Research on the impact of green finance on energy efficiency in different regions of China based on the DEA-Tobit model

Wang, Zilong; Wang, Xinbin

doi:10.1016/j.resourpol.2022.102695

Cited by 68 publications

(12 citation statements)

References 27 publications

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“…Due to differences in green energy efficiency, the impact of the digital economy on carbon emissions may also be different. On the one hand, regions with low green-energy efficiency are mostly concentrated in central and western China [ 43 ], where there are many zombie enterprises or resource-intensive enterprises, which makes it difficult to achieve emission reduction through the digital economy [ 23 ]; on the other hand, low green-energy efficiency may affect the development of digitalization and ultimately inhibit the development of a regional digital economy. In other words, regions with higher green-energy efficiency may be more flexible in production, and digital technology is integrated into production as an important factor of production, thereby greatly reducing carbon emissions.…”

Section: Theoretical Analysis and Research Hypothesesmentioning

confidence: 99%

Has the Digital Economy Reduced Carbon Emissions?: Analysis Based on Panel Data of 278 Cities in China

Zhou

Liu

Zhu

2022

IJERPH

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China is undergoing an urbanization process at an unprecedented scale, and low-carbon urban development is of great significance to the completion of the “dual carbon goals”. At the same time, the digital economy has become an important engine for urban development, and its role in environmental improvement has become increasingly prominent. While the digital economy is booming, can it promote the low-carbon development of cities? Based on the panel data of 278 cities in China from 2011 to 2019, this paper discusses the impact of the digital economy on carbon emissions and the long-term development trend between the digital economy and carbon emissions, the impact of differences in the development level of the digital economy on carbon emissions reduction, and the impact of green energy efficiency in the relationship between the digital economy and carbon emissions. The results show that the digital economy has a significant inhibitory effect on carbon emissions, and with the development of the digital economy, more and more cities show an absolute decoupling of the digital economy and carbon emissions and are turning to low-carbon development. The development level of the digital economy has a heterogeneous impact on carbon emissions. With the improvement of the development level of the digital economy, the effect on emission reduction is more significant. As a threshold variable, green energy efficiency affects the relationship between digital economy and carbon emissions. When green energy efficiency is low, the digital economy promotes carbon emissions, and when green energy efficiency is high, the digital economy reduces carbon emissions.

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Section: Theoretical Analysis and Research Hypothesesmentioning

confidence: 99%

Has the Digital Economy Reduced Carbon Emissions?: Analysis Based on Panel Data of 278 Cities in China

Zhou

Liu

Zhu

2022

IJERPH

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“…Based on the improved entropy weight method (Li and Wang (2022)) [12,37], Table 6 and Figure 1 illustrate the indicators of green financial development for each Chinese province. In particular, the indicators of green financial development in each Chinese province show an increasing trend over time.…”

Section: Results Of the Green Finance Development Indexmentioning

confidence: 99%

Impact of Green Finance on Carbon Emissions Based on a Two-Stage LMDI Decomposition Method

Lin,

Wang,

et al. 2023

Sustainability

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As the “double carbon” goal gains traction worldwide, achieving a balance between economic growth and environmental sustainability has become a focal point for researchers. Green finance, as a specialized financial service, offers a new approach to sustainable development. This study analyzed carbon emission sources in 25 Chinese provinces between 2007 and 2020, dividing them into energy structure, economic development, energy efficiency, and industrial structure, using a two-stage LMDI method. It then examines the linear and non-linear relationships between green finance and carbon emissions using spatial measurement methods. The findings indicate that green finance is an effective way to reduce carbon emissions, primarily through its impact on energy structure, energy efficiency, and industrial structure. There are significant non-linear relationships between green finance and the factors affecting carbon emissions, with spatial effects playing a significant role in carbon emissions influenced by energy structure, economic development, energy efficiency, and industrial structure.

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“…As DEA effi ciency estimates are serially correlated, this could aff ect the results of the tobit regression (Simar and Wilson, 2007). On the other hand, Wang and Wang (2022) claim that the tobit model has strong robustness and feasibility. Hence, it was decided to employ tobit regression in order to investigate the impact of DESI sub-indicators on the effi ciency of the digital economy of the EU.…”

Section: Methodsmentioning

confidence: 99%

Efficiency of Digital Economy in the Context of Sustainable Development: DEA-Tobit Approach

Skvarciany¹,

Lapinskaitė²,

Stasytytė³

2023

Prague Economic Papers

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The paper aims at measuring the efficiency of the digital economy in EU countries. For that purpose, data envelopment analysis (DEA) is used. Sub-dimensions of the Digital Economy and Society Index (DESI) are used as inputs and the Sustainable Development Goals Index (SDGI) as an output. The results revealed that Bulgaria, Italy and Romania are the most efficient digital economies in terms of human capital; Belgium,

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Research on the impact of green finance on energy efficiency in different regions of China based on the DEA-Tobit model

Cited by 68 publications

References 27 publications

Has the Digital Economy Reduced Carbon Emissions?: Analysis Based on Panel Data of 278 Cities in China

Has the Digital Economy Reduced Carbon Emissions?: Analysis Based on Panel Data of 278 Cities in China

Impact of Green Finance on Carbon Emissions Based on a Two-Stage LMDI Decomposition Method

Efficiency of Digital Economy in the Context of Sustainable Development: DEA-Tobit Approach

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