Provincial Panel Data In China Research Articles

Exploring the moderating role of digital finance in the two-way foreign direct investment and green technology innovation nexus: an empirical evidence from China.

Based on the provincial panel data of China from 2011 to 2020, this paper explores the relationship between two-way FDI and green technology innovation and examines the moderating role of digital finance in the impact of two-way FDI on green technology innovation. The results show that (1) two-way FDI can significantly enhance the level of green technology innovation. (2) Digital finance plays a moderating effect in the process of two-way FDI to enhance the level of green technology innovation. The conclusion is still robust by replacing the dependent variable, eliminating special samples and shrinking the tail. (3) The results of sub-dimensional analysis show that the three sub-dimensions indicators of the digital finance also have a positive moderating effect on the relationship between two-way FDI and green technology innovation. (4) The results of sub-regional regression show that the moderating effect in the central and western regions is greater than that in the eastern region. The results of the study can provide reference for governments to formulate policies about digital finance, which is conducive to achieve high-quality opening-up and realize green development.

How does artificial intelligence affect the transformation of China's green economic growth? An analysis from internal-structure perspective

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

数字普惠金融对城乡收入差距的影响及机制分析——基于2011~2021中国省际面板数据的实证分析

数字普惠金融对城乡收入差距的影响及机制分析——基于2011~2021中国省际面板数据的实证分析

Analysis of the Impact of Environmental Regulation Heterogeneity on the Eco‐Economic Efficiency of Mariculture Industry

Mariculture has not fundamentally reduced its dependence on resources and the environment; ecological and economic efficiency has become an important target of concern for the sustainable and healthy development of China’s mariculture industry. Environmental regulation (ER) is a core tool to realize the synergistic development of economic development and environmental resource protection in mariculture. In this paper, the provincial panel data of China’s coastal areas from 2007 to 2020 was selected, and the level of ecological and economic efficiency of mariculture in different provinces of China was measured by using the super slacks‐based measurement–data envelopment analysis model considering the undesirable output of mariculture, and the impact of different ERs on ecological and economic efficiency was explored. It was found that the impacts of different ER methods on the eco‐economic efficiency (EEF) of mariculture may be non‐linearized, and there is also regional heterogeneity in the optimal choice and combination of ER methods to improve the EEF of mariculture.

Impact of artificial intelligence technology innovation on total factor productivity: an empirical study based on provincial panel data in China

<abstract> <p>As the focus of the new round of technological revolution, it is crucial to explore the role of artificial intelligence (AI) technology innovation in improving total factor productivity (TFP). Based on the data from 30 Chinese provinces from 2003 to 2021, this article measured AI innovation using the number of patent applications and empirically investigated the effects of AI technology innovation on TFP. The results demonstrated that AI technology innovation exerts significantly positive influences on the TFP. The mechanism analyses revealed that AI technology innovation improves TFP by upgrading industrial structures and promoting human capital. The subsample results indicated that the promotion effect of AI technology innovation on TFP is significant only in areas with high levels of marketization, financial development, and digital infrastructure. The panel quantile regression results indicated that as the TFP increases, the promoting effect of AI technology innovation on TFP gradually strengthens. This study offers comprehensive empirical evidence for understanding the impacts of AI technology innovation on TFP, giving a reference for further enhancing the level of AI development and promoting a sustainable economic development.</p> </abstract>

Has the Development of Inter-Provincial Transportation Infrastructure Improved the Construction of China’s Unified Market?

With the implementation of regional development policies in recent years, transportation infrastructure has greatly promoted regional economic development, but what impact it has on the construction of market integration in the local and surrounding regions has not been specifically answered. Based on the provincial panel data of China from 2010 to 2021, this paper uses the spatial panel method to study the impact of transportation infrastructure development and the construction of national unified market and its spatial spillover effects. The empirical results show that there is significant spatial auto-correlation between inter-provincial transport infrastructure and market integration. Railway density plays a greater role in promoting the national unified market. The government expenditure and foreign direct investment play a positive role in promoting the construction of a unified national market, while the dependence of foreign trade inhibits the development of market integration. In the analysis of spatial spillover effects, the direct effect of railway density is significantly higher than that of highway. The government should strengthen the quality and efficiency of railway transportation, promote the scale of foreign direct investment of enterprises, and actively promote the construction of national unified market.

Can bidirectional investment improve resource misallocation:A study based on provincial panel data in China

Can bidirectional investment improve resource misallocation:A study based on provincial panel data in China

Does green technology innovation contribute to regional carbon emission reduction? –Empirical analysis based on China provincial panel data

To promote low-carbon economic, China proposed building a green low-carbon circular development economic system. Green technology innovation is the essential core to promote green high-quality development, and is an important support to solve the realistic ecological environmental problems in our country. To study the influence mechanism of green technology innovation on regional carbon emission reduction, a fixed-effect model is constructed based on panel data from 30 provinces during 2011-2020, and this paper examines the mediating mechanism of energy efficiency. The results show that green technology innovation can significantly promote carbon emission reduction. Further research shows that green technology innovation can promote carbon emission reduction by improving energy efficiency.

