Hui Wang

With the rapid development of technology and the evolution of the global financial system, digital inclusive finance has become a new way to promote rural revitalization and rural residents’ consumption with the power of financial technology. This study explores the relationship between digitally inclusive finance, rural revitalization, and rural residents’ consumption. Based on the panel data of 30 provinces and cities in China from 2011 to 2021, this study empirically examines the impact of digitally inclusive finance on rural residents’ consumption and the mediating and threshold effects of rural revitalization. The results reveal that digitally inclusive finance is conducive to the enhancement of rural residents’ consumption, and rural revitalization acts as a mediator. Meanwhile, there is a nonlinear positive correlation between the impact of digitally inclusive finance and rural revitalization on rural residents’ consumption, in which there is a double-threshold effect of digitally inclusive finance and rural revitalization in the lagged period. Based on the above findings, we believe that while promoting digitally inclusive finance, it is important to promote rural revitalization strategy in a timely manner, improve rural infrastructure, and continuously stimulate the impact of digitally inclusive finance on rural residents’ consumption.

The jump in the value of the stock may result in a corresponding escalation of risk associated with the stock market. When a jump occurs in any particular market, such a risk can spread to other markets. This paper examines realized volatility and risk contagion of the jump between the Chinese mainland and Hong Kong market utilizing realized volatility and three realized jump separation methods. Correspondingly, the Markov regime‐switching approach is employed to exhibit the contagion effect of the jump risk in two economic states. This study employs the Shanghai–Shenzhen 300 Index and the Hang Seng Index as empirical research subjects. The results show that the Hong Kong market has a higher frequency of jumps compared to the mainland market. The MedRV method is found to be effective in identifying more jumps, while the mainland market displays a unidirectional contagion effect on Hong Kong. Under such circumstances, the risk associated with a continental market jump exhibits an unevenly contagious effect on the Hong Kong market. In conclusion, China needs to enhance its financial market risk management in order to avert the spread of escalating risk across markets.

Against the backdrop of the COVID-19 pandemic and China’s pursuit of the "double circulation" strategy, scholars are increasingly focusing on ensuring high-quality economic development in China. In this regard, digital inclusive finance and consumer consumption are of utmost significance. This study employs panel data from 30 provinces and cities spanning 2011 to 2020 to explore the impact of digitized inclusive finance on consumer consumption and high-quality economic development through a spatial econometric model. Our findings indicate that integrating digital finance with consumer consumption and economic development fosters high-quality economic growth. Furthermore, our semi-parametric spatial lag model suggests a nonlinear relationship between digital inclusive finance and high-quality economic growth, shaped like an inverted "U". Additionally, we examine the mediating effect of consumer consumption on the relationship between digital inclusive finance and high-quality economic development. Our results reveal a substitution effect between digital inclusive financing and consumer consumption in promoting high-quality economic development. Therefore, it is essential to promote the development of digital inclusive finance, harness its positive spillover effects between regions, and encourage an increase in consumer consumption to optimize the consumption structure, upgrade and adjust the industrial structure, and spur growth in emerging industries.

As the “double carbon” goal gains traction worldwide, achieving a balance between economic growth and environmental sustainability has become a focal point for researchers. Green finance, as a specialized financial service, offers a new approach to sustainable development. This study analyzed carbon emission sources in 25 Chinese provinces between 2007 and 2020, dividing them into energy structure, economic development, energy efficiency, and industrial structure, using a two-stage LMDI method. It then examines the linear and non-linear relationships between green finance and carbon emissions using spatial measurement methods. The findings indicate that green finance is an effective way to reduce carbon emissions, primarily through its impact on energy structure, energy efficiency, and industrial structure. There are significant non-linear relationships between green finance and the factors affecting carbon emissions, with spatial effects playing a significant role in carbon emissions influenced by energy structure, economic development, energy efficiency, and industrial structure.

Graph cut is a popular approach to solving optimization tasks related to Min-cut/Max-flow problems. However, existing FPGA accelerators of graph cut have difficulty in handling large grid graphs and achieving real-time performance. To address the issue, we propose a novel folding grid architecture that maps an actual one-layered large 2-dimension grid graph into a virtual multi-layered small 2-dimension grid graph. The new architecture not only enables the virtual multi-layered grid graph to execute on a small-size processor array but also adds the potential to concurrently execute grid graph nodes in different layers. In addition, we also propose a novel out-of-order parallel execution technique to fully utilize the architecture parallelism potential. Compared to the state-of-the-art, experimental results show that our design can solve the graph cut problem for grid graphs of 1920 × 1080 nodes in real-time (above 60fps) and achieve a 5.4× improvement in execution time with similar FPGA resources.

