efficiency principles may assume an essential role in upholding the standard of ecological integrity. The primary objective of this inquiry revolves around the meticulous analysis of the intricate interplay between economic growth, the trajectory of industrialization, the up-gradation of industrial sector structure, the integration of green energy paradigms, and the implementation of energy efficiency strategies and environmental policies in the frame spanning from 2000 to 2019. To tackle the matter of cross-sectional dependency and heterogeneity, second-generation cointegration estimators, Dynamic Seemingly Unrelated Regression (DSUR) and Augmented Mean Group (AMG), were employed to estimate long-run relationships. The consequences of DSUR and AMG indicate that while economic and industrial growth contributes to environmental degradation, renewable energy usage, and medium-high-tech industries mitigate the carbon emissions in selected countries. Further study results suggest that energy intensity positively impacts environmental degradation, which means energy efficiency helps mitigate CO2 emissions in these countries. This study also reveals that the degree of stringency in environmental policy negatively affects CO2 releases in the selected nations. Consequently, our study recommends the enhancement of the stringency of environmental policies, promoting environmentally friendly energy usage, the efficient use of energy, and the advancement of industries into medium-high-tech industries as effective ways to mitigate climate change in specific developing countries.

Evaluating the impact of the innovation efficiency of high-tech industry on carbon emissions: a case study of the manufacturing industry in China

Amid China's economic shift to high-quality development, addressing environmental challenges like greenhouse gas emissions and manufacturing pollution, there is a crucial demand for sustainable and eco-friendly development strategies. This study aims to investigate the impact of innovation efficiency in the high-tech industry on carbon emissions. It seeks to explore regional differences, mechanisms, and the influence of energy consumption structures in achieving sustainable development goals. Utilizing data from 30 provinces spanning 2009 to 2020, the study employs the DEA-Malmquist index model, spatial and temporal classification evaluation, and a panel measurement model to assess the efficiency of innovation and development in high-tech industries and their relationship with carbon emissions. The results indicate several key findings: (1) The overall operational efficiency of high-tech industry innovation and development in China is steadily increasing. However, there are distinct characteristics observed among provinces and cities, reflecting diverse input and output types. (2) High-tech industry innovation efficiency significantly contributes to carbon emission reduction, and there is regional heterogeneity in this impact. The central and western regions exhibit greater effects compared to other provinces and cities. (3) The optimization of the energy structure is identified as a mechanism through which high-tech industry innovation efficiency reduces carbon emissions. Moreover, different intervals of high-tech industry innovation efficiency yield varying effects on carbon emissions. This research underscores the importance of fostering high-tech industry innovation efficiency as a means to reduce carbon emissions. It also identifies key areas for future policy development and resource allocation, emphasizing the support needed for low-carbon technology research and development.

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

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

Economic Growth Targets and Carbon Emissions: Evidence from China

Carbon emissions have become a new threat to sustainable development in China, and local government actions can play an important role in energy conservation and emission reduction. This paper explores the theoretical mechanisms and transmission paths of economic growth targets affecting carbon emissions from the perspective of economic growth targets and conducts an empirical analysis based on 30 provincial panel data in China from 2003 to 2019. The results show that: economic growth targets are positively correlated with carbon emissions under a series of endogeneity and robustness; there are regional heterogeneity, target heterogeneity and structural heterogeneity in the impact of economic growth targets on carbon emissions; after economic growth targets are set, government actions can influence carbon emissions by affecting resource mismatch and industrial restructuring; It is further found that there is a “U” shaped relationship between economic pressure and carbon emissions. Based on the above findings, this paper further proposes that a high-quality performance assessment mechanism should be developed to bring into play the active role of local governments in achieving carbon reduction goals, and thus contribute to high-quality economic development.

