Provincial Level In China Research Articles

How does technological progress affect provincial financial resilience? Evidence at the provincial level in China

The ever-changing global economy and sudden global public health events have posed challenges to financial resilience worldwide. As its important role in maintaining domestic economic stability, safeguarding national security, and enhancing international status, financial resilience has long been widely studied. However, few studies have empirically explored how technological progress affects financial resilience. Based on data from 30 provinces in China, this study adopts a panel two-way fixed effect model to identify the impact of technological progress on financial resilience and the underlying mechanisms. Results show that technological progress can significantly enhance financial resilience, and this impact is stronger in provinces with large population size, high employment proportion in the tertiary sector, high social consumption capacity, and provinces located in Central China. Further, technological progress have a positive impact on financial resilience through increased asset liquidity and government intervention.

The comparison of spatial patterns and factors associated with healthcare provider knowledge in palliative care in various regions of China

As an integral part of the overall life cycle, it is crucial to ensure equity and accessibility to palliative care services at the end of life. The knowledge of healthcare providers has a significant beneficial impact on the quality of palliative care services. This study aimed to compare the nationwide geographic distribution of healthcare providers’ knowledge of palliative care at the provincial level in China and identify the possible factors associated with its geographic disparities. A descriptive cross-sectional study was conducted in all provinces (n = 29) that implemented palliative care pilot programs in China. Data were collected online using a structured questionnaire. The possible factors associated with healthcare providers’ knowledge including economy, demographics, and health, were explored by using exploratory regression and ordinary least squares. In addition, spatial autocorrelation was also examined with Moran’s I, LISA, and Geographically Weighted Regression. A total of 18,272 participants from 903 health institutions in 87 palliative care pilot cities were included across 29 out of 31 provinces in China. The average knowledge score (mean ± standard deviation [SD]) was 8.61 ± 2.85. A positive spatial correlation was observed in healthcare providers’ palliative care knowledge level in China. The high level of knowledge was significantly associated with fewer hospitals per 10,000 population (β = −0.384, 95% CI: −0.601 to −0.168, p = 0.001), more primary healthcare institutions per 10,000 population (β = 0.220, 95% CI: 0.032–0.407, p = 0.024), and more community health center visits (β = 0.259, 95% CI: 0.054–0.465, p = 0.016), with higher coefficients being observed in the northwest and northeast regions. This study suggested that the knowledge level of palliative care among healthcare providers nationwide was relatively low, indicating the existence of a disparity between the supply and demand of palliative care services. There may be regional disparities in palliative care services based on the substantial geographical variation in healthcare provider knowledge, emphasizing the necessity of tailored interventions targeting areas with the greatest need.

Green finance reform and application intensity of chemical fertilizer and pesticide: policy evidence from China.

The environmental hazards resulting from the excessive application of pesticides and fertilizers have been an inevitable agricultural production issue in various countries around the world. New technologies and policies are constantly trying to improve their application efficiency. This paper utilizes panel data of the provincial level in China from 2009 to 2019 to empirically study the effect of green finance reform policies on the chemical fertilizer application intensity (FAI) and pesticide application intensity (PAI). Standard difference-in-differences (DID), synthetic DID, difference-in-difference-in differences (DDD), and spatial DID models are constructed for specific empirical analysis. The findings can be concluded as follows: (1) A unit of the green finance reform policy reduces FAI by 0.0144 and PAI by 1.7921 by promoting green technology innovation. (2) Government financial extractive capacity hinders the reduction effect of green finance on PAI. (3) Coastal geographical location is conducive to reducing PAI through green finance reform. (4) FAI and PAI show positive spatial autocorrelations, and the influence of green finance reform overflows to surrounding areas. The research results can provide policy references for countries around the world to promote the green development of agriculture and reduce environmental pollution.

Construction and evolutionary factors of spatial correlation network of China's provincial tourism resource conversion efficiency

Research objectiveTo explore the spatial correlation network characteristics and formation mechanisms of tourism resource conversion efficiency, and provide reference for the collaborative improvement of tourism resource conversion efficiency at the provincial level in China. Research methodsNon parametric SBM efficiency measurement method and social network analysis method. Research hypothesis: The spatial network correlation characteristics of tourism resource conversion efficiency are obvious, and regional connections are close. Research findings(i) during the research period, the spatial connection strength of China's tourism resource conversion efficiency continued to increase and the spatial network structure of tourism resource conversion efficiency tended to become more complex and significantly more stable. (ii) A spatially linked network with a stable tourism resource conversion efficiency structure formed in China. The number of network relations and density of the network fluctuated and increased, while the network efficiency continued to decrease; however, a strong small-world nature was observed. (iii) The economic development level difference matrix, tourism industry agglomeration difference matrix, human capital difference matrix, and marketization degree difference matrix significantly and positively affected spatial association relationship establishment, while the provincial adjacency matrix significantly and negatively affected such relationships.

