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This paper introduces a new green decomposition model of carbon productivity that aims to further analyze the regional differences in carbon productivity and its interaction with regional industrial performance. We combine desired outputs and undesired outputs orientation, and multiple factor inputs to derive a new green decomposition theorem, establish a new green decomposition model of carbon productivity, and obtain nine effects of regional carbon productivity differences. Empirical analysis is conducted using input-output data from 29 provinces and 15 industries in China, comparing the differences in carbon productivity from both the provincial and industry perspectives and exploring the mechanism of action. This paper provides theoretical basis and empirical evidence for regional carbon productivity enhancement and economic and industrial optimization from the perspective of multi-factor inputs, as well as policy insights for regional low-carbon transition development. [ABSTRACT FROM AUTHOR]

Economic agglomeration has played a key function in China's economic transformation. Meanwhile, structural adjustment and external pressure to reduce carbon emission necessitate a deeper investigation into its relationship with carbon productivity. This paper measures economic agglomeration and carbon productivity of 281 cities in China in 2003–2017. With the purpose of exploring the spatial effect of economic agglomeration on carbon productivity, a spatial Durbin model is constructed. In addition, the mediation effect model is also adopted for examining the transmission mechanism of economic scale and technological progress on economic agglomeration as well as carbon productivity. A heterogeneity test is also carried out to uncover the varying effects of economic agglomeration on carbon productivity. The empirical results suggest that economic agglomeration raises carbon productivity not only in the local cities but also in the neighbouring ones. The impact of economic agglomeration on carbon productivity becomes more potent as the level of economic agglomeration increases. For cities with low level of economic agglomeration, the effect is mainly achieved through the expansion of economic scale, but for cities with high level of economic agglomeration, the effect is mainly achieved through technological progress. Therefore, we suggest encouraging carbon productivity improvement through technology effect in cities with high economic agglomeration level, while enhancing carbon productivity through scale effect in cities with low economic agglomeration level. [ABSTRACT FROM AUTHOR]

Based on the international community's analysis of the present CO2 emissions situation, a Log Mean Divisia Index (LMDI) decomposition model is proposed in this paper, aiming to reflect the decomposition of carbon productivity. The model is designed by analyzing the factors that affect carbon productivity. China's contribution to carbon productivity is analyzed from the dimensions of influencing factors, regional structure and industrial structure. It comes to the conclusions that: (a) economic output, the provincial carbon productivity and energy structure are the most influential factors, which are consistent with China's current actual policy; (b) the distribution patterns of economic output, carbon productivity and energy structure in different regions have nothing to do with the Chinese traditional sense of the regional economic development patterns; (c) considering the regional protectionism, regional actual situation need to be considered at the same time; (d) in the study of the industrial structure, the contribution value of industry is the most prominent factor for China's carbon productivity, while the industrial restructuring has not been done well enough. [ABSTRACT FROM AUTHOR]

As urbanization has developed, a variety of urban clusters have gradually emerged with important effects on regional economic growth and carbon emissions. This paper constructs a multi-period difference-in-difference (DID) model for testing how urban cluster synergistic development policy (UCSDP) affects urban carbon productivity in 148 cities of China with 13 urban clusters as the experimental group from 2003 to 2019. According to the results, the UCSDP improves carbon productivity, mainly via reducing energy intensity. In addition, UCSDP improves carbon productivity by adjusting energy structure, increasing green innovation, altering city greening levels, and accelerating the process of urbanization. Moreover, it can produce synergistic effects in terms of energy structure, green innovation, greening level, and urbanization level. Furthermore, the UCSDP has heterogeneous effects on the carbon productivity in various cities. Specifically, the carbon productivity of high-status, high-rank, and resource-based cities responds more significantly to UCSDP. Therefore, policymakers should strengthen the integration of urban clusters, offer targeted development suggestions for different cities, modify the energy and greening structure, accelerate the process of urbanization, and focus on the formulation of reasonable environmental regulation policies. • Exploring the impact of UCSDP on carbon productivity with multi-period DID model. • The improvement of carbon productivity by UCSDP mainly comes from the decrease of energy intensity. • UCSDP increases carbon productivity by affecting energy structure, green innovation, greening level and urbanization level. • UCSDP produces synergistic effects in terms of energy structure, green innovation, greening level and urbanization level. • The impact of UCSDP on carbon productivity varies by city status, city rank and city type. [ABSTRACT FROM AUTHOR]

