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The emitted levels of CO2 continue to be a striking topic. These emissions have been growing over the years, thus, making them a predicament to be reckoned with. Eradicating such a predicament has not been easy because finding an optimal determinant has not been achieved by scholars; however, foreign direct investment inflows are known to play a role in such varying instances. Therefore, to analyze the impact that such inflows have on CO2 emissions, this study employs data from 41 African countries from 2005 to 2019 and aims to assess how foreign direct investment and other variables influence CO2 emitted levels. Moreover, this study tests the validity of the pollution haven and halo hypotheses on the employed African countries as its two main objectives. After applying the pooled least squares, fixed and random effects models, and the generalized method of moments, the findings revealed that per the adopted African countries, the pollution haven and halo hypotheses do not hold; however, foreign direct investment inflows contribute to the rising and falling levels of CO2 emissions. In addition, the financial structure and per capita GDP increase the African countries’ CO2 emitted levels, while trade openness causes a reduction. Based on the aforementioned findings, this study recommends that the government, policy-makers, industries, and interested personnel of this study’s employed countries should: apply and execute policies, laws, and regulations that will deter or punish polluting foreign investment and encourage clean ones; since green finance is making waves but is not well established in most African countries, green financing systems should be initiated and implemented; establish preferential trading policies that will highlight an addition of value via clean technology; and practice carbon capture, usage, and storage.

Industrial structure upgrading is a huge driving force for China’s green economic development. The Yangtze River Economic Belt (YREB), a crucial component of China’s spatial economic pattern, is facing the dual pressure of economic development and environmental protection. Therefore, it needs to have its industrial structure upgraded immediately. This article measures the development levels of green finance using the entropy method and bases its analysis on the panel data of 11 provinces (municipalities) in the YREB from 2005 to 2019. A moderated mediating effect model is then built to thoroughly examine the influence paths of green finance and green technology innovation on industrial structure upgrading. According to the empirical findings, green finance and green technology innovation have a significant direct role in promoting the upgrading of industrial structures. They reflect significant regional disparities across the East, Midland, and West. Second, green technology innovation has an effective transmission mechanism in green finance, boosting industrial structure upgrading. Third, environmental regulations positively regulate green finance’s direct and indirect routes to support industrial structure upgrading. This study is the first to combine green finance, green technology innovation, environmental regulation, and industrial structure upgrading under one research framework, broadening the research scope of industrial transformation. These research findings provide theoretical and practical guidance for upgrading China’s Yangtze River Economic Belt’s industrial structure.

Traditionally, in the pursuit of economic development, ecological health was sacrificed, but this is no longer tenable considering the vast environmental damage that is difficult to control and expensive to repair. This is especially true for China’s Jianghuai River Basin (JRB). As a result, this paper uses the slacks-based measure (SBM) directional distance function and the tobit model on panel data from various cities and counties in the Jiangsu section of the HRB to empirically analyze regional green agricultural production efficiency and influencing factors from 2005 to 2019. The results illustrate that agricultural and environmental efficiency fluctuate upward in provincial areas. Still, a downward trend is observed in both redundancy and insufficiency rates of undesirable and desirable output. While this indicates improving regional agricultural and environmental efficiency, there is no readily detectable positive effect of technological progress and technical efficiency on green agricultural production efficiency improvements. Following a full analysis, policy implications are presented and discussed.

With the data of 41 cities, including urban and rural areas in the Yangtze River Delta (YRD) region from 2007 to 2019, this paper mainly uses the spatial econometric method to analyze the impact of forest resource abundance in the YRD region on economic development under the background of carbon neutrality. Direct effects, indirect effects, and total effects are further decomposed. The main conclusions are as follows. (1) The abundance of forest resources in the YRD has a U-shaped non-linear effect on economic development, and the curse of forest resources will gradually form forest resource welfare with economic improvement. (2) The phenomenon of economic convergence exists in the YRD region. (3) The spatial effect of forest resource abundance on economic development is non-linear, and the increase in greenery and carbon reduction should be moderately reasonable. (4) The abundance of forest resources can also promote the development of green total factor productivity. The research in this paper complements the existing literature and provides a reference for policymakers.