The Impact of Fiscal and Environmental Protection Budget on Ecological Protection and its Mechanism

This paper uses data from 30 provincial levels in China from 2014 to 2021 to empirically test the impact and mechanism of fiscal and environmental protection budgets on ecological protection. The results show that: (1) government budget expenditure has an enabling effect on ecological protection; (2) The comprehensive environmental situation plays a positive role in the fiscal and environmental protection budget to empower ecological protection; (3) The fiscal and environmental protection budgets of provinces in the eastern and central regions have a significant enabling effect on ecological protection, while the enabling role in the western region is weakened.

The trajectory of carbon emissions and terrestrial carbon sinks at the provincial level in China

Global greenhouse gas emission, major factor driving climate change, has been increasing since nineteenth century. STIRPAT and CEVSA models were performed to estimate the carbon emission peaks and terrestrial ecosystem carbon sinks at the provincial level in China, respectively. Utilizing the growth characteristics and the peak time criteria for the period 1997–2019, the patterns of energy consumption and CO2 emissions from 30 Chinese provinces are categorized into four groups: (i) one-stage increase (5 provinces), (ii) two-stage increase (10 provinces), (iii) maximum around 2013 (13 provinces), and (iv) maximum around 2017 (2 provinces). According to the STIRPAT model, the anticipated time of peak CO2 emissions for Beijing from the third group is ~ 2025 in both business-as-usual and high-speed scenarios. For Xinjiang Uygur autonomous region from the first group and Zhejiang province from the second group, the expected peak time is 2025 to 2030. Shaanxi province from the fourth group is likely to reach carbon emission peak before 2030. The inventory-based estimate of China’s terrestrial carbon sink is ~ 266.2 Tg C/a during the period 1982–2015, offsetting 18.3% of contemporary CO2 emissions. The province-level CO2 emissions, peak emissions and terrestrial carbon sinks estimates presented here are significant for those concerned with carbon neutrality.

Spatio-temporal characteristics and influencing factors of land disputes in China: Do socio-economic factors matter?

Land disputes pose significant challenges to social stability and development. In this paper, land dispute intensity (LDI) is measured at the provincial level in China from 2009 to 2018 and its spatiotemporal evolution characteristics and influencing factors are explored. The ordinary least squares(OLS), spatial durbin model (SDM), geodetector model, and panel threshold model are used to explore the spatial spillover effects of LDI and its potential non-linear relationship with socio-economic factors. The results reveal that LDI is spatially distributed in a decentralized form, with local areas showing the structural characteristics of “single core, multiple clusters”. The LDI exhibits a significant positive spatial autocorrelation and follows a “logarithmic” upward trend over time. The urbanization rate (UR), social security expenditures (SSE), and the number of land and resources institutions (NLRI) are important driving forces affecting LDI. The SSE and NLRI have a single threshold effect on the LDI, with a “V” shaped weakening trend, and the UR is an important factor causing nonlinear effects. Interestingly, the effect shifts from inhibition to stimulation when the SSE and NLRI cross the corresponding threshold value. This paper can provide new insights into the governance of land disputes.

Detecting regional unevenness and influencing factors of ecological resilience in China

Existing research on the state transition process of ecological resilience (ER) has neglected the ultimate goal of enhancing well-being and lacks theoretical framework support. To address these issues, we have innovatively developed a three-dimensional analysis framework of “resistant, absorptive, and restorative capacity” to measure ER. We also explored the regional unevenness and factors influencing ER at the provincial level in China through spatiotemporal evolution analysis and GeoDetector models. The results indicate that: the ecological resilience of Chinese provinces ranges from 0.415 to 0.596, with all provinces falling into the risk or good areas. Furthermore, a fluctuating and increasing trend is observed. The eastern coastal provinces, such as Beijing and Shandong, comprise predominantly good areas of ecological resilience that are distributed in a band manner, while the western provinces, notably Xinjiang, comprise primarily risk areas distributed in a clustered pattern. The per capita electricity consumption, per capita GDP, and patent applications in high-tech industries are identified as the primary factors influencing the spatiotemporal heterogeneity of ecological resilience, and the interaction effects of each factor have synergistic enhancement effects. Spatial ecological resilience displays certain degrees of “nonhomogeneous” agglomeration and spatial heterogeneity. However, no apparent spatial polarization phenomenon is observed. These findings provide valuable insights for cities aiming to address ecological risks and enhance urban resilience.

