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Chang K, Wang S. Impact of dual-carbon attention competition from local government on regional carbon emissions in China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2025; 374:124064. [PMID: 39809004 DOI: 10.1016/j.jenvman.2025.124064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 12/16/2024] [Accepted: 01/05/2025] [Indexed: 01/16/2025]
Abstract
Extreme climate change induced by carbon emissions has received extensive attention from governments worldwide. Strong competition in local governments' dual-carbon attention (GCA) produces an effective influence on the reduction of regional carbon emissions, confirming crucial policy implications. In this study, textual content analysis is employed to measure the GCA level and GCA competition, and the mechanism by which GCA competition reduces regional carbon emissions in China is explored from the perspective of competition behaviors. The findings demonstrate that the increase of GCA competition positively influences the reduction of regional carbon emissions. Influence mechanism analyses verify that increasing GCA competition primarily stimulates the greater reduction of regional carbon emissions by intensifying competition in energy consumption reduction and the optimization of the energy consumption structure. The influence of GCA competition on reduced regional carbon emissions is significantly related to industrial structure upgrading, the energy consumption structure, and environmental governance investment, as well as inter-government competition in these areas. The detailed findings of this research can provide economic and environmental benefits for policymakers, and can provide corporations with more targeted policy recommendations related to dual-carbon attention and carbon emission reduction.
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Affiliation(s)
- Kai Chang
- School of Finance and Business, Shanghai Normal University, Shanghai, 200234, China
| | - Susheng Wang
- Business School, Southern University of Science and Technology, Shenzhen, 518055, China.
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2
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Wei C, Xu J, Wang Z, Wu H, Wang J. How to implement pairing assistance during fighting COVID-19 in China: collaborative governance between local governments under the authoritative regulation. Front Public Health 2025; 12:1417832. [PMID: 39850856 PMCID: PMC11754058 DOI: 10.3389/fpubh.2024.1417832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 12/27/2024] [Indexed: 01/25/2025] Open
Abstract
Background The pairing assistance policy represents a distinctive instrument utilized by the Chinese government to address major public crises. This study examines the development of a pairing assistance policy by the Chinese Government through its central authority to foster collaborative governance among local governments in areas affected by COVID-19. Methods The aim of the study was to gain a clear understanding of how the policy of pairing assistance in public health emergencies is successfully implemented through the top-down application of authority. A case study design was used as a methodology to present an explanatory framework for implementing pairing assistance policies during major public crises. We focus on the operational process of pairing assistance, using the assistance provided by Jiangsu Province to Huangshi City in Hubei Province as an illustration. Results This paper finds that responding to a crisis requires the guidance of a central authority and the cooperation of local governments. The process is driven by three key factors: the vertical intervention of the crisis, the inevitability of horizontal cooperation and the policy allocation and incentives of the bureaucracy. The three stages of co-operative governance based on authoritative regulation work together in a step-by-step manner to enhance the effectiveness of crisis response. Conclusion The results of the study indicate that collaborative governance under the authoritative regulation is the main reason why provincial counterpart support mechanism plays a great role in COVID-19. This study is the first to approach the study of pairing assistance from the perspective of government authority. It broadens the research horizon of local government cooperation and provides a model for future collaboration.
