2022
DOI: 10.1371/journal.pone.0271455
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Research on coupling coordination and influencing factors between Urban low-carbon economy efficiency and digital finance—Evidence from 100 cities in China’s Yangtze River economic belt

Abstract: China is a large country with rapid economic expansion and high energy consumption, which implies that the country’s overall carbon emissions are enormous. It is vital to increase urban low-carbon economy efficiency (ULEE) to achieve sustainable development of China’s urban economy. Digital finance is a significant tool to boost ULEE by providing a convenient and effective funding channel for urban low-carbon economic transformation. Analyzing the coupled and coordinated relationship between ULEE and digital f… Show more

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Cited by 8 publications
(4 citation statements)
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“…This study calculates and analyzes the synergy degree of the ecological and environmental risk synergistic prevention and control mechanism of the Yangtze River Economic Belt based on the relevant indicator data of 11 provinces and cities in the Yangtze River Economic Belt from 2017 to 2021, and the findings further support the findings of previous researchers in this field [ 39 43 ]. First, the indicator system related to ecological environment shows a general increasing trend of synergy degree in the synergy measure, but the synergy degree is generally low.…”
Section: Discussionsupporting
confidence: 77%
“…This study calculates and analyzes the synergy degree of the ecological and environmental risk synergistic prevention and control mechanism of the Yangtze River Economic Belt based on the relevant indicator data of 11 provinces and cities in the Yangtze River Economic Belt from 2017 to 2021, and the findings further support the findings of previous researchers in this field [ 39 43 ]. First, the indicator system related to ecological environment shows a general increasing trend of synergy degree in the synergy measure, but the synergy degree is generally low.…”
Section: Discussionsupporting
confidence: 77%
“…The study area is stratified by factors, and the total number of samples is represented by = 1,2,… The variance value of the overall sample in the study area is σ 2 . The value range is [0,1], where a larger value indicates a stronger driving effect of the independent variable (X) on the dependent variable (Y), and vice versa 48 .…”
Section: Methodsmentioning
confidence: 99%
“…In order to examine the potential factors that influence the CCD, referring to the research conducted by Yao et al (2022) [ 44 ], this study incorporates five control variables, as follows: GDP per capita (X1): The GDP per capita is employed as a measure of each city’s economic development, and the data are adjusted for inflation using 2011 as the base year. Urbanization rate (X2): The urbanization rate of each city reflects its degree of urbanization.…”
Section: Convergence Analysismentioning
confidence: 99%