scholarly journals Can Financial Development Curb Carbon Emissions? Empirical Test Based on Spatial Perspective

2021 ◽  
Vol 13 (21) ◽  
pp. 11912
Author(s):  
Xueyang Liu ◽  
Xiaoxing Liu

To respond to global climate change and achieve a “carbon peak” and “carbon neutrality” as soon as possible has become a common goal around the world. Economic growth relies heavily on financial development; indeed, low-carbon economic development is inseparable from financial support. This paper studies the impact of financial development on carbon emission intensity and its mechanism from both theoretical and empirical aspects. Based on the 2005–2018 data on Chinese cities and the Spatial Durbin Model (SDM) research results, this paper finds that: (1) Financial development has significantly reduced China’s carbon emission intensity overall. After considering spatial effects, financial development increases local carbon emission intensity, although it may lead to a more significant decrease in the surrounding area. (2) The analysis of heterogeneity shows that only the financial development in the eastern region has a substantial detrimental impact on total carbon emission intensity and the carbon emission intensity of neighboring cities. The financial development in the central and western regions has no significant effect on carbon emission intensity. (3) The mechanism test shows that financial development mainly reduces carbon emission intensity through technological innovation and structural optimization, with the effect of technological innovation being 9.5%, and the effect of structural optimization being 12.15%. The expansion of the consumption effects of financial development has no significant impact on carbon emission intensity. Accordingly, this article believes that it is necessary to further support financial development, build large-scale financial centers, continue to optimize the structure of financial products, and encourage the development of green finance.

2021 ◽  
Author(s):  
Xueyang Liu ◽  
Xiaoxing Liu

Abstract To respond to global climate change and achieve "carbon peak" and "carbon neutrality" as soon as possible has become a common goal around the world. Economic growth relies heavily on financial development; indeed, low-carbon economic development is inseparable from financial support. This paper studies the impact of financial development on carbon emission intensity and its mechanism from both theoretical and empirical aspects. Based on the 2005–2018 data on Chinese cities and the Spatial Durbin Model (SDM) research results, this paper finds: (1) Financial development has significantly reduced China's carbon emission intensity overall. After considering spatial effects, financial development increased local carbon emission intensity, although it may lead to a more significant decrease in the surrounding area. (2) The analysis of heterogeneity shows that only the financial development in the eastern region has a substantial detrimental impact on total carbon emission intensity and the carbon emission intensity of neighboring cities. The financial development in the central and western regions has no significant effect on carbon emission intensity. (3) The mechanism test shows that financial development mainly reduces carbon emission intensity through technological innovation and structural optimization, with the effect of technological innovation 9.5%, and the effect of structural optimization 12.15%. The expansion of the consumption effects of financial development has no significant impact on carbon emission intensity. Accordingly, this article believes that it is necessary to further support financial development, build large-scale financial centers, continue to optimize the structure of financial products and encourage the development of green finance.


Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shuping Cheng ◽  
Lingjie Meng ◽  
Lu Xing

PurposeThe purpose of this paper is to examine the effects of energy technological innovation on carbon emissions in China from 2001 to 2016.Design/methodology/approachConditional mean (CM) methods are first applied to implement our investigation. Then, considering the tremendous heterogeneity in China, quantile regression is further employed to comprehensively investigate the potential heterogeneous effect between energy technological innovation and carbon emission intensity.FindingsThe results suggest that renewable energy technological innovation has a significantly positive effect on carbon emission intensity in lower quantile areas and a negative effect in higher quantile areas. Contrarily, fossil energy technological innovation exerts a negative correlation with carbon emission intensity in lower quantile areas and a positive effect on carbon emission intensity in higher quantiles areas.Originality/valueConsidering that energy consumption is the main source of CO2 emissions, it is of great importance to study the impact of energy technological innovation on carbon emissions. However, the previous studies mainly focus on the impact of integrated technological innovation on carbon emissions, ignoring the impact of energy technological innovation on carbon emissions mitigation. To fill this gap, we construct an extended STIRPAT model to examine the effects of renewable energy technological innovation and fossil energy technological innovation on carbon emissions in this paper. The results can provide a reference for the government to formulate carbon mitigation policies.


