China's Belt and Road Initiative (BRI), launched in 2013, aims to boost regional economic and policy cooperation. The BRI's alignment with the UN's 2030 Agenda for Sustainable Development, particularly its emphasis on co-consultation, co-construction, and sharing, makes it crucial to analyze the initiative's impact on sustainable development. While existing research focuses on the BRI's effect on economic growth and the environment, few studies examine the specific link between China's financial development and the achievement of SDGs in BRI participating countries. This research gap is significant because financial development plays a critical role in funding sustainable projects, improving resource allocation, and fostering technological advancements. The study addresses this gap by examining the multifaceted impact of China's financial development – considering scale, structure, and efficiency – on the SDGs of BRI participating countries. The research questions focus on whether China's financial development has promoted SDGs, how this impact varies across different types of BRI countries (geographic location, income level), and how the influence changes over time. The study's findings are relevant to policymakers in China and BRI participating countries, informing strategies to enhance sustainable development and build a shared future within the BRI framework. The timely implementation of SDGs in BRI participating countries is crucial because many lack sufficient development funding. The BRI promotes free flow of production factors, enhancing resource allocation and dismantling trade barriers, aiming to facilitate sustainable development.

Existing literature primarily focuses on individual dimensions of financial development (financial depth, stability, institutional environment) and their impact on specific aspects of sustainable development (e.g., CO2 emissions, deforestation, health). Many studies lack a multi-dimensional perspective and fail to comprehensively analyze the role of China's financial development in promoting the overall achievement of the SDGs within the BRI framework. This study addresses this gap by considering the scale, structure, and efficiency of financial development simultaneously, offering a more holistic perspective. Previous research often links financial development to a single SDG indicator, neglecting the interconnectedness of the goals. This research incorporates multiple SDGs (2, 3, 5, 8, 9, 11, and 15) allowing for a more comprehensive assessment of the impact of China's financial development. The lack of heterogeneity analyses in previous studies is also addressed by this research, as the impact of financial development is examined across different country types (based on geography, income level).

This study uses panel data from 61 BRI participating countries from 2005 to 2018, sourced primarily from the World Bank database. The dependent variable is a composite SDG index calculated using the entropy method, representing an aggregate score across selected SDGs. The explanatory variables capture China's financial development through three dimensions: 1. **Scale:** Measured as the ratio of RMB deposit and loan balances of financial institutions to GDP. Alternative measures include the value-added of the financial industry relative to GDP and the scale of social financing in China. 2. **Structure:** Measured as the ratio of the stock market value to bank credit. An alternative measure uses the ratio of direct financing to the scale of social financing. 3. **Efficiency:** Measured as the ratio of the balance of loans to deposits in financial institutions. Alternative measures include the stock turnover rate and market capitalization of shares. Control variables include population growth, technological level (R&D expenditure as a percentage of GDP), foreign trade (imports of goods and services as a percentage of GDP), education development (government expenditure on education as a percentage of total government expenditure), and human capital (number of R&D personnel per million people). A panel data regression model is employed to assess the overall impact of China's financial development on the SDGs. To account for spatial and temporal heterogeneity, a Geographically and Temporally Weighted Regression (GTWR) model is also used. The GTWR model allows for the regression coefficients to vary across space and time, providing a more nuanced understanding of the impact. For comparison, the study also implements a Geographically Weighted Regression (GWR) model. The Gaussian kernel function and Euclidean distance are used in both spatial regression models, and the optimal bandwidth is determined using the Akaike Information Criterion (AIC). The study compares the GWR and GTWR model results, demonstrating the superior performance and goodness of fit of the GTWR model in capturing the spatiotemporal heterogeneity. The entropy method involves data standardization (positive and negative indicators), calculation of indicator weights, entropy calculation, calculation of the coefficient of variability, and finally, the calculation of evaluation scores.

The study's key findings indicate that China's financial development has a significant positive impact on the SDGs of BRI participating countries. The impact varies across different dimensions of financial development: * **Scale:** The financial development scale has a positive but relatively smaller effect on SDGs compared to structure and efficiency. The coefficient is positive and statistically significant at the 1% level in the baseline model. This effect remains robust even when using alternative measures. * **Structure:** Financial development structure shows a positive and statistically significant impact on SDGs, especially in European and high-income countries. * **Efficiency:** Financial development efficiency exhibits the most substantial positive impact on SDGs. The coefficient is statistically significant at the 5% level in the baseline model and 1% level in sensitivity tests. Heterogeneity analysis reveals considerable differences in the effects of China's financial development across various country types: * **Geographic location:** The scale and efficiency of China's financial development have more pronounced effects on Asian countries compared to European countries. The structure of financial development primarily benefits European countries. * **Income level:** The scale of financial development is more impactful for low- and middle-income countries compared to high-income countries. Efficiency and structure show a more substantial effect in high-income countries. * **Silk Road:** The scale and efficiency of China's financial development have a greater effect on the Land Silk Road countries. Financial structure exhibits a stronger influence on European countries. Spatiotemporal analysis using GTWR models reveals that the positive impact of the scale of financial development has gradually decreased over time, while the positive impact of efficiency has increased. The structure's impact shows varied trends across different regions. The GTWR model provides a more detailed picture of these spatial and temporal variations compared to the GWR model, offering a refined understanding of the localized influences.

The findings demonstrate that China's financial development has played a crucial role in advancing the SDGs of BRI participating countries, especially in Asia, low- and middle-income countries, and those along the Land Silk Road. This positive effect is consistent with the BRI's goals of fostering economic growth and sustainable development in partner countries. The heterogeneous impacts across different country types likely reflect variations in economic conditions, institutional frameworks, and policy implementation. The inverted U-shaped relationship observed between the scale/structure of financial development and SDGs in some countries aligns with the Environmental Kuznets Curve (EKC) hypothesis, suggesting that the initial benefits of financial expansion may plateau or even decline as environmental concerns become more prominent. The consistently positive relationship between financial efficiency and SDGs highlights the importance of effectively allocating financial resources to sustainable initiatives. This study underscores the need for tailored strategies to maximize the positive impact of China's financial development on SDGs, focusing on optimizing resource allocation and promoting institutional reforms in BRI partner countries. The study also highlights the role of partnerships in achieving sustainable development, strengthening the overall efficacy of the BRI initiatives.

This study provides strong evidence that China's financial development has positively impacted the SDGs of BRI participating countries. The impact varies significantly across different dimensions of financial development and different types of BRI participating countries. Policymakers should focus on enhancing financial efficiency, optimizing the structure of financial development, and tailoring strategies to specific geographic and income contexts. Future research should focus on deepening the understanding of the mechanisms through which financial development influences specific SDG targets, incorporating more SDGs into the analysis, and investigating the interplay between financial development, institutional quality, and sustainable development in greater detail.

This study's limitations include the use of a specific set of SDGs and the potential for omitted variable bias. The analysis relies on aggregate data, limiting the ability to capture country-specific nuances or the impact on individual communities. The study's time frame (2005-2018) may not fully capture long-term impacts of the BRI. Furthermore, the study does not explicitly address potential negative externalities associated with China's financial involvement in the BRI, such as debt sustainability concerns or environmental degradation from certain projects.