Factors affecting the incidence of pulmonary tuberculosis based on the GTWR model in China, 2004-2021.

Contra-posing panel data on the incidence of pulmonary tuberculosis (PTB) at the provincial level in China through the years of 2004-2021 and introducing a geographically and temporally weighted regression (GTWR) model were used to explore the effect of various factors on the incidence of PTB from the perspective of spatial heterogeneity. The principal component analysis (PCA) was used to extract the main information from twenty-two indexes under six macro-factors. The main influencing factors were determined by the Spearman correlation and multi-collinearity tests. After fitting different models, the GTWR model was used to analyse and obtain the distribution changes of regression coefficients. Six macro-factors and incidence of PTB were both correlated, and there was no collinearity between the variables. The fitting effect of the GTWR model was better than ordinary least-squares (OLS) and geographically weighted regression (GWR) models. The incidence of PTB in China was mainly affected by six macro-factors, namely medicine and health, transportation, environment, economy, disease, and educational quality. The influence degree showed an unbalanced trend in the spatial and temporal distribution.

Study on regional carbon quota allocation at provincial level in China from the perspective of carbon peak

This paper constructs a carbon quota allocation index that takes into account equity, efficiency and ecological construction, and calculates carbon emissions and energy consumption data in important periods based on the expected carbon emission targets and economic and social development indicators of the Chinese government. Based on the calculated carbon emissions, the zero-sum game data Envelopment model (ZSG-DEA) is used to discuss the initial allocation of regional quotas and the optimal carbon quota scheme. The results show that:(1) there is a large gap between the optimal carbon quota and the initial carbon quota allocation in Shandong, Guangdong, Jiangsu and other provinces in 2025, and the implementation of emission reduction measures should be accelerated. (2) By 2030, the final allocation of Beijing, Tianjin, Inner Mongolia, Qinghai, Shanghai, Ningxia, Liaoning and Xinjiang will be positive. The provinces with negative final allocation should carry out the work of carbon peak as soon as possible to avoid increasing the pressure of emission reduction in the future. (3) The central region faces greater pressure of emission reduction, while the western region can accept the transfer of carbon emissions from other regions over time. The research conclusions have important policy implications for establishing a fair and effective carbon quota allocation mechanism, achieving the national total carbon emission control target, stimulating the vitality of the unified carbon market, and promoting regional coordinated emission reduction.

Water Footprint of Animal Breeding Industry and Driving Forces at Provincial Level in China

Agriculture significantly contributes to the global water footprint (WF) with the animal breeding industry accounting for over 33% of agricultural water consumption. Since 2000, rapid development in animal breeding has intensified the pressure on water resources. Forecasts indicate a projected 70% increase in freshwater usage in the meat industry by 2025 compared to 2000, particularly in developing countries, such as China, yet comprehensive studies regarding China’s animal breeding industry WF remain limited. This study aimed to assess the variations in the green, blue, and gray WF of pork, beef, milk, eggs, and chicken meat across 31 provinces in China from 2000 to 2017. Additionally, a driving force analysis using the Kaya equation and LMDI method was conducted. Findings revealed that the total WF of animal products increased from 1049.67 Gm3 (in 2000) to 1385.05 Gm3 (in 2017) in China, and pork exhibited a significantly higher WF compared to other animal products, contributing 64.49% to China’s total animal product WF. The sharp rise in the green WF demonstrated regional disparities in water consumption efficiency within the animal breeding industry. The increase in the blue WF was associated with rising livestock numbers and China’s efforts to conserve water. The increase in the gray WF indicated that increased consumption of animal products heightened wastewater treatment pressures, particularly in economically developed provinces. The augmentation in China’s animal product WF was primarily influenced by policy and economic effects, with increased agricultural equipment funding and enhanced production efficiency identified as effective strategies for WF reduction. This study suggests that the promotion of technology, combined with scientific policies, can alleviate the pressure on water resources in the animal breeding industry in developing countries.