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Affiliation(s)
- Changwei Wei
- School of Public Policy and Management, China University of Mining and Technology, Xuzhou, China
| | - Jiaxi Xu
- School of Political Science and Public Administration, Wuhan University, Wuhan, China
| | - Zhixiang Wang
- School of Public Administration, Jilin University, Changchun, China
| | - Huangyue Wu
- School of Public Policy and Management, China University of Mining and Technology, Xuzhou, China
| | - Juan Wang
- School of Public Policy and Management, China University of Mining and Technology, Xuzhou, China
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3
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Alofaysan H, Radulescu M, Balsalobre-Lorente D, Si Mohammed K. The effect of eco-friendly and financial technologies on renewable energy growth in emerging economies. Heliyon 2024; 10:e36641. [PMID: 39281578 PMCID: PMC11395751 DOI: 10.1016/j.heliyon.2024.e36641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 08/20/2024] [Accepted: 08/20/2024] [Indexed: 09/18/2024] Open
Abstract
Successfully integrating renewable energy sources depends on eco-friendliness, financial technology, and economic growth (GDP). This paper examines the dynamic effect of innovative financial and green technology on renewable energy for 38 emerging economies from 2006 to 2021. Using the dynamic First-difference Generalized Method of Moments (FD-GMM) model, the analysis identifies a critical GDP threshold of 1831.772 US dollars, significant at the 1 % confidence level. Below this threshold, GDP negatively affects green energy adoption, while above it, GDP positively influences the shift to greener energy, supporting the predicted U-shaped relationship in the data. The results conclude that eco-friendly and financial technology positively and significantly influence renewable energy adoption, where the dynamics and barriers to adopting eco-friendly and financial technologies in emerging countries may differ from those in developed nations. Based on the findings, relevant energy policies have been recommended for energy stakeholders, Tech firms and decision-makers.
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Affiliation(s)
- Hind Alofaysan
- Department of Economics, College of Business Administration, Princess Nourah bint Abdulrahman University, Saudi Arabia
| | - Magdalena Radulescu
- Institute of Doctoral and Post-Doctoral Studies, University Lucian Blaga of Sibiu, Sibiu, Romania
- UNEC Research Methods Application Center, Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str. 6, Baku 1001, Azerbaijan
| | - Daniel Balsalobre-Lorente
- Department of Applied Economics I, University of Castilla La Mancha, Spain
- UNEC Research Methods Application Center, Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str. 6, Baku 1001, Azerbaijan
- Department of Management and MarketingCzech University of Life Sciences PragueFaculty of Economics and Management, Prague Czech Republic
- Western Caspian University, Economic Research Center (WCERC), Baku, Azerbaijan
| | - Kamel Si Mohammed
- University of Ain Temouchent, Algeria
- Université de Lorraine, CEREFIGE, F-57000 Metz, France
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4
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Xia M, Dong L, Zhao X, Jiang L. Green technology innovation and regional carbon emissions: analysis based on heterogeneous treatment effect modeling. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:9614-9629. [PMID: 38196040 DOI: 10.1007/s11356-023-31818-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 12/28/2023] [Indexed: 01/11/2024]
Abstract
The impact of green technology innovation on regional carbon emissions has been a contentious issue in academic research. In this study, we attempt to analyze the influence of green technology innovation on regional carbon emissions using panel data from 28 Chinese provinces for the period of 2007-2020. Utilizing a heterogeneous treatment effect model, we systematically examine the effects of green technology innovation on regional carbon emissions. Firstly, we conduct a feature selection analysis on the factors influencing regional carbon emissions using causal inference methods based on machine learning. Subsequently, we explore the conditional and marginal treatment effects of green technology innovation on regional carbon emissions using the heterogeneous treatment effect model. Finally, we investigate the dynamic effects of green technology innovation on regional carbon emissions across different periods. Empirical results indicate that firstly, green technology innovation indirectly reduces regional carbon emissions by promoting energy efficiency improvement; secondly, the impact of green technology innovation on carbon emissions exhibits significant regional heterogeneity, with the largest effect observed in the eastern region, followed by the western region and the smallest effect in the central region; thirdly, at a significance level of 5%, green technology innovation has a direct inhibitory effect on carbon emissions in certain regions.