The Environmental Cost of Attracting FDI: An Empirical Investigation in Brazil

Many emerging economies seek to increase their Foreign Direct Investment (FDI) inflows to achieve some promised benefits, such as economic growth and advanced technologies. Nevertheless, FDI does not represent a random investment decision, and international literature demonstrates that foreign investors are mostly interested in fast-growing regions. Therefore, this study uses traditional panel data econometrics coupled with Data Envelopment Analysis (DEA) to investigate the environmental impact in regions with great potential to attract foreign investments (e.g., more advanced regions with growing infrastructure), therefore analyzing the environmental cost of attracting FDI. Additionally, this study employs regional data from the ‘Atlas of FDI in the State of São Paulo’ to investigate the environmental effects of FDI in the periphery, where attractiveness levels are low. The results indicate that regions with higher attractiveness levels prepare a pollutant development strategy and that FDI in less-developed regions is harmful to the environment. The results point to new perspectives on the FDI–environment debate and suggest that attracting FDI is environmentally costly. Also, FDI is heterogeneous, with its presence in peripheral areas being harmful to the environment. To conclude, we discuss these results and present an agenda for future research.

How industrial convergence affects regional green development efficiency: A spatial conditional process analysis

Industrial convergence is a key means to transform the economic mode. Taking the convergence of manufacturing and producer services in China as the research object, this study explored how industrial convergence affects regional green development efficiency (GDE). First, a coupling evaluation system was established to measure industrial convergence degree, and the directional distance function-based slacks-based measure was combined with the global Malmquist-Luenberger index to measure GDE. Second, we employed spatial econometric models to analyze the relationship between industrial convergence and GDE. Then, using the spatial conditional process analysis, a unified framework of green innovation, investment structure, and energy intensity was constructed to investigate the transmission mechanism involved. The results showed that: (1) Regional GDE and green innovation had a spatial dependence. (2) Considering the spatial correlation, industrial convergence is conductive to regional GDE. (3) Green innovation is an effective path by which industrial convergence improves regional GDE. (4) In this mediating process, the investment structure and energy intensity play a moderating role. The investment bias in high-tech industries increases the role of industrial convergence in promoting regional GDE and green innovation, while the moderating direction of energy intensity is opposite. In addition, there is a crowding-out effect in energy dependence, which hinders the effectiveness of green innovation.

Sulfur dioxide (SO2) emission reduction and its spatial spillover effect in high-tech industries: based on panel data from 30 provinces in China

Industrial sulfur dioxide (SO2) has become an important source of environmental pollution in China, and the regional SO2 emission reduction capacity is a comprehensive reflection of cleaner production capacity, environmental regulation, and economic development. It is obvious that high-tech industries play a crucial role in promoting the cleaner production capacity of the whole industry. Simultaneously, only considering the regional emission and the development of high-tech industry in isolation may deviate from actual economic characteristics. Therefore, by using the panel data of 30 provinces in China from 2005 to 2016, this paper adopts spatial autoregression model (SAR), spatial error model (SEM), and spatial Durbin model (SDM) to analyze the effect of the high-tech industry development on SO2 emission reduction under the spatial adjacency matrix (W1), geographic distance matrix (W2), and economic distance matrix (W3). In addition, this paper selects three indicators, which is SO2 removal rate, SO2 emission, and SO2 removal quantity, as explanatory variables, and R&D investment and number of enterprises in high-tech industry are selected to represent the industrial development level. The major conclusions are as follows: (1) The ability of SO2 emission reduction in the local province is significantly affected by the surrounding provinces, showing the agglomeration characteristics of "high-high" or "low-low." (2) The R&D investment of high-tech industry has a negative impact on SO2 removal rate and SO2 removal quantity, but a positive effect on the SO2 emissions for the local province, and has a positive effect on the emission reduction of surrounding provinces. (3) The expansion of high-tech industry has significantly improved the SO2 emission reduction capacity of the local province and its surrounding provinces. The robustness test supports the empirical conclusions of this paper. Finally, this paper puts forward some policy suggestions for government in environmental governance, such as "joint prevention and control" and the promotion of cleaner production.