Since China’s reform and opening up, the speed of economic development has increased significantly. However, at the same time, there are also serious environmental pollution problems. To resolve the deep-seated contradiction between economic growth and environmental protection, green finance has gradually gained attention in China’s development. Based on this, the paper explores the impact of green finance on the quality of the ecological environment in the Yangtze River Economic Belt. The main part of the paper is based on panel data of eleven provinces and cities in China’s 2011–2020 Yangtze River Economic Belt. Seven indicators, including chemical oxygen demand COD, harmless treatment rate of domestic waste, and green coverage rate of built-up, were used to construct an ecological and environmental quality evaluation index system. The entropy method is used to measure the ecological environment quality level and green finance development level of various provinces and cities in the Yangtze River Economic Belt. The impact of green finance development on ecological environment quality is analyzed using a panel data model. The research results show that: (1) The development level of green finance and the quality of the ecological environment in the Yangtze River Economic Belt have improved between 2011 and 2020. (2) The development of green finance has a significant positive impact on the quality of the ecological environment in the Yangtze River Economic Belt. In addition, related research has focused on the impact of green finance on a certain branch of ecological and environmental quality and lacks an analysis of the overall impact. Therefore, this paper constructs a comprehensive evaluation system for ecological environment quality and analyzes the overall impact of green finance on ecological environment quality in the region.

Oil plays a vital role in the economic growth and sustainability of industries and their corporations. The current study sought to forecast oil demand in Ghana for the next decade. The variables analyzed in this study were Petroleum and other liquids, motor gasoline, distillate fuel, and liquefied petroleum gases (LPG). The study utilized three univariate models; thus, linear regression, exponential regression, and exponential smoothing for forecasting various oil components. The linear regression model was deemed a better fit for the analysis of most of the variables. Furthermore, the findings revealed that the LPG growth rate is faster and requires less time to double in numbers than the other energy sources. Also, the exponential smoothing model was ineffective and inefficient. Overall, the demand for oil components analyzed will follow an increasing pattern from 2017 to 2027.

The quality of the ecological environment is related to people’s health and quality of life, and is a prerequisite for happiness. This paper uses data from the 2019 Chinese Social Survey(CSS) and matches it with green tax data of 30 provinces and autonomous regions in China in 2019 using the mediation effect model to empirically analyze the influence mechanism and internal logic of the environmental governance on happiness. The results show that: (1) environmental governance can significantly improve happiness and indirectly affect happiness through green tax; (2) green tax can significantly enhance happiness; (3) income, regional, and education heterogeneity exists in the direct and mediating effects of environmental governance on happiness. Based on these results, in the context of the new era, we should solidly promote environmental governance and ecological civilization construction, promote the reform of the green tax system, and improve happiness. We should also consider the coordinated development of urban and rural areas and regions and focus on equity and efficiency. In addition, it is necessary to continue to deepen education reform, improve the quality of education, increase people’s income, and improve people’s happiness. This paper identifies the causal relationship between environmental governance and happiness and helps to clarify the influence mechanism and internal logic of environmental governance on happiness; it also discusses how to address the relationship between governance and development, promote green development, and improve happiness.

A country’s manufacturing industry is often an important route for national prosperity, but it is also a conduit by which a digital economy may become truly useful. This is so the deep integration of the digital economy and manufacturing industry can enhance independent innovation efficiencies, promote the development of advanced manufacturing clusters, and constantly spawn new models, forms of business, and industries. Consequently, it is crucial to improve China’s global manufacturing value chain. This article starts with an analysis of the development status and competitiveness of the digital economy in China and abroad. It establishes a structural equation and uses the latest data from the World Input-Output and Asian Development Bank databases. It introduces new variables, such as digitization, research and development (R&D) investment, and industrial scale to empirically analyze China’s manufacturing industry’s global value chain (GVC). The results show that the digitization of China’s manufacturing industry can increase the forward participation of GVC in the manufacturing industry to improve the division status of GVCs. Analyses suggest that due to insufficient R&D investment in the division of labor in the GVCs, China’s manufacturing industry is prone to low-end lock-in, inefficient industrial structures, and weak innovation ability. Consequently, the following suggestions are proposed: China’s manufacturing industry needs to accelerate digital transformation, increase R&D investment, actively participate in the division of labor in the GVCs, and enhance core competitiveness.