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Affiliation(s)
- Maosen Xia
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, 233030, Anhui, China
| | - Linlin Dong
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, 233030, Anhui, China
| | - Xin Zhao
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, 233030, Anhui, China.
| | - Lingling Jiang
- School of Finance, Anhui University of Finance and Economics, Bengbu, 233030, Anhui, China
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5
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Chen S, Ding R, Shen S, Zhang B, Wang K, Yin J. Coordinated development of green finance and green technology innovation in China: from the perspective of network characteristics and prediction. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:10168-10183. [PMID: 37093384 DOI: 10.1007/s11356-023-27028-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 04/11/2023] [Indexed: 05/03/2023]
Abstract
Under the path of sustainable development, the key to achieving green and low-carbon transformation lies in green technology innovation (GTI), and how to effectively coordinate the relationship between green finance (GF) and GTI is an issue worth studying. This paper constructed an evaluation system of GF and GTI and combined them with the coupled coordination degree model to explore their coordination of Chinese provinces from 2012 to 2019. Then, the core network evolution and spatial structure characteristics of GTI and GF were studied using the modified gravity model. Finally, based on the link prediction, the general future network prediction is made to provide guidance and direction for the future GTI and GF development and construction. The results found that the coordination level between GF and GTI has been continuously improved from 0.356 to 0.436. The core network structure is keeping changing with their connection becoming more complex, and there is still room for optimization. Network centrality characteristics show that the spatial spillover effects are stronger in the more economically developed regions. The overall network possibility prediction shows the potential network connections in different urban agglomerations. This paper provides a certain reference role for China and developing countries to predict the GF and GTI cooperation network development in the future.
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Affiliation(s)
- Shihui Chen
- College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang, 550025, China
- Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guiyang, 550025, China
- Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang, 550025, China
| | - Rui Ding
- College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang, 550025, China.
- Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guiyang, 550025, China.
- Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang, 550025, China.
| | - Siwei Shen
- College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang, 550025, China
- Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guiyang, 550025, China
- Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang, 550025, China
| | - Bin Zhang
- College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang, 550025, China
- Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guiyang, 550025, China
- Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang, 550025, China
| | - Kexin Wang
- College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang, 550025, China
- Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guiyang, 550025, China
- Key Laboratory of Green Fintech, Guizhou University of Finance and Economics, Guiyang, 550025, China
| | - Jian Yin
- Center for China Western Modernization, Guizhou University of Finance and Economics, Guiyang, 550025, Guizhou, China
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6
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Zhou X, Hu X, Duan M, Peng L, Zhao X. Go for Economic Transformation and Development in China: Financial Development, Higher Education, and Green Technology Evolution. EVALUATION REVIEW 2024; 48:32-62. [PMID: 37022801 DOI: 10.1177/0193841x231166741] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Technology innovation is the key driving force in achieving economic transformation and development. Financial development and the expansion of higher education can promote technological progress primarily by easing financing constraints and improving the level of human capital. This study examines the impact of financial development and higher education expansion on green technology innovation. It conducts an empirical analysis by constructing a linear panel model and a nonlinear threshold model. The present study sample is based on the urban panel data of China from 2003-2019. (1) Financial development can significantly promote the expansion of higher education. (2) The expansion of higher education can improve energy and environment-based technological progress. (3) Financial development can both directly and indirectly promote green technology evolution by expanding higher education. The joint financial development and higher education expansion can significantly empower green technology innovation. (4) In the process of promoting green technology innovation, financial development has a non-linear influence on it, with higher education as the threshold. The effect of financial development on green technology innovation varies according to the degree of higher education. Based on these findings, we put forward policy proposals for green technology innovation to promote economic transformation and development in China.
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Affiliation(s)
- Xiaoxiao Zhou
- School of Finance, Anhui University of Finance and Economics, Bengbu Anhui, PR China
| | - Xinyue Hu
- School of Finance, Anhui University of Finance and Economics, Bengbu Anhui, PR China
| | - Mei Duan
- Book and Information Center, Anhui University of Finance and Economics, Bengbu Anhui, PR China
| | - Licheng Peng
- Financial Derivatives Department, China Industrial Securities Co., LTD, Shanghai PR China
| | - Xin Zhao
- School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, PR China
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7
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Yang R, Chen B, Wu J. Does digital economy curb carbon intensity? New insights from China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:123214-123225. [PMID: 37981605 DOI: 10.1007/s11356-023-30767-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 10/26/2023] [Indexed: 11/21/2023]
Abstract
China is in the period of vigorously developing the "digital economy" and "low-carbon economy," facing the double pressure of realizing the "dual-carbon" target and maintaining stable economic growth. This paper tests the role of the digital economy (DIEC) in the process of carbon emission reduction for the advancement of low carbon economy based on this issue from the perspective of carbon intensity (CI) by constructing a fixed effects and mediation effects model using data from 30 areas from 2011 to 2021. The study results show that at the national level, the advancement of DIEC significantly inhibits CI, and the conclusion still holds after various robustness tests. From the geographic region level, the suppression of CI by digital economic advancement has the most substantial impact in the central region. Although the eastern and western areas have similar results, the significance level is higher in the east region. When considering the economic development level, the impact of DIEC on CI is more significant in areas with lower economic development than those with higher economic growth. In analyzing the path of the DIEC affecting CI, it is found that the DIEC mainly inhibits CI by promoting technological advancement and reducing energy consumption intensity.
