The Study of the Impact of Carbon Finance Effect on Carbon Emissions in Beijing-Tianjin-Hebei Region—Based on Logarithmic Mean Divisia Index Decomposition Analysis

Li, Li; Liu, Di; Hou, Jian; Xu, Dazhi; Chao, Wenbo

doi:10.3390/su11051465

Cited by 26 publications

(13 citation statements)

References 22 publications

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“…Referring to the group of studies that are related to financial and economic development, our findings are in line with the research results presented by Li et al [51], who determined the positive impact of sustainable finance on carbon emissions in the Beijing-Tianjin-Hebei region (China).…”

Section: Discussionsupporting

confidence: 91%

“…The general trends and research results showed that there is a relationship between economic and financial development and environmental degradation (usually defined by greenhouse gas emissions). Our findings are in line with the group of studies that have determined the positive impact of economic and financial development on greenhouse gas emissions [53][54][55][56] and they are in line with the group of research that refers to the positive impact of sustainable finance on greenhouse gas emissions [40,[45][46][47][48][49]51,52]. The positive role of environmental taxes is especially worth mentioning.…”

Section: Discussionsupporting

confidence: 91%

“…The empirical results of this study found that sustainable finance is a crucial factor that will inhibit the increase of carbon emissions. These research results inter alia showed that the total carbon emission reduction value that was caused by the green credit effect from 2010 to 2016 in the Beijing-Tianjin-Hebei region was 66,193.96 million tons [51].…”

Section: Discussionmentioning

confidence: 90%

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Impact of Sustainable Financial and Economic Development on Greenhouse Gas Emission in the Developed and Converging Economies

2019

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Several studies have examined the relationship between environmental performance and economic development. However, most of them did not take sustainable development and financial development into account. The study argues that sustainable financial and economic development contributes to reducing greenhouse gas emissions. We use the panel data regression model to capture the relationship between greenhouse gas emission and sustainable economic and financial development. The panel data refers to the period of 2007–2017. The EU 25 countries were analysed. The results show that the relationship between sustainable financial development and environmental degradation is more relevant for converging economies than developed countries. We found that the variable “energy productivity” has the strongest impact on greenhouse gas emissions for both country groups (converging and developed); however, it increases for developed countries and it decreases the greenhouse gas emissions for converging economies. We also found that environmental taxes are an efficient instrument that mitigates greenhouse gas emissions, especially in developed countries group.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 90%

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Impact of Sustainable Financial and Economic Development on Greenhouse Gas Emission in the Developed and Converging Economies

2019

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“…LMDI has been widely used to decompose GHG emissions from many fields. For example, it has been applied to the transport (Kim, 2019), industrial (L. Li et al, 2019), and household sector (Kurniawan et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

A LMDI decomposition analysis of carbon dioxide emissions from the electric power sector in Northwest China

Mai

Ran

2020

Natural Resource Modeling

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Taking advantage of the electrification strategy, Northwest China has made full use of its natural resources endowment, to develop renewable energy as the substitution of thermal power. To evaluate carbon dioxide (CO2) emissions from electric power sector, an extended Kaya identity equation and the Logarithmic mean Divisia index decomposition method are applied to Northwest China from 1998 to 2017. Six explaining factors are analyzed, including carbon intensity, energy mixes, generating efficiency, electrification, economy and population. The results show that driving forces of CO2 emissions from electricity system varied greatly among provinces. Generally, economic growth has mainly contributed to increase CO2 emission, while the improvement in the power‐generating efficiency has crucially decreased CO2 emission. In 2017, Promoting electrification directly increased CO2 emissions from electric system, but indirectly reduced CO2 emissions from the whole region by 5.10% through the estimation of a clean development mechanism method. Therefore, local governments are suggested continuing to promote electrification to guide future emission reduction, while enterprises and individuals need to make their own contributions to low‐carbon development. Recommendations for Resource Managers: Variations of carbon dioxide (CO2) emissions of all five provinces in Northwest China are analyzed. Logarithmic mean Divisia index analysis is used to study the main drivers of CO2 emission change. Improvements in the generating efficiency significantly reduced CO2 emissions. Due to electrification effects, CO2 emissions from electric power increased, but CO2 emissions from the region decreased. Economy effects were still the biggest drivers affecting CO2 emission.

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“…The empirical results show that financial development can not only promote economic growth, but also indirectly restrain carbon emissions by stimulating technological innovation. Li (2019) [29] believes that the development of green credit will help reduce carbon emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial Effects of Technological Progress and Financial Support on China’s Provincial Carbon Emissions

Zhou

Liu

et al. 2019

IJERPH

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The spatial autocorrelation analysis method was applied to panel data from the provinces of China (including autonomous regions and municipalities directly under the central government) for the period 2003 to 2016 in order to construct a spatial Durbin model of technological progress and financial support in relation to reductions in carbon emissions. The results show that China’s carbon intensity presents significant spatial spillover effects under different spatial weights, which indicates that the carbon intensity of a province is influenced not only by its own characteristics, but also by the carbon emission behaviors of geographically adjacent and economically similar provinces and regions. Financial structure, financial scale, and financial efficiency all have significant effects on carbon intensity within a province, while financial structure is also linked to carbon intensity in other regions, but financial scale has no significant spillover effect on carbon intensity in space. Areas with high financial efficiency can reduce their own carbon intensity as well as that of surrounding areas. The inter-regional spillover effect of technological progress on carbon intensity is stronger than the spillover effect, but there is a time lag.

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The Study of the Impact of Carbon Finance Effect on Carbon Emissions in Beijing-Tianjin-Hebei Region—Based on Logarithmic Mean Divisia Index Decomposition Analysis

Cited by 26 publications

References 22 publications

Impact of Sustainable Financial and Economic Development on Greenhouse Gas Emission in the Developed and Converging Economies

Impact of Sustainable Financial and Economic Development on Greenhouse Gas Emission in the Developed and Converging Economies

A LMDI decomposition analysis of carbon dioxide emissions from the electric power sector in Northwest China

Spatial Effects of Technological Progress and Financial Support on China’s Provincial Carbon Emissions

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