The development of digital financial inclusion helps create a healthy rural financial ecological environment and plays an important role in integrating rural tertiary industries. This paper incorporates digital financial inclusion into the rural tertiary industry integration research framework. Furthermore, it adopts the double-difference method to empirically analyze the impact of the development of digital financial inclusion on rural tertiary industry integration from the perspective of policy impact. In addition, it considers regional differences in the financial ecological environment; robustness tests were carried out using methods such as placebo tests and validated the conduction mechanism. The study through the double-difference model found that digital financial inclusion is very conducive to promoting rural tertiary industry integration; using the quantile DID (difference in differences) method to analyze the heterogeneity, it is concluded that there is a heterogeneous impact on rural tertiary industry integration. It exerts a more significant improvement in provinces and cities with higher rural tertiary industry integration levels. Constructing an intermediary effect model to verify the transmission mechanism concludes that the policy has promoted the improvement of rural tertiary industry integration efficiency by promoting technological innovation, improving agricultural modernization, and building a risk-sharing mechanism. Finally, it puts forward policy recommendations from optimizing the financial ecological environment, rationally allocating financial resources, and perfecting the transmission mechanism.

To solve the problems of economic growth and environmental pollution in China, it is crucial for local governments, as the responsible body for environmental protection, to rely on digital technology platforms to promote the green transformation of manufacturing industries, which is conducive to achieving sustainable social development. This study constructs a tripartite evolutionary game model and simulates and analyzes the influencing factors of manufacturing enterprises, the government and digital technology platforms. The study found that the critical value of the government subsidies for manufacturing enterprises using digital technology platforms is between 0.2 and 0.5. Manufacturing enterprises as “economic agents” should ensure their own profits and the good operation of their business when using digital technology platforms for green upgrading. The government penalties can improve enterprises’ green productivity as tested. This study enriches the research in the field of combining game theory and digital economy. It provides a theoretical reference for behavioral decisions of manufacturing enterprises, the government and digital technology platforms.

After a long struggle against poverty, the problem of absolute poverty among Chinese rural residents has been solved, but the problem of relative poverty still exists. With digitalization, the ecological environment of rural inclusive finance has been optimized. This paper empirically tests the individual fixed-effect model and finds that digital inclusive finance has a positive income-increasing effect on rural residents. Wage income, operating income, and transfer income among the income types undergo a certain degree of promotion, while property income is affected to the contrary. In addition, digital inclusive finance has the same effect on farmers’ income increases in the east and central regions of China. However, it has a slightly smaller impact on farmers in the west. This paper uses a spatial econometric model and finds that promoting the development of local digital inclusive finance will enhance the income level of local farmers and increase the income of neighboring farmers. Therefore, this paper proposes to speed up the development of digital inclusive finance, optimize the rural financial ecological environment, strengthen government supervision and other recommendations, further enhance farmers’ income, and achieve common prosperity.

With the continuous practice of the “Belt and Road” initiative, the countries along the “Belt and Road” have achieved rapid social and economic development. However, environmental problems have become increasingly prominent. Around the world, there are comments that China’s “Belt and Road” initiative is a result of resource plundering, transfer of backward production capacity, and environmental degradation of countries along the line. This study quantitatively evaluated the static, dynamic, linear, and non-linear effects of China’s foreign direct investment on the carbon emissions of countries along the line. The results showed that: (1) The direct effect of China’s foreign direct investment on the carbon emissions of countries along the route was significantly negative. (2) The economic scale and industrial structure effects of China’s foreign direct investment increased the carbon emissions of countries along the route. The production technology effect suppressed the carbon emissions of countries along the route and played a leading role. (3) The estimation results of the system generalized method of moments showed that the carbon emissions of countries along the route were significantly affected by the lag period, but the impact was small. (4) The results of the threshold regressive model showed that the GDP and proportion of industrial added value had significant threshold effects on the carbon emissions effect of China’s outward foreign direct investment. When the GDP of countries along the route exceeded 7.2696, China’s outward foreign direct investment carbon emissions reduction effect could not be realized; when the proportion of the industrial added value of countries along the route was lower than 4.0106, China’s outward foreign direct investment carbon emission reduction effect could not be realized. Based on the research conclusion, we concluded that China and countries along the “Belt and Road” should strengthen cooperation on carbon emissions reduction, jointly promote low-carbon construction of industrial parks, accelerate cooperation on green energy projects, and establish a green development fund to achieve sustainable development of the countries along the “Belt and Road”.

