Yifeng Wang

As the greenhouse effect and the environmental problems thus arising become increasingly prominent, great concern has been aroused for agricultural carbon emissions reduction and sustainable development. Aiming at exploring how to reduce agricultural carbon emissions from agricultural green finance perspective, this study theoretically analyzed the impact and mechanism of agricultural green finance on agricultural carbon emission intensity, and empirically examined the specific impact and the corresponding impact mechanism of agricultural green finance on agricultural carbon emission intensity. Specifically, a two-way fixed effect model was employed to conduct the study based on the panel data of 30 provinces in China from 2011 to 2022. The results show that agricultural green finance can significantly reduce agricultural carbon emission intensity, which has been verified to be valid after a series of robustness tests; and the reduction displays a heterogenous pattern. As it is, the impact of agricultural green finance is more prominent in the eastern region than in the central and western regions, and greater in non-major-grain-producing areas than in major grain-producing areas. On this basis, some policy suggestions are put forward, mainly including developing agricultural green finance, promoting agricultural and green technological innovation, and implementing differentiated agricultural green finance policies so as to reduce agricultural carbon emission intensity.

Agricultural green finance is an important means to boost the development of agricultural green. Based on the panel data of 30 provinces in China from 2011 to 2021, this paper theoretically discusses the impact of agricultural green finance on the level of agricultural green development and conducts an empirical study by using the two-way fixed effect model and panel threshold model. The empirical findings show that agricultural green finance can significantly improve the level of agricultural green development mainly through facilitating the level of agricultural green technology innovation. The promoting effect of agricultural green finance on the level of agricultural green development is remarkable in the eastern region and non-major grain-producing areas, but not obvious in the central and western regions and major grain-producing areas. Indeed, the impact has a single threshold effect with environmental regulation as the threshold. Therefore, efforts should be made to improve the level of agricultural green development from the following aspects: vigorously developing agricultural green finance; promoting agricultural green technology innovation; strictly implementing environmental protection policies; and designing appropriate environmental regulation zones.

The construction of enterprise digitization serves as a "gateway" for the integration of the digital and real economies. As enterprises undergo robust digital transformations, it becomes crucial to delineate the pathway from enterprise digitization level to value creation and realization in order to maximize enterprise value. We select sample data from Chinese A-share listed companies from 2015 to 2021 as the research subject. Based on the fixed-effects model, we empirically test the impact of enterprise digitization level on both value creation and realization, as well as the mediating mechanism of entrepreneurship and internal control within it. The results indicate that the enterprise digitization level significantly enhances both value creation and realization. However, significant differences exist in the impact of the digitization level on value creation and realization among enterprises with different technological attributes and at different stages of the lifecycle. Further mechanism tests demonstrate that the "breakthrough-based" entrepreneurship and "compliance-based" internal control quality play effective mediating roles between enterprise digitization level and enterprise value. This study provides a new perspective for understanding the value creation and realization process in the digital context, and offers relevant insights for further stimulating and guiding enterprises of different types and stages to drive value enhancement with digital capabilities, thereby facilitating the deep integration of the digital with the real economy.

The digital economy, as a new economic form with high information density, provides a new driving force for the realization of high-quality agricultural development. Panel data of 31 provinces in China from 2011 to 2020 were selected for analysis. The static panel data interaction effect model and panel threshold model were used to verify the nonlinear influence mechanism and heterogeneity of financial development in the process of the digital economy affecting high-quality agricultural development. The findings are as follows. (1) During the study period, the high-quality development of China’s agriculture showed a steady upward trend; however, the regional differences were significant, and the eastern part was larger than the central and western part. (2) The digital economy can promote high-quality agricultural development. (3) The digital economy has a double threshold effect in the process of affecting high-quality agricultural development, which depends on the level of financial development. When the threshold is exceeded, the digital economy has a more significant promoting effect on high-quality agricultural development. (4) The impact of the digital economy on high-quality agricultural development is heterogeneous. From the perspective of different regions, the impact effect is greatest in the eastern region, while the effect is smaller in the central and western regions. From different resource endowments, the positive impact effect is greatest in the major grain-selling areas, followed by the major grain producing areas, but the positive digital economy driving effect is not significant in the balance of production and sales areas. Finally, three policy suggestions are proposed. First, the Chinese government should increase investments in and support for digital technology to promote the integration of the digital economy and agriculture. Second, the Chinese government should promote the development of digital inclusive finance in areas with financial development below the threshold. Third, different regions should implement differentiated digital economies to promote high-quality agricultural development.

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.

In this paper, 22 indexes are selected at three levels, including the informatization development level, the Internet development level, and the digital transaction development level, based on China’s provincial panel data from 2011 to 2020, so as to build a digital economy development index system. Moreover, 28 basic indexes are selected from three aspects, including energy construction, energy production and energy consumption, so as to develop an energy economy development evaluation index system. The development index of China’s digital economy and energy economy are measured by using the entropy weight method. The effect of the digital economy on the energy economy and its mechanism are tested by the static panel, the dynamic panel, and the mediating effect and regulating effect models. The results indicate that the digital economy has pronouncedly promoted the development of China’s energy economy, and the development of the digital economy can have an effect on the rationalization of the industrial structure and then affect the development of the energy economy, and there is an intermediary effect. Moreover, the upgrading of the industrial structure is conducive to regulating the digital economy and facilitates the development of the energy economy. The development of the energy economy can be better promoted by focusing on the coordinated regional layout of the digital economy development, building a reliable energy commodity trading platform, and expediting the optimization and upgrading of the industrial structure.

This article uses the entropy weight method to calculate China’s economic high-quality development index and carbon finance development index from 2000 to 2020. Additionally, it conducts empirical examinations to scrutinize impacts of carbon finance regarding quality-focused development of China’s economy through dynamic spatial models. The findings reveal that the advancement of carbon finance substantively promotes the quality-focused economy advancement through enhancing the overall factor productivity, thereby establishing a mediating effect. Concurrently, the allocation of resources in green fiscal expenditure assumes a moderating effect, subsequently amplifying the promoting effect of carbon finance regarding quality-focused economy advancement. Consequently, it is recommended that a robust financial milieu be established, energy efficiency be enhanced, scientific and technological progress be bolstered, total factor productivity be further augmented, and the expenditure on green conservation be escalated. These measures will effectively stimulate the quality-focused development of China’s economy.

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.

In order to study the impact of inclusive finance on agricultural green development, This paper uses both static panel and dynamic panel (system GMM model) estimation methods to make empirical analysis of the impact of inclusive financial development on agricultural green development. The results both find that there is a significant positive correlation between the level of inclusive financial development, real GDP per capita, the proportion of the added value of agriculture, forestry, animal husbandry and fishery in GDP and agricultural green development. This paper puts forward some countermeasures and suggestions to promote agricultural green development, including vigorously developing inclusive finance, promoting economic growth, promoting the development of agriculture, forestry, animal husbandry and fishery, and increasing environmental protection expenditures.