The Dynamics of Interorganizational Collaboration in Disaster Management: A Network Study Based on Flood Disasters in China

Interorganizational collaboration networks have become an important tool for disaster management. However, research on how different organizations can effectively collaborate throughout the entire disaster management process in centralized states such as China is scarce. This study begins to fill this lacuna by investigating interorganizational collaboration in different phases of disaster management and analyzing changes in the structure of the networks constructed during the preparedness and response phases of the 2020 flood disaster in Hubei Province, China. Building on the complex adaptive systems (CAS) theory, we argue that interorganizational collaboration changes dynamically according to its tasks and requirements. In the preparedness phase, interorganizational collaborations primarily follow established plans and choose horizontal self-organized collaboration mechanisms. However, when the urgent information and resource requirements increase in the response phase, many organizations choose vertical mandatory collaboration mechanisms. We found that organizations at the central and provincial levels in China were well positioned to coordinate information and resources and strengthen the interorganizational collaboration and communication that is crucial in disaster management. These findings contribute to the study of interorganizational collaboration networks in disaster management.

The mortality and years of life lost for community-acquired pneumonia before and during COVID-19 pandemic in China

Community-acquired pneumonia (CAP) is a leading cause of mortality worldwide, but disease burden of CAP is not clear so far. We aim to explore the spatial and temporal trends of mortality and years of life lost (YLL) due to CAP during 2013-2021 in mainland China, especially the mortality changes before and during COVID-19 pandemic due to COVID-19 related non-pharmaceutical interventions (NPIs). We used data from the National Mortality Surveillance System to estimate the age-standardized rates of death and YLL of CAP at national and provincial level in China during 2013-2021. Monthly and provincial NPIs data were obtained from Oxford COVID-19 Government Response Tracker. The Average annual percentage change (AAPC) and mortality reduction were estimated by log-linear regression and interrupted time series, respectively. In China, most CAP that caused deaths had no clear etiology, and bacterial pneumonia and viral pneumonia were the leading 2 causes among CAP deaths with determined etiology before and during COVID-19 pandemic. The age-standardized CAP mortality rate decreased from 11.18 per 100,000 in 2013 to 8.76 per 100,000 in 2019, and to 5.74 per 100,000 in 2021 (AAPC-4.51% vs-7.89%). Trends were similar in age-standardized rate of YLL. Both rates declined more for viral pneumonia, compared with bacterial pneumonia. After adjusting for NPIs at provincial level after 2020, the NPIs for COVID-19 was associated with significant reductions in CAP mortality (-0.34 per 100,000,-0.41 to-0.27; p<0.0001), and provinces that economically developed and conducted strict regular NPIs against COVID-19 contributed the most reduction. We observed a decreasing trend of age-standardized CAP mortality from 2013 to 2019, and a dramatical reduction during COVID-19 pandemic, especially for viral pneumonia. Our study provided the evidence for the effectiveness of regular NPIs on the significant reductions in CAP mortality. This work has been supported by Beijing Municipal Science and Technology Project Z191100006619101, Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (CIFMS 2021-I2M-1-048), CAMS Institute of Respiratory Medicine Grant for Young Scholars (2023-ZF-8) and the New Cornerstone Science Foundation.

Equilibrium price estimation of green bonds from the perspective of resource allocation.

Green bonds offer substantial positive externalities compared to other types of bonds. This leads to a resource distribution efficiency that falls below the optimal level dictated by Pareto efficiency. It becomes essential to determine a means by which green bonds can achieve an equilibrium price, ensuring optimal public resource allocation and maximized social welfare. From the perspective of externalities, this study employs the carbon shadow price (CSP) to determine the equilibrium price of carbon emissions. Subsequently, this value aids in estimating the equilibrium price of green bonds. Firstly, we introduced an optimized bootstrap method to estimate the bias-corrected CSP at the provincial level in China from 2007 to 2020. Then, a pricing framework is developed, integrating both the carbon trading price and the estimated CSP, to determine the green bond's equilibrium price. Numerical simulations indicate that, under current conditions, green bonds cannot achieve the equilibrium price by relying solely on the carbon trading mechanism. Therefore, further development of China's carbon emissions trading market is required.