Examining the U-shaped relationship between non-agricultural sources water pollution and the urban-rural income gap.

Determining how the economy and society interact with the environment of water quality is essential to determining the financial impact of green development. Based on China's provincial panel data from 2010 to 2021, this research considers non-agricultural sources of water pollution (NASWP) as a negative factor of production, investigates its influence on the urban-rural divide, and explains the mechanism of action. The empirical results show that there is a significant correlation between NASWP and the urban-rural gap, with a "U-shaped" relationship between the two. Water pollution first reduces and then increases the urban-rural income gap, and the results are robust after considering endogeneity. Mechanistic research demonstrates that NASWP cause a loss in food output, which in combination with changes in food prices and food subsidy programs impacts the incomes of rural dwellers, thereby having an influence on the urban-rural income gap. Using the threshold effect model, it is discovered that under the combined influence of agricultural mechanization and food subsidy policy, the relationship between NASWP and urban-rural income divide exhibits an U-shape in areas with high agricultural mechanization and an "inverted U" shape in areas with low agricultural mechanization.

CAN FINTECH CURB INCOME INEQUALITY IN CHINA?

The effect of FinTech on income inequality in China and the characteristics of the existing thresholds are examined in this study based on China provincial panel data from 2011 to 2020 by combining dynamic panel differential GMM with panel threshold models. As revealed by this study, (1) FinTech can significantly curb income inequality. (2) FinTech can mitigate income inequality in all regions, and the degree of mitigation is more significant in the central and western regions of China. (3) The improvement of FinTech development can reduce income inequality in all quantiles. The regions with high-income inequality and low-income inequality are compared. The comparison results reveal that FinTech can reduce income inequality to a greater extent in regions with lowincome inequality. (4) FinTech can restrain income inequality under different threshold variables, and the restraining effect of economic growth is the most significant. The policy significance of this study is to fully exploit the empowerment and income-generating role played by FinTech, build a more inclusive financial system, create a good financial environment, cultivate residents’ financial knowledge level, enhance the ability of low-income groups to obtain income from financial services and reduce income inequality, to fulfill the development goal of common prosperity.

Research on the dynamic changes of China's agro-processing industry agglomeration and spatial impact of production factors on agglomeration.

Agglomeration is an important phenomenon that accompanies with a large concentration of various production factors. Since the agro-processing industry has become a vital bridge connecting the primary and secondary industries, agglomeration and distribution within this industry are arousing wide concern. Based on provincial panel data of China from 2001 to 2020, this study described the dynamic changes of China's agro-processing industry agglomeration using spatial Gini coefficient and average concentration ratio. A theoretical analysis framework was established and a dynamic spatial Durbin model was used to quantitatively explore the spatial effects of production factors on the agro-processing industry agglomeration, results showed that: first, the agglomerations of agro-processing industry and its sub-industries all have exhibited a fluctuating trend of "up-down-up-down", meanwhile the agro-processing industry shifted from the Eastern coastal region to the central and western regions. Second, in the short term, the capital, labor, and technology factors respectively have remarkably promoted the agro-processing industries agglomeration both in local and neighboring areas. Third, in the long term, these three production factors all had a crowding effect on industrial agglomeration. Therefore, it is necessary to continue optimizing the agro-processing industry spatial layout through adjusting production factor inputs to promote high-quality development of the agro-processing industry.

The coupling coordination and spatial effect of eco-environmental governance efficiency and green innovation in China

ABSTRACT Green innovation effectively supports environmental protection during the process of economic development, and the benign interaction between green innovation and environmental protection has a vital significance to ecological civilisation construction. Based on DEA model and coupling coordination method, this paper analyses the coupling coordination relationship between eco-environmental governance efficiency and green innovation by using China's provincial panel data from 2005 to 2019. And it mainly draws the following conclusions: (1) The coupling and coordination relationship between eco-environmental governance efficiency and green innovation differs greatly among provinces. The coupling coordination degree in the eastern region is not only generally high, but also in the run-in stage, and its environmental governance and green innovation have a positive interaction. (2) Eco-environmental governance efficiency significantly promotes green innovation, but inhibits green innovation in the surrounding areas, which may be due to the elements of innovation are affected by the siphon effect. (3) There is a threshold effect of eco-environmental governance efficiency in promoting green innovation in the surrounding areas. Only when the coupling coordination degree of the ‘eco-environmental & green innovation’ within the province exceeds a certain level, the eco-environmental governance efficiency promotes the green innovation of surrounding areas.

Does green credit help reduce smog pollution? Empirical evidence from China.