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Affiliation(s)
- Rui Yang
- School of Business, Xinjiang University, Urumqi, 830000, Xinjiang, China
| | - Bing Chen
- School of Economics and Management, Xinjiang University, Urumqi, 830000, Xinjiang, China.
| | - Jing Wu
- School of Economics and Management, Xinjiang University, Urumqi, 830000, Xinjiang, China
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8
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Wu X, Pan A. The impact of the digital economy on low-carbon innovation in the Yangtze River Delta region. PLoS One 2023; 18:e0293835. [PMID: 37922254 PMCID: PMC10624302 DOI: 10.1371/journal.pone.0293835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 10/18/2023] [Indexed: 11/05/2023] Open
Abstract
This study narrows its focus to the Yangtze River Delta, an important region in China known for its advancements in both digital economy and low-carbon technology. In contrast to previous studies, we also examine the heterogeneous effects between central and non-central cities, as well as the role of local financial development, when analyzing the impact of the digital economy on low-carbon innovation. Based on the data of 41 cities from 2011 to 2019, we find a significant direct promoting effect of the digital economy on low-carbon innovation. Furthermore, the development of the digital economy indirectly enhances low-carbon innovation through local financial development. The heterogeneous analysis reveals a positive impact of the digital economy on low-carbon innovation in both central and non-central cities, with a stronger effect observed in non-central cities. These findings suggest several policy recommendations, including promoting digital economy and finance, green finance, and fostering regional integration in the Yangtze River Delta.
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Affiliation(s)
- Xiaoli Wu
- Business School, Shaoxing University, Shaoxing, Zhejiang, China
| | - An Pan
- School of Economics, Zhongnan University of Economics and Law, Wuhan, Hubei, China
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9
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Li Z, Xinlan C, Yixuan M, Guangming Y. Coupling coordination evaluation and driving path of digital economy and carbon emission efficiency in China: A fuzzy-set qualitative comparative analysis based on 30 provinces. PLoS One 2023; 18:e0287819. [PMID: 37883359 PMCID: PMC10602363 DOI: 10.1371/journal.pone.0287819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 06/13/2023] [Indexed: 10/28/2023] Open
Abstract
Enhancing the level of coupling coordination between the digital economy (DIE) and carbon emission efficiency (CEE) is not only an inevitable choice for achieving the goals of energy conservation and emission reduction and promoting green development in China, but also a key path to implementing China's "Double Carbon" strategy. Based on the relevant statistical data of 30 provincial-level regions in China from the period covering 2011 to 2019, this paper empirically analyzed the coupling coordination between the DIE and CEE and its influencing factors. In this study, an improved coupling coordination degree (CCD) model was used to evaluate the degree of the coupling and coordinated development of the DIE and CEE in provincial regions of China. Finally, based on the Technology-Organization-Environment (TOE) framework, a fuzzy-set qualitative comparative analysis (fsQCA) method was employed to identify the realization path of the coupling and coordinated development of the DIE and CEE from the perspective of configuration. The results demonstrated that the coupling coordination between the DIE and CCE in China demonstrated a gradual upward trend, and exhibited regional differences, showing a decreasing trend of east > middle > west. Regarding the influencing factors, no single influencing factor could act as a necessary condition for the high CCD, the coupling and coordinated development of the DIE and CEE is a multifactorial synergy. There were five paths for the high degree of coupling coordination between the DIE and CEE, which were divided into three types: organization-environment-led type, environment-led type, and technology-organization-led type. Furthermore, technological innovation level and industrial structure could substitute for one another in some conditions, and environmental regulation and economic development level were synchronized. These conclusions provide a theoretical basis for countries to formulate policies to promote the coupling and coordinated development of their DIE and CEE.