Study of the Spatio-Temporal Variation of Agricultural Sustainability at National and Provincial Levels in China

As an important pillar of human civilization, the development of agriculture has gradually become the focus of the international community to solve the development dilemma and promote the implementation of the global Sustainable Development Goals (SDGs). Agricultural sustainability issues are widely addressed in scientific literature and various reports by international organizations. However, there are some problems in the existing studies, such as the design of agricultural sustainable development evaluation indicators does not consider the differences in development stages and data statistical capacity of various countries, and the research depth of spatial and temporal change of agricultural sustainable development is insufficient. Agriculture has become a bottleneck for the world and China to achieve the SDGs. Based on the global indicator framework of the Sustainable Development Goals and comprehensive consideration of agricultural development common problems and regional characteristics, this work has established a basic index library consisting of 86 indicators to evaluate the agricultural sustainable development in China and provide the basis for the assessment in different regions. In the indicator optimization process, having considered the development stage of China, the basic characteristics of agriculture, data availability, and reliability, we determined an evaluation index system of China’s agricultural sustainable development that includes 25 specific indicators. The constant elasticity of substitution (CES) model was used to assess the temporal and spatial changes in agricultural sustainability in China at the national, regional, and provincial levels. The results showed that China’s Agricultural Sustainable Development Index (ASDI) score increased from 44.76 in 2011 to 59.22 in 2021, and the ASDI scores of all agricultural regions and provinces also increased to varying degrees. In terms of goal scores, SDG2, SDG6, SDG7, SDG8, SDG9, and SDG12 all exhibited an overall upward trend, in which SDG6 performed the best, and SDG2 performed the worst, scoring 84.76 and 43.05 in 2021, respectively. This paper will provide a basis for systematically evaluating the progress of agricultural sustainable development goals and accurately identifying unsustainable problems in agricultural development to help China implement the 2030 Agenda for Sustainable Development.

Research on the green innovation promoted by environmental vertical management reform: evidence from green patents of Chinese listed companies

ABSTRACT The environmental vertical management reform (EVMR) below the provincial level in China is an important driving force for enterprise green innovation. This article employs a progressive double-difference method to test the green innovation performance of enterprises in pilot areas relative to non-pilot areas before and after the implementation of the reform, to analyse its impact on green innovation. The findings of the article indicate that: (1) EVMR can significantly promote enterprise green innovation. This conclusion still holds after controlling for endogeneity and conducting other robustness tests. (2) In terms of the mechanism, EVMR primarily promotes green innovation by improving the supervisory capacity of provincial-level environmental protection departments, the enforcement capacity of grassroots environmental protection departments, and the incentives and supervision for managers from shareholders in enterprises. (3) Heterogeneity results show that the EVMR has a more significant promoting effect on enterprise green innovation in regions with lower degree of marketization and less emphasis on the environment.

The burden of disease attributable to indoor air pollutants in China from 2000 to 2017

High-level exposure to indoor air pollutants (IAPs) and their corresponding adverse health effects have become a public concern in China in the past 10 years. However, neither national nor provincial level burden of disease attributable to multiple IAPs has been reported for China. This is the first study to estimate and rank the annual burden of disease and the financial costs attributable to targeted residential IAPs at the national and provincial level in China from 2000 to 2017. We first did a systematic review and meta-analysis of 117 articles from 37 231 articles identified in major databases, and obtained exposure-response relationships for the candidate IAPs. The exposure levels to these IAPs were then collected by another systematic review of 1864 articles selected from 52 351 articles. After the systematic review, ten IAPs with significant and robust exposure-response relationships and sufficient exposure data were finally targeted: PM2·5, nitrogen dioxide, sulphur dioxide, ozone, carbon monoxide, radon, formaldehyde, benzene, toluene, and p-dichlorobenzene. The annual exposure levels in residences were then evaluated in all 31 provinces in mainland China continuously from 2000 to 2017, using the spatiotemporal Gaussian process regression model to analyse indoor originating IAPs, and the infiltration factor method to analyse outdoor originating IAPs. The disability-adjusted life-years (DALYs) attributable to the targeted IAPs were estimated at both national and provincial levels in China, using the population attributable fraction method. Financial costs were estimated by an adapted human capital approach. From 2000 to 2017, annual DALYs attributable to the ten IAPs in mainland China decreased from 4620 (95% CI 4070-5040) to 3700 (3210-4090) per 100 000. Nevertheless, in 2017, IAPs still ranked third among all risk factors, and their DALYs and financial costs accounted for 14·1% (95% CI 12·3-15·6) of total DALYs and 3·45% (3·01-3·82) of the gross domestic product. Specifically, the rank of ten targeted IAPs in order of their contribution to DALYs in 2017 was PM2·5, carbon monoxide, radon, benzene, nitrogen dioxide, ozone, sulphur dioxide, formaldehyde, toluene, and p-dichlorobenzene. The DALYs attributable to IAPs were 9·50% higher than those attributable to outdoor air pollution in 2017. For the leading IAP, PM2·5, the DALYs attributable to indoor origins are 18·3% higher than those of outdoor origins. DALYs attributed to IAPs in China have decreased by 20·0% over the past two decades. Even so, they are still much higher than those in the USA and European countries. This study can provide a basis for determining which IAPs to target in various indoor air quality standards and for estimating the health and economic benefits of various indoor air quality control approaches, which will help to reduce the adverse health effects of IAPs in China. The National Key Research and Development Program of China and the National Natural Science Foundation of China.