In light of the growing emphasis on sustainable development, financial poverty alleviation has become an increasingly important strategy. This study explores whether green finance, a new financial tool aimed at achieving sustainable development, can effectively reduce poverty. Using data from 25 provinces in China between 2004 and 2019, the study builds the China Green Financial Development Index, using the improved entropy power method, and uses a spatial econometric model to analyze the linear and non-linear impact of green finance on absolute and relatively poor poverty. The results demonstrate that green finance has a positive impact on poverty reduction, with a more significant impact on rural poverty reduction than urban poverty reduction. Interestingly, non-linear results reveal that the impact of green finance on rural poverty alleviation has gradually weakened, while the impact on urban poverty alleviation has gradually increased. Moreover, the introduction of technological progress as an intermediary variable has revealed an intermediary effect between green finance and poverty reduction. Overall, this study contributes to our understanding of the link between green finance and poverty and suggests a new approach to poverty alleviation.

Risk preference has constantly been one of the vital issues in economics and finance. In this study, the time series and term structure of Chinese investors’ implicit risk aversion are investigated using the implicit risk aversion extraction method, and the dynamic term structure of Chinese investors’ implicit risk aversion is modeled using the Vasicek model. In the empirical process, the SSE 50 ETF option data from March 2015 to July 2018 are adopted to extract model‐free risk‐neutral skewness. The standard deviation, skewness, and kurtosis of reality measure are extracted using the Shanghai 50 ETF data, and then the monthly implied risk aversion time series and term structure of Chinese investors are obtained. As indicated by the results of this study, the risk preference of Chinese investors exhibits significant time series characteristics, and it will show risk‐loving and risk‐averse phenomena at certain times. Moreover, for different periods in the future, differences are generated in investors’ risk preferences, suggesting an aversion to short‐term risk and a certain tolerance for long‐term risk, i.e., there are significant characteristics of the term structure. Besides, the term structure of implied risk aversion of Chinese investors is dynamically modeled using the Vasicek model. To be specific, its first principal component can account for 90% of the change in the term structure. The “level factor” refers to the critical factor load, and the level of long‐term implied risk aversion reaches 0.658. Furthermore, the term structure of implied risk aversion exhibits the characteristics of mean regression. Next, more effective research results on investors’ risk preference are achieved, and the time‐varying characteristics and term structure characteristics of investors’ risk preference are investigated. The result suggests that the long‐term risk preference of Chinese investors approaches 1, and there is a significant feature of “mean regression,” i.e., a vital finding of this study.

This study explores the relationship between the proportion of basic research investment in R&D expenditure and regional economic growth efficiency and its influence path. A panel of data from 31 China’s provincial was analysed by the fixed-effects model over 2009 to 2019. Empirical results highlight that: (1) the increase in the proportion of basic research investment has a significant promoting effect on regional economic growth efficiency, but it presents an "inverted U-shaped" impact path. Meanwhile, the threshold effect model test results reveal that basic research investment plays a more significant role in promotion when the per capita income level exceeds a certain threshold. (2) The test results of the mediating effect model indicate that the improvement of the level of human capital is the intermediate channel through which the investment in basic research affects regional economic growth efficiency, while the mediating effect of the increase of knowledge storage on the process of the investment in basic research affecting regional economic growth efficiency is not supported by data. Potential policy measures are discussed.

Carbon peaking and neutrality goals have been an important issue in China’s economic development in recent years. Here is increasing academic interest in ways to realize emission peak and carbon neutrality goals within a finite timeframe. As an important means of sustainable development, high-quality economic development and green credit are of great significance to achieve carbon peak and carbon neutrality. Based on the panel data of 29 provinces and cities in China from 2007 to 2020, spatial Durbin and semi-etric spatial lag models are adopted to investigate the impact of high-quality economic development on green credit and carbon emissions. This study also analyzes whether green credit plays a moderating role in the impact of high-quality economic development on carbon emissions through the moderating effect model. The results reveal that such development has a significant negative correlation with carbon emissions, and presents an “inverted U” -shaped nonlinear relationship. There is a significant negative correlation between green credit and carbon emissions, and an “n-type” nonlinear relationship. Finally, the moderating role of green credit in the impact of high-quality economic development on carbon emissions is analyzed. This study presents the following suggestions: (1)Give full play to the positive spillover effect of high-quality economic development between various regions, and build a complete high-quality economic development system, (2) Improve the green credit system, increase green credit funds, and promote green development.