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Affiliation(s)
- Zhou Li
- School of Business Administration, Chongqing Technology and Business University, Chongqing, China
| | - Chen Xinlan
- School of Business Administration, Chongqing Technology and Business University, Chongqing, China
| | - Mi Yixuan
- School of Business Administration, Chongqing Technology and Business University, Chongqing, China
| | - Yang Guangming
- School of Management, Chongqing University of Technology, Chongqing, China
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10
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Li M, Hu J, Liu P, Chen J. How can digital finance boost enterprises' high-quality development?: evidence from China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:88876-88890. [PMID: 37440136 DOI: 10.1007/s11356-023-28519-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 06/27/2023] [Indexed: 07/14/2023]
Abstract
As a new industry derived from the traditional financial system and enhanced by emerging technologies, digital finance is significant in microenterprise development. Based on the 2011-2018 Digital Inclusive Finance Index of Peking University, we examine the mechanism-inventory optimization and incremental innovation. We use the data of small and medium-sized enterprises to reveal the effect of digital finance-mismatch correction and defect improvement. The study results show that digital financing significantly improves enterprises' high-quality development. Further research has revealed that digital finance can effectively correct scale, attribute, phase, and industry mismatches. Digital finance alleviates financing constraints, solves the expensive financing problem, and pushes enterprises to deleverage in the economic development process. However, digital finance is still limited for companies with high financing constraints and leverage. Moreover, financial regulation can significantly improve the economic performance of digital finance. The findings provide reliable empirical evidence and policy inspiration for promoting digital finance development, deepening the supply-side structural reform of finance, better serving the real economy, and achieving high-quality economic development.
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Affiliation(s)
- Mingrui Li
- School of Economics, Jinan University, Guangzhou, 510632, China
| | - Jin Hu
- School of Big Data Application and Economics, Guizhou University of Finance and Economics, Guiyang, 550025, China
| | - Pengzhen Liu
- School of Economics, Jinan University, Guangzhou, 510632, China
| | - Jiayu Chen
- School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
- Ji Yang College of Zhe Jiang A&F University, Zhuji, 311800, China.
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11
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Yao F, Song Y, Xue L. Study on the effect of green financial policies on low-carbon economic development based on evidence from green financial reform and innovation pilot zone. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27658-y. [PMID: 37231135 DOI: 10.1007/s11356-023-27658-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/11/2023] [Indexed: 05/27/2023]
Abstract
Green finance is key in supporting industries' green transformation and helping achieve low-carbon economic (LCE) development. This paper constructs an LCE development index using panel data from 30 provinces in China from 2011 to 2020. Based on the establishment of the first five pilot green finance zones in China in 2017 as a quasi-natural experiment, the synthetic control method (SCM) is applied to explore the impact of green finance policies on the level of LCE development and to analyze the mechanism and evaluate the policy effects. The empirical results show that (1) the synthetic analysis unit better fits the development trend before the implementation of the pilot. (2) After the implementation of the pilot reform, the level of LCE development in Zhejiang, Jiangxi, Guangdong, and Guizhou provinces has a more significant enhancement effect, but the enhancement in Xinjiang is not significant, which indicates that the reform effect in Zhejiang, Jiangxi, Guangdong, and Guizhou is significantly better than that in Xinjiang to a certain extent. (3) The samples were statistically significant and passed the placebo and ranking tests. Additionally, this paper analyzes the mechanism of policy effectiveness in terms of sci-tech innovation (STI) and energy consumption structure: green finance as a grip for economic transformation can provide financial support for regional STI and energy consumption structure upgrade and promote the capital flow to green low-energy industries, ultimately achieving sustainable economic development. Based on the above findings, policy insights can be provided for the improvement of green finance pilot regions.