Renewable energy consumption has a strong driving force for promoting energy conservation and emission reduction, and is a new way to achieve clean and low-carbon development. Based on this, this paper uses the data of renewable energy consumption, carbon productivity, GDP, population, energy efficiency and technological innovation of 30 provinces in China from 2011 to 2020, and empirically analyzes the impact of renewable energy consumption on carbon productivity in 30 provinces in China, using STIRPAT model, comprehensively considers spatial horizontally and temporal vertically dimension. The empirical results show that: (1) China's carbon productivity shows a significant spatial spillover effect, its impact can spill over to adjacent areas within 1000 km; (2) China's renewable energy power consumption plays a significant role in promoting the improvement of carbon productivity. (3) Renewable energy consumption in the western region plays the most important role in driving carbon productivity. Finally, according to the temporal and spatial relationship between renewable energy consumption and carbon productivity in different regions, we provide specific regional policy suggestions. • The STIRPAT model is employed to explore temporal and spatial impact, while it considers sub regions. • Spatialy, the impact can spill over to adjacent areas within 1000km. Temporally, the impact fluctuates and rises. • The positive role of renewable energy consumption is found in China's western region. [ABSTRACT FROM AUTHOR]

whether political resource endowment affect regional low-carbon economic development has attracted the attention of many relevant stakeholders. Given that, by using remote sensing data such as nighttime light data and introducing the spatial econometric models, this paper selected 519 counties covering 69 prefecture-level cities in China's 14 provinces to explore the impact of political resource endowment on carbon productivity at the county level. The results showed that regional carbon productivity along the Long March areas was more 12% higher than that along non-Long March areas. Moreover, a series of robustness tests also verify that political resource endowment can effectively promote regional carbon productivity. Additionally, regional industrial structure is the most significant influencing factor in reducing carbon productivity. Our results also showed economic benefits generated from per unit carbon emissions in these counties along the Long March areas were obviously higher than those of counties along the non-Long March areas, indicating that counties along non-Long March areas should pay more attention to improving the balanced development of economic growth and environmental protection. Finally, for counties along the Long March areas and their surrounding regions, their carbon productivity spatially presents the typical spatial autocorrelation trend. Therefore, it is necessary to combine the transformation of industrial structure with the optimization of industrial spatial layout, and formulate the targeted improvement plan on carbon productivity for counties along the Long March areas to achieve coordinated low-carbon development. • The impact of political resource endowment on regional carbon productivity is explored; • Carbon productivity of counties along the Long March areas is higher than that of other counties; • Industrial structure hindered the growth of carbon productivity along the non-Long March areas; • Carbon productivity of counties benefitted from the endowment of political resources. [ABSTRACT FROM AUTHOR]

The rational implementation of environmental regulation and efforts to improve carbon productivity are the practical choices for China to address climate change. This paper mainly explores the correlations between environmental regulation and carbon productivity in China. The study first measures and analyzes carbon productivity and its changes. The results indicate that China's carbon productivity experienced several fluctuations during the study period. Overall, the carbon productivity is currently in a stable rising phase. According to the empirical research on the basis of the spatial spillover effect, a positive spatial correlation exists between carbon productivity in the different regions of China, and there is a threshold for the impact of environmental regulation on carbon productivity. As the intensity of environmental regulation changes from weak to strong, its effect on carbon productivity in local regions will be affected and change from negative to positive. Similar effects will be seen in neighboring regions. At present, the average intensity of China's environmental regulation has not yet reached this threshold. The eastern region's average intensity of environmental regulation is closest to its threshold, while the average intensities of the central and western regions are far from their respective thresholds. There is great potential to improve China's carbon productivity through the implementation of appropriate environmental regulations. • China's overall carbon productivity is currently in a stable rising phase. • China's carbon productivity has a significant positive spatial correlation. • The improvement of carbon productivity in local regions will also improve carbon productivity in neighboring regions. • There is a threshold for the impact of environmental regulation on carbon productivity in China. • The integral intensity of environmental regulation in China has not yet reached the threshold. [ABSTRACT FROM AUTHOR]