As a resource production factor in environmental governance activities, can green credit help reduce smog pollution? Based on China's provincial panel data from 2006 to 2019, this paper empirically tests the impact of green credit on smog pollution by using an OLS regression model and a spatial Durbin model. The results show that green credit helps to reduce smog pollution overall; Industrial structure upgrading and green technology innovation are two critical paths for green credit to reduce smog pollution. The analysis of period heterogeneity finds that the descending effect of green credit on smog pollution becomes more significant after the transformation of China's economic development stage. The regional heterogeneity analysis finds that the descending effect of green credit on smog pollution is more significant in non-low-carbon pilot provinces and regions with lower economic development levels. In addition, green credit not only helps to reduce local smog pollution but also has a spatial spillover effect of "benefiting thy neighbors" on smog pollution in geographically neighboring areas. This study provides important inspiration for the government to further promote the innovation of green financial instruments and promote the improvement of environmental governance performance, provides decision-making references for different regions to implement differentiated green credit strategies to improve ambient air quality, and provides an experience reference for the development of green finance and environmental governance in emerging market countries.

Agricultural insurance and rural revitalization-an empirical analysis based on China's provincial panel data.

Agricultural insurance is a kind of compensation insurance designed to provide protection for the economic losses caused by insured accidents suffered by agricultural producers in agricultural production. Rural revitalization refers to the strategy of improving the level of rural economic, social and cultural development and achieving coordinated and sustainable development of urban and rural development. Agricultural insurance can effectively diversify risks and reduce losses for agricultural producers, which plays an important role in stabilizing farmers' income, helping rural economic development, and promoting rural revitalization. Based on the theoretical analysis of the mechanism of agricultural insurance on rural revitalization, this paper empirically studies the effect of agricultural insurance on rural revitalization by using panel data from various provinces in China from 2011 to 2020. In this paper, the TOPSIS entropy weight method, the system generalized method of moments (GMM) and the threshold model are used to calculate the actual development level of rural revitalization in each province of China, the promotion effect of agricultural insurance on the development level of rural revitalization and the promotion of rural revitalization in five dimensions, and whether there is a threshold effect of agricultural insurance on rural revitalization. The empirical results show that: (1) The level of rural revitalization in various provinces in China shows a dynamic trend of "overall slow rise, with obvious differences between provinces." (2) Improving the development level of agricultural insurance can drive the improvement of China's rural revitalization level, and every 1 unit increase in the development level of agricultural insurance will drive the level of China's rural revitalization to increase by 0.1633 units. At the same time, the role of agricultural insurance on social etiquette and civility is not significant, and the role of the remaining four rural revitalization goals is significant. (3) Agricultural insurance has a significant effect on the level of rural revitalization in eastern provinces, but does not play a significant role in rural revitalization in central and western provinces. (4) The role of agricultural insurance on rural revitalization has a double threshold effect. Accordingly, this paper puts forward some suggestions for increasing the capital investment in agricultural insurance, innovating the new mode of agricultural insurance operation, promoting the in-depth development of agricultural insurance according to local conditions, and reasonably adjusting the capital investment of agricultural insurance. Finally, because the data used in this paper do not cover the entire process of rural revitalization and the research is mainly carried out from a macro perspective, there are still some shortcomings in this paper.

Synergizing natural resources and sustainable development: A study of industrial structure, and green innovation in Chinese region

Amid China's rapid economic growth, the depletion of resources and escalating environmental pollution have emerged as critical impediments to its sustainable development. The efficient, convenient, and inclusive features of green innovation can facilitate economic transformation and provide technical support for sustainable industries. Optimization of the industrial structure can promote the allocation of resources in a more environmentally friendly and sustainable direction. Thus, we explore the impact of natural resource dependence on environmental quality and possible mechanisms through industrial structure, and green innovation using China's provincial panel data from 2011 to 2021. Research has shown that the decrease in natural resource dependency has a more obvious effect on improving environmental quality in the eastern region and the Yangtze River economic zone. Natural resource dependency influences sustainable ecology mainly through positive industrial structure upgrading and reverse spillovers in terms of green technological innovation. Industrial structure optimization and upgrading, improving factor allocation efficiency, and fostering a diversified industrial system are imperative for sustainable regional development.

Does green finance reduce environmental pollution?-a study based on China's provincial panel data.