Research on the income distribution effect of factor allocation efficiency changes among China's three major industries.

This paper aims to study the impact of correcting the factor misallocation among China's three major industries on China's income gap and income distribution pattern. By using the industry Panel data at the provincial level in China, we measure the degree of factor misallocation among the three major industries in China's provinces from 2002 to 2019 by building a factor misallocation measurement model, and then uses reverse thinking to compare the income gap under the condition of no factor misallocation with the actual income gap, and then obtains the impact of factor misallocation on the income gap, And use this method to focus on analyzing the impact of factor allocation efficiency changes among the three industries on income distribution pattern. The research finds that: (1) There is a serious factor misallocation among the three major industries in each province. From the perspective of subdivided factors, the factor misallocation among the three major industries in China's provinces is mainly caused by labor misallocation. Factor misallocation shows a trend of convergence first and then divergence among regions. (2) There is a strong heterogeneity in the explanatory power of different dimensions of the income gap of factor misallocation among the three major industries in China's provinces. Among them, correcting the misallocation of total factors among the three major industries in China's provinces can only narrow the internal income gap of the tertiary sector of the economy, and expand the internal income gap between the primary and secondary industries. (3) The impact of correcting the total misallocation, capital misallocation and labor misallocation among the three industries on the income gap among industries or provinces is narrowing first and then expanding. (4) Further research shows that although the level of factor misallocation among provinces in China is significantly lower than the average level of factor misallocation among the three major industries within each province, it has a stronger explanatory power for the inter-provincial income gap. Correcting the total factor misallocation and labor misallocation among provinces can significantly reduce the inter-provincial income gap in China. Correcting the total factor misallocation and labor misallocation among provinces in 2019 can reduce the inter-provincial income gap by 51.48% and 81.68% respectively. Only correcting the capital misallocation among provinces will expand the inter-provincial income gap, and only correcting the capital misallocation among provinces in 2019 will expand the inter-provincial income gap by 112.21%.

Has the Development of The Digital Economy Reduced the Growth Rate of Carbon Emissions?

Against the backdrop of the "30 · 60" dual carbon target, low-carbon development and the progress of the digital economy are the focus of attention at home and abroad. The digital economy has become an important driving force for high-quality economic development in China. This article studies panel data at the provincial level in China from 2011 to 2018, empirically testing the negative correlation between the development of the digital economy and the growth rate of carbon emissions, and verifying the mechanism effect of green technology innovation, Finally, the situation in the eastern, central, and western regions was discussed through sample analysis and robustness testing was conducted. Based on the above research conclusions, the following insights can be drawn: firstly, improve the speed and quality of digital economy development; Secondly, focus on the development of green innovative technologies.

How to achieve the common developments of green finance and clean energy in China? Evidence from coupling coordination evaluation

Investigating the integrated development between green finance and clean energy has significant implications for achieving structural energy transformation and sustainable financial development. This paper aims to explore the path toward achieving a positive interaction between green finance and clean energy. To achieve this, a coupling coordination degree model for the green finance – clean energy system is constructed. Additionally, limited attention has been paid to the interconnectedness of multiple factors with coupling coordination. Hence, we introduce a fuzzy set qualitative comparative analysis (fsQCA) approach to explore diverse pathways to enhance coupling coordination. Empirical results indicate that from 2011 to 2020, the degree of coupling coordination between green finance and clean energy in China improved from 0.3341 to 0.4718. However, it remains on the verge of an imbalanced level. Furthermore, the regional coupling coordination degree exhibits uneven development, with a tendency towards high-value clustering. The coordinated development paths of different provinces are driven by various configurations of conditions. Based on these findings, this study suggests that provinces should formulate policies tailored to their local characteristics and condition configurations, and effectively promote the coordinated development of green finance and clean energy in their respective regions. This study improves the comprehension of the coordinated development between green finance and clean energy at the provincial level in China. The employed fsQCA technique offers a novel approach for investigating developmental pathways of coupling coordination, bearing significance in promoting a mutually beneficial and harmonious relationship between green finance and clean energy.