Since the reform and opening up some forty years ago, China has suffered from a capital shortage problem. To both solve this problem and satisfy its economic and social needs, China has been bringing in foreign investment, much of which has gone toward economic reconstruction. However, with the continuous inflow of foreign direct investment (FDI) into China, not only has the gap between rich and poor become increasingly wide but, due to China’s unique dualistic economic structure, the gap between urban and rural areas also appears to be widening. This aspect of the problem has attracted the attention of scholars around the world, as it may affect the future sustainable development of China’s economy and society. Cognizant of the need for practical solutions, this study conducts a more in-depth study of the relationship between foreign direct investment and the urban–rural income gap in China. Based on a review of previous studies and panel data from 30 Chinese provinces, this paper argues that FDI will affect this income gap through mechanisms such as employment structure, industrial structure and international trade. The findings of this study suggest that FDI inflows will first improve income inequality between urban and rural Chinese at a point in time but then have a worsening effect. In addition, China’s three major economic zones are examined, with results showing that the overall impact of FDI on the urban–rural income gap in China displays an inverted ‘U’ curve. Today, the impact of FDI on the urban–rural income gap is on the right-hand side of the curve, with regional differences in its impact. Urban–rural income inequality in the eastern region responds the most to FDI.

Based on the outward direct investment data of each manufacturing industry segment in Jiangsu Province from 2000 to 2020, this paper establishes a correlation network by constructing a grey incidence model with the average value of absolute grey incidence as the threshold. We further analyze the relationship between each manufacturing industry segment in Jiangsu Province in the process of outward direct investment from two perspectives, namely, point and surface. The study shows that from the perspective of each node, the correlation coefficient between equipment manufacturing and other industries is significantly higher, i.e., the influence of equipment manufacturing on other industries is significantly greater. Chemical raw materials and chemical products manufacturing, general equipment manufacturing, special equipment manufacturing, and transportation equipment manufacturing are the important nodes in the network. From the perspective of the network as a whole, the Jiangsu manufacturing OFDI affiliation network is not concentrated. Still, it has small-world characteristics, which are conducive to disseminating information. In contrast, the close nature of the industry has more commonalities, leading to it being more easily divided into the same module in the network block model analysis.

Revenue is one of the hottest topics in the field of open-source innovation. Can open-source innovation really bring more revenue to firms? What affects the revenue from open-source innovation? Based on the perspective of product homogenization and the enterprise-strength gap, these questions are answered in this study using theoretical analyses and the construction of a game model to explore the influence of product homogeneity and the strength gap between firms regarding the revenue from open-source innovation. The results show that enterprise homogeneity and the revenue from open-source innovation are not linearly related. High homogeneity does harm the revenue from open-source innovation, while the revenue is relatively high when the homogeneity is moderate. Additionally, it was also identified that the strength gap between firms has a negative influence on the revenue from open-source innovation. The wider the strength gap is, the greater the revenue loss of the weaker firms and, thus, the lower the total revenue of the two firms will be. This paper provides a reference for research on enterprise revenue from open-source innovation and the selection of participants in open-source activities.

It is of great significance to study the impact of innovation-driven strategy on high-quality development. This paper investigates the relationship between the economic development quality index (EDQI) and the innovation-driven index (IDI) using the entropy method based on China’s macroeconomic data from 2000 to 2019. It examines the impacts of innovation-driven strategy on the economy using systematic cluster analysis and the impact of innovation on economic development quality through regression analyses. Results of empirical analyses illustrate that the innovation-driven strategy of China has played an important role in the quality of economic development. Still, the lack of hard innovation leads to primary and secondary industries’ insufficient development quality. Different innovation indicators have different effects, and the overall efficiency of financial research funds is insufficient. Further, the results also show that the positive role of innovation-driven strategy is mainly realized through high-tech markets in China. Therefore, R&D investment should focus on high-tech industries or fields related to the national economic lifeline or strategic industries, such as environmental protection, microchips, and high-end instruments industries in China. This paper attempts to study the effect of China’s innovation-driven strategy on the quality of economic development to provide reference experience for developing countries’ sustainable economic development.

The Yangtze River economic belt is an inland river economic belt with international influence composed of 11 provinces and municipalities in the Yangtze River Basin. This paper uses the super-efficiency model to calculate the green total factor productivity of 11 provinces and municipalities in the Yangtze River economic belt (YREB). Then we establish a model to study the impact of industrial structure upgrading, industrial structure rationalization, and environmental regulation on green total factor productivity (GTFP). Empirical analysis shows that the industrial structure upgrading and environmental regulation have a significant impact on GTFP and show regional characteristics. The more developed the economy and the higher the industrial structure, the greater the impact of upgrading and environmental regulation on GTFP. Compared with other control variables, the urbanization rate impacts GTFP, followed by regional economic development.