As a bridge between economy and ecology, green finance is vital in improving environmental quality and promoting sustainable development. Based on the building of an environmental pollution index system, this paper constructs the [Formula: see text] model to deeply explore the specific impact of green finance on environmental pollution using China's provincial panel data from 2007 to 2020. This paper constructs an intermediary model to test the impact mechanism of green finance on reducing environmental pollution and discusses the regional heterogeneity of green finance in reducing environmental pollution. The results show that (1) green finance can significantly reduce environmental pollution, among which green credit has a pronounced effect on reducing environmental pollution, green investment has a relatively small effect, and green securities have not significant effect. (2) Green finance has the best inhibitory effect on solid pollution, less inhibitory effect on air pollution, and no significant improvement effect on water pollution. (3) Green technology innovation, industrial structure upgrading, and environmental regulation play an intermediary role in the process of green finance reducing environmental pollution and improving environmental quality. (4) The effect of green finance in the eastern and carbon emission pilot areas is significantly better than in the central and western regions and non-carbon emission pilot areasrespectively. According to the research results of this paper, suggestions are put forward to promote the development of green finance, which is of great significance to reducing environmental pollution and achieving sustainable development goals.

A Study on the Relationship Between Cross-border E-commerce, Business Environment, and High-quality Development of Foreign Trade

An essential factor in achieving high-quality development of foreign trade is cross-border e-commerce, which serves as a new catalyst for trade growth. This paper empirically analyzes the impact of cross-border e-commerce on the high-quality development of foreign trade using China's provincial panel data from 2013 to 2021. The study employs the static fixed effect model and dynamic Gram Molecular Mass (GMM) regression model to investigate the relationship, and further utilizes the mechanism effect model to explore the role of the business environment. The findings demonstrate that the emergence of cross-border e-commerce has significantly facilitated the growth of international trade. By improving the structure and increasing the level, scale, and competitiveness of foreign trade, it directly promotes the high-quality development of foreign trade. Moreover, the impact of cross-border e-commerce is more pronounced in regions with high Internet penetration rates compared to those with low rates.

What Information Do We Have on the Government's Environmental Management?

As one of the important pillars of China's industrial sector, the mining industry is critical to China's modernization and energy security. Based on China's provincial panel data, this paper collects the information on government's environmental management and estimates the impact of environmental regulation on China's mining industry's energy and carbon performance. The study further collects information on the industries' technological innovation and analyzes the technological innovation's moderating effect on environmental regulation. The research results indicate that the interconnection between the intensity of environmental regulations and the energy and carbon performance of the mining industry is inverted U-shaped, and mining enterprises with high levels of technological innovation have better adaptability when facing pressure from external environmental regulations. Regarding policy recommendations, it is imperative that the government should enhance the environmental policy framework, develop clean energy, and incentivize mining firms to advance technological innovation.

The environmental performance of agricultural production trusteeship from the perspective of planting carbon emissions

PurposeIn the context of carbon peaking and neutrality, effectively controlling agricultural carbon emissions has gained academic attention. As an essential form of agricultural service scale management, this study investigates whether and how trusteeship affects the carbon emission behavior in planting production.Design/methodology/approachThe authors established a theoretical framework to analyze the impact of agricultural production trusteeship on carbon emissions from planting. China's provincial panel data in the 2012–2021 period were selected to test the impact, mechanisms and heterogeneity of agricultural production trusteeship on carbon emissions from planting using the bidirectional fixed effect model and the panel correction standard error regression model.FindingsThe findings indicate that agricultural production trusteeship significantly inhibits carbon emissions from planting, especially in the dimensions of fertilizer input, pesticide application, agricultural film use and mechanical fuel. Agricultural production trusteeship primarily affects the intensity of these carbon emissions through contiguous farmland management and planting structure adjustment. Further examinations revealed that the influence of agricultural production trusteeship on carbon emissions from planting was heterogeneous with respect to geographical location, proportion of non-farming income and scale of agricultural production.Originality/valueThis study is the first to systematically evaluate the impact of agricultural production trusteeship on carbon emissions from planting.

Differentiated environmental taxes and high-quality economic development in China: theory and evidence.

Environmental tax policy plays an important role in promoting economic efficiency, but it is unclear whether the taxation is well-designed and effective. The differentiated environmental tax and fee policy in China has come a long way in the past 20years, along with the aim of high-quality economic development that focuses on the harmony of environment and productivity, so it is necessary to evaluate the effectiveness of the differentiated environmental tax and fee policy. This paper constructs a pollution and environmental tax model based on the new economic geography framework to simulate the effect of environmental tax and technological innovation in the eastern and western region on pollution, output, and productivity. Using China's provincial panel data from 2005 to 2020 with difference-in-difference method, empirical evidence shows that differentiated environmental tax and fee adjustments generally boost industrial high-quality development by the industrial sulfur dioxide emission deduction and green total factor productivity improvement. When the adjustment is more differentiated between treatment and control, the effect is greater and more significant. Additionally, high environmental tax standard in high SO2 emission provinces significantly contributes to high-quality development. Progressive adjustments in 2007, 2014, and 2018 lead to heterogeneous policy effect. Technological innovation plays a mediating effect between differentiated environmental tax and high-quality economic development. The results above provide theoretical analysis and empirical study of China's differentiated environmental taxes and high-quality economic development for policy making.