Author(s):  
Xuhui Ding ◽  
Zhongyao Cai ◽  
Qianqian Xiao ◽  
Suhui Gao

It is greatly important to promote low-carbon green transformations in China, for implementing the emission reduction commitments and global climate governance. However, understanding the spatial spillover effects of carbon emissions will help the government achieve this goal. This paper selects the carbon-emission intensity panel data of 11 provinces in the Yangtze River Economic Belt from 2004 to 2016. Then, this paper uses the Global Moran’s I to explore the spatial distribution characteristics and spatial correlation of carbon emission intensity. Furthermore, this paper constructs a spatial econometric model to empirically test the driving path and spillover effects of relevant factors. The results show that there is a significant positive correlation with the provincial carbon intensity in the Yangtze River Economic Belt, but this trend is weakening. The provinces of Jiangsu, Zhejiang, and Shanghai are High–High agglomerations, while the provinces of Yunnan and Guizhou are Low–Low agglomerations. Economic development, technological innovation, and foreign direct investion (FDI) have positive effects on the reduction of carbon emissions, while industrialization has a negative effect on it. There is also a significant positive spatial spillover effect of the industrialization level and technological innovation level. The spatial spillover effects of FDI and economic development on carbon emission intensity fail to pass a significance test. Therefore, it is necessary to promote cross-regional low-carbon development, accelerate the R&D of energy-saving and emission-reduction technologies, actively enhance the transformation and upgrade industrial structures, and optimize the opening up of the region and the patterns of industrial transfer.


2019 ◽  
Vol 14 (3) ◽  
pp. 381-385 ◽  
Author(s):  
Yan Li ◽  
Guilin Dai

Abstract Energy saving and emission reduction have been not only a slogan but also a policy in this modern society where the phenomenon of greenhouse is exacerbated. In this study, calculation method of carbon emission and integrated parallel acquisition technique (IPAT) scenario prediction model were combined to predict the changes of total carbon emissions, energy structure distribution, and carbon emission intensity under three measures of energy saving and emission reduction in the next ten years in Shandong, China. The results showed that the total carbon emission increased year by year, and the coal ratio and carbon emission intensity decreased under the natural scenario; the total carbon emission in the weakly constrained scenario would increase annually until 2029, the amplitude was smaller than that of the natural scenario, while the coal ratio and carbon emission intensity would decrease, and the amplitude was larger than that of the natural scenario. Under the strongly constrained scenario, the total carbon emission would increase annually before 2025, and the amplitude was smaller than the weakly constrained scenario, while the coal ratio and carbon emission intensity would decrease, and the amplitude was larger than the weakly constrained scenario.


Author(s):  
Zhanglan Wu ◽  
Jie Tang ◽  
Dong Wang

As the world’s second largest economy, China ranks amount the world’s top nations when it comes to carbon emission, and therefore its attitude towards climate change is closely followed by all parties concerned. There have been few researches on the role of environmental governance in low-carbon city transformation process, especially the Chinese one. This paper analyses the role of government environmental regulation played in the low-carbon city transformation process by taking Shenzhen as the research object. One of the world's youngest super cities, it also happens to be the lowest carbon emission intensity city in China. Striving to explore green low-carbon development path for the whole country, Shenzhen provides practical experience for countries to cope with global climate change. However, its efforts to reduce the total carbon emissions failed, but it emphasized the carbon emission intensity, which is consistent with the international commitments made by the central government. China’s policy towards handling climate change relies on hierarchical governance arrangement. The strength of the NGOs in the country is weak and incomparable with the government’s, which has mastered most of the resources and is just a reality in China.


2021 ◽  
Vol 251 ◽  
pp. 02070
Author(s):  
Yang Li

This paper uses China’s provincial panel data from 1997 to 2015 to construct the Malmquist- Luenberger productivity indicators to measure the level of green biased technology progress, and measures the change in industrial structure based on indicators of low-carbon transformation, optimization and rationalization of industrial structure, and empirically tests the impact of green biased technology progress and industrial structure adjustment on China’s provincial carbon emission intensity. The results show that green biased technology progress can significantly exert the suppression effect of carbon emission intensity through the channel of low-carbon transformation of industrial structure.


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