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Affiliation(s)
- Fengge Yao
- School of Finance, Harbin University of Commerce, Harbin, Heilongjiang, China
| | - Ying Song
- School of Finance, Harbin University of Commerce, Harbin, Heilongjiang, China
| | - Liqing Xue
- School of Finance, Harbin University of Commerce, Harbin, Heilongjiang, China.
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12
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Zhang J, Huang R, He S. How does technological innovation affect carbon emission efficiency in the Yellow River Economic Belt: the moderating role of government support and marketization. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:63864-63881. [PMID: 37059949 DOI: 10.1007/s11356-023-26755-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/25/2023] [Indexed: 04/16/2023]
Abstract
The Yellow River Economic Belt (YREB) is a fundamental ecological protection barrier for China. Its carbon pollution issues are currently severe owing to the extensive energy consumption and unsatisfactory industrial constructions. In this context, this paper estimates carbon emission efficiency (CEE) based on the panel data from 56 cities in the YREB during the period 2006-2019 and analyzes its spatial distribution characteristics. Additionally, the spatial Durbin model (SDM) is utilized to examine the effect of technological innovation (TI) on CEE as a result of the moderating effects of government support (GS) and marketization (MA), respectively. The results indicated that (i) in the YREB, CEE exhibited significant spatial autocorrelation characteristics; (ii) TI negatively affected local CEE; (iii) the moderating effect of local GS on the relationship between TI and CEE in the local area was negative, but its spatial spillover effect was still not significant; (iv) the moderating effect of local MA on the relationship between TI and CEE in the local area was also negative, but positive in the surrounding areas. Based on the empirical analysis, a series of policy suggestions are proposed to improve the YREB's CEE.
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Affiliation(s)
- Jingxue Zhang
- Business School, Zhengzhou University, Zhengzhou, 450001, People's Republic of China
| | - Rongbing Huang
- Accounting School, Zhejiang Gongshang University, Hangzhou, 310018, People's Republic of China.
| | - Siqi He
- Business School, Zhengzhou University, Zhengzhou, 450001, People's Republic of China
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13
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Gao J, Wu D, Xiao Q, Randhawa A, Liu Q, Zhang T. Green finance, environmental pollution and high-quality economic development-a study based on China's provincial panel data. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:31954-31976. [PMID: 36456678 DOI: 10.1007/s11356-022-24428-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
Under the new normal, green finance is inevitably linked to high-quality economic development in China. Based on 30 province panel data sets from China from 2010 to 2019, this research employs an innovative spatial econometric model to integrate green finance, environmental pollution and high-quality economic development into a unified empirical analysis framework. Regional green finance and high-quality economic development have spatial spillover effects in China, according to spatial auto-regressive and spatial error model tests, with the eastern region leading, the central region running in parallel and the western region chasing, because of a strong moderating effect in the eastern region. Green finance contributes greatly to high-quality economic development, but increased environmental pollution impedes high-quality economic development. Green financing can help to mitigate the detrimental effects of pollution on high-quality economic development. According to the mechanism of action analysis, green finance reduces pollution by modifying the industrial structure and boosting scientific and technological growth. Finally, the green finance threshold test demonstrates a nonlinear impact on economic quality development after passing a specified threshold value and has a strong threshold characteristic. This research has policy implications since it improves understanding of the dynamics of high-quality economic development as well as the benefits, mechanisms and heterogeneity of green finance in reducing pollution and empowering high-quality economic development.
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Affiliation(s)
- Jing Gao
- School of Business, Nanjing Normal University, Nanjing, 210000, China.
