Green finance, technological progress, and ecological performance—evidence from 30 Provinces in China

Guo, Lin; Zhao, Haoxiang; Junyao, Yang; Yu, Jingyue; He, Taiyi

doi:10.1007/s11356-022-20501-w

Cited by 27 publications

(12 citation statements)

References 54 publications

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“…There are a number of approaches to measuring ecological performance, and we have compared these approaches, as shown in Table 2: In the current study, the calculation of the ecoperformance index can be broadly divided into two categories, the ratio method and the input-output model method (Dyckhoff and Allen, 2001;Dahlström and Ekins, 2005). In contrast, scholars prefer input-output modeling approaches, such as DEA, to evaluate ecological performance (Ge et al, 2022). There are two traditional forms of DEA models, CCR and BCC, which are unable to measure the full range of undesirable output.…”

Section: Ecological Performance Indexmentioning

confidence: 99%

“…Among these submodels, the Super-SBM method considers both undesirable output and super efficiency and is considered a more appropriate method. Therefore, a set of measurement systems of ecological performance was built based on the Super-SBM method, Frontiers in Environmental Science frontiersin.org according to researchers (Dong et al, 2020;Ge et al, 2022). The inputs, desirable and undesirable outputs used here are given in Table 3.…”

Section: Ecological Performance Indexmentioning

confidence: 99%

“…Moreover, excessive energy consumption has caused large emissions of greenhouse gases and has led to the emergence of global extreme climate phenomena. Increasingly frequent natural disasters continue to threaten human settlements and reduce the resilience of cities day-by-day (Yang et al, 2021;Ge et al, 2022;You et al, 2022). Hence, it is necessary to explore the relationship between economic development and the ecological environment to seek future development directions.…”

Section: Introductionmentioning

confidence: 99%

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Digital economy and ecological performance: Evidence from a spatial panel data in China

Shen

Zhao

et al. 2022

Front. Environ. Sci.

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The rapid development of information and communication technologies has brought the concept of digital economy into the limelight. Data elements have played a more important role in economic production. As an environmentally friendly economic model, the data factor-driven economy, compared to the traditional one, has low energy consumption and less pollution emissions. Hence, the effect of digital economy development on ecological performance is worth exploring. We measured the digital economy index and the ecological performance index for 30 provinces in China. Furthermore, the relationship between the two was analyzed with the help of a dynamic spatial Durbin model. The results showed the following: 1) closely related to the regional economic foundation, the development level of the digital economy showed obvious spatial characteristics that were high in the eastern region and low in the western region in China. 2) Over time, the pattern of ecological performance in China has changed markedly, showing a high level in the south and a low level in the north. 3) The digital economy showed a significant promoting effect on ecological performance, with a strong externality in space that could have a spillover effect on the surrounding areas. 4) The effect of the digital economy on ecological performance had a significant positive effect, although it lagged behind over time. In addition, the effect has regional heterogeneity and was more obvious in developed regions. Based on these findings, we recommend that the role of ICT in economic activity be strengthened in some developed regions. However, in some developing regions, a balance needs to be struck between digitalization and environmental benefits. At the same time, developed regions should be encouraged to realize economic collaboration with developing regions, with the help of data elements in an effort to narrow the regional gap.

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Section: Ecological Performance Indexmentioning

confidence: 99%

Section: Ecological Performance Indexmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Digital economy and ecological performance: Evidence from a spatial panel data in China

Shen

Zhao

et al. 2022

Front. Environ. Sci.

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“…In terms of environmental protection (E), green credit allocation has a substantial impact on the overall core competitiveness of banks and also has a positive impact on the return on interest-bearing assets of banks, thereby enhancing their financial performance (Ge et al 2022 ; Lian et al 2022 ; Luo et al 2021 ). In Finger et al ( 2018 )’s study of the effect of the equatorial principle on the business performance of banks, the authors note that for banks in developing nations, adhering to the equatorial principle is a long-term strategic decision.…”

Section: Literature Reviewmentioning

confidence: 99%

Environmental, social, and governance (ESG) and market efficiency of China’s commercial banks under market competition

Sun

Liu

et al. 2022

Environ Sci Pollut Res

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As the leading financial institutions in China, it is crucial for commercial banks to pay attention to environmental protection (E), social responsibility (S), and corporate governance (G) in order to enhance operational efficiency and to advance the high-quality development of the country’s social economy. This research explores the market share of banks as exogenous variables in the profit stage and the market and sustainability stage to investigate the efficiency of 20 listed banks in China over 2016–2020 and innovatively incorporates indicators such as green credit, social giving, executive compensation, and ESG score into the meta-dynamic two-stage SBM under the exogenous variable DEA model. The results demonstrate the following. (1) By integrating market share as an exogenous variable in the model, the efficiency estimate is more precise. (2) In overall, UCBs are the most efficient type of banks, JSCBs are the second, SOCBs are the least efficient. All three types of banks are more efficient in profit stage versus the market and sustainability stage, JSCBs perform best in the profit stage, where SOCBs perform best in the market and sustainability stage. The three different bank types’ TGR performance is comparable to their efficiency value performance. (3) SOCBs lead in ESG investment and have the best ESG performance due to their distinct state-owned background. With their ongoing dedication to profit maximization and disregard for social responsibility and sustainable development, JSCBs have the worst ESG performance. (4) Policy recommendations are made based on the study’s findings for commercial banks, stakeholders, and regulators to support ESG investment and to bring about long-term sustainable development. Finally, as ESG develops in China, future research can consider longer time scales and larger perspectives to investigate the sustainability efficiency of commercial banks themselves, as well as their role in the local economy and industrial transformation.

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“…For example, finance development can provide an inexhaustible source of funds, ensure the continuity, and reduce the external risk impact of technology innovation (Irwan et al, 2021;Stefano et al, 2022;Wang W. J. et al, 2022). Technology innovation can significantly improve, accelerate, and stabilize the quality of finance development (Chi et al, 2021;Ge et al, 2022;Sun and Razzaq, 2022). Strictly speaking, there are three main points.…”

Section: Introductionmentioning

confidence: 99%

Coupling coordination analysis of green finance and industrial technology innovation: A case study in Zhejiang Province, China

Wang

Lin

et al. 2022

Front. Environ. Sci.

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Both green finance and industrial technology innovation play irreplaceable roles in the framework of sustainable development. Research on the coupling and coordination between these systems will deepen the realization of sustainable development models. This study applied the TOPSIS entropy weight method to measure the development of green finance and industrial technology innovation in Zhejiang Province between 2012 and 2019 and used the coupling coordination degree model to determine the strength and effect of the interaction between these systems in Zhejiang Province. The results showed strong regional heterogeneity in the development of green finance and industrial technology innovation in the nine cities in Zhejiang Province within the study period. Moreover, mutual assistance and correlation between green finance and industrial technology innovation in the nine cities of Zhejiang Province increased over time. Finally, the effect of green finance and industrial technology innovation in the nine cities of Zhejiang Province was complex. The results of this study may inform policy suggestions regarding the roles potential roles of the government, commercial banks, and enterprises.

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Green finance, technological progress, and ecological performance—evidence from 30 Provinces in China

Cited by 27 publications

References 54 publications

Digital economy and ecological performance: Evidence from a spatial panel data in China

Digital economy and ecological performance: Evidence from a spatial panel data in China

Environmental, social, and governance (ESG) and market efficiency of China’s commercial banks under market competition

Coupling coordination analysis of green finance and industrial technology innovation: A case study in Zhejiang Province, China

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