Since the reform and opening-up, China has made remarkable achievements in economic growth, but also led to a substantial increase in carbon emissions. The Chinese government has actively formulated energy intensity reduction targets and taken carbon emission reduction measures. The paper investigates the impact of energy intensity reduction targets on carbon emissions using a dynamic spatial Durbin model based on panel data from 30 provinces in China from 2006 to 2019. The results show that energy intensity reduction targets promote the reduction of local carbon emissions, but have a positive spillover effect on carbon emissions in adjacent regions. Meanwhile, green technology innovation has a non-linear moderating effect between energy intensity reduction targets and carbon emissions. Energy intensity reduction targets promote carbon emission reduction when green technology innovation is less than a threshold, while the promotion effect disappears when green technology innovation exceeds a threshold. The mechanism analysis shows that energy consumption structure is a channel through which energy intensity reduction targets affect carbon emissions in both local and adjacent regions. Further research found that peer competitive pressure promotes carbon emission reduction and alleviates pollution spillover, while central assessment pressure increases carbon emissions and aggravates pollution spillover. Based on the above findings, this study provides suggestions for policymakers aiming at carbon emission reduction by implementing target management policies and optimizing target management systems.
With the rapid development of new generation of information technology and the continuous deterioration of ecological environment, the environmental effect of digital economy has begun to receive attention. Based on panel data from 30 provinces in China during the period of 2014–2020, this study investigates the impact and mechanisms of digital economy on environmental quality using the fixed effect model and moderating effect model. The results show that the digital economy can significantly inhibit environmental pollution. The inhibitory effect of digital economy shows obvious regional heterogeneity, which is the strongest in the west, followed by the east, and the weakest in the center. The economic development level and income distribution inequality play positive and negative roles in regulating the negative linkage between digital economy and environmental pollution, respectively. The government should implement a differentiated strategy to promote the comprehensive development of digital economy and maximize its environmental effects, accelerate the integrated development of urban and rural economies through inclusive growth, and optimize the moderating effect of economic development level and income distribution inequality.
Based on the panel data of 281 city level in China for the period of 2004–2016, this study uses the Cobb–Douglas production function to investigate the distribution of environmental regulation dividends and further adopts the threshold model to explore the impact of environmental regulation dividends inequality (ERDI) on inclusive growth (IG). Results indicate that the distribution structure of the environmental regulation dividends has improved, but the inequality between urban–rural residents is still apparent. Environmental regulation dividends inequality has a non-linear threshold effect on inclusive growth, which turns from a significant inhibition to a slight promotion after exceeding the threshold value. Grouping tests show that environmental regulation dividends inequality has a heterogeneous effect on cities with different resource endowments and leading industries and still inhibits inclusive growth of non-resource-based cities even if the inequality is higher than the threshold value. Mechanism analysis reveals that primary distribution and redistribution are the main channels through which environmental regulation dividends inequality inhibits and promotes inclusive growth when the inequality is below and above the threshold value, respectively. These conclusions have important implications for enhancing and distributing environmental regulation dividends to promote inclusive growth.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.