- Finance Office, Jiangsu Normal University, Xuzhou, 221116, China.
| | - Dailong Wu
- School of Business, Nanjing Normal University, Nanjing, 210000, China
| | - Quan Xiao
- School of Business, Nanjing Normal University, Nanjing, 210000, China
| | - AbidAli Randhawa
- School of Business, Nanjing Normal University, Nanjing, 210000, China
| | - Qiang Liu
- School of Business, Jiangsu Ocean University, Lianyungang, 222006, China
| | - Teng Zhang
- School of Business, Nanjing Normal University, Nanjing, 210000, China
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Chen L, Huang J. Study on the Interaction Effect between the Intensity of Government Low-Carbon Subsidies and the Growth Ability of Green and Low-Carbon Emerging Enterprises. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2438. [PMID: 36767804 PMCID: PMC9916363 DOI: 10.3390/ijerph20032438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 12/16/2022] [Accepted: 12/21/2022] [Indexed: 06/18/2023]
Abstract
With the development of science and technology and society, people's demand for a healthy living environment is increasing, and the expression "low carbon" has become a daily feature of people's lives. The emergence of a low-carbon economy, the impact on the traditional industrial structure and the formation of a new economic landscape make China, a developing country, eager to seize this opportunity to enhance its international competitiveness. To achieve this, it is necessary to establish a low-carbon concept, to actively restructure industrial and develop low-carbon industries; only in this way can we take advantage of the new round of industrial restructuring and grasp the initiative of development. Therefore, this paper selects data from enterprises in the emerging low-carbon industry, and uses a SVAR model to conduct a dynamic interaction analysis between government subsidy intensity, enterprise profitability, asset growth capacity and enterprise size. The results of the study show that the intensity of government subsidies in the first period has a certain positive effect on a company's current profitability and asset growth, the improvement being most significant on its profitability. Among the larger companies, asset growth and profitability in the first period had a significant positive impact on current earnings, and the contribution of profitability to the company's own performance was much larger than the average; among the smaller companies, asset growth and profitability in the first period had a significant positive impact on current earnings, and the contribution of asset growth to the company's own performance was much larger than the average. The intensity of prior government subsidies in the Highs group has a significant positive relationship with the intensity of current government subsidies, the firm's asset growth capacity and profitability; the intensity of prior government subsidies in the Lows group only has a significant positive impact on the asset growth capacity in the current period. In addition, the interaction between the three core variables in the Highs group is also significantly higher than that in the Lows group. This indicates that the government should implement differential policies and financial subsidies according to the actual needs of enterprises to maximize the effect of capital use and promote the development and growth of emerging enterprises.
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Affiliation(s)
- Lixia Chen
- School of Marxism, Hefei Normal University, Hefei 230601, China
| | - Jianyuan Huang
- School of Public Administration, Hohai University, Nanjing 210098, China
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Shen B, Yang X, Xu Y, Ge W, Liu G, Su X, Zhao S, Dagestani AA, Ran Q. Can carbon emission trading pilot policy drive industrial structure low-carbon restructuring: new evidence from China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:41553-41569. [PMID: 36633739 DOI: 10.1007/s11356-023-25169-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 01/02/2023] [Indexed: 01/13/2023]
Abstract
Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals.
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Affiliation(s)
- Bing Shen
- School of Economics and Management, Xinjiang University, Urumqi, 830047, China
- College of Finance and Taxation, Xinjiang University of Finance & Economics, Urumqi, 830047, China
| | - Xiaodong Yang
- School of Economics and Management, Xinjiang University, Urumqi, 830047, China
| | - Yang Xu
- School of Economics and Management, Xinjiang University, Urumqi, 830047, China
| | - Wenfeng Ge
- School of Economics and Management, Xinjiang University, Urumqi, 830047, China
| | - Guangliang Liu
- School of Economics and Management, Xinjiang University, Urumqi, 830047, China
| | - Xufeng Su
- School of Economics and Management, Xinjiang University, Urumqi, 830047, China
| | - Shikuan Zhao
- School of Public Administration, Chongqing University, Chongqing, 400000, China
| | | | - Qiying Ran
- Shanghai Business School, 200235, Shanghai, China.
- Center for Innovation Management Research of Xinjiang, Xinjiang University, 830047, Urumqi, China.
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