Panel Data Of China Research Articles

Economic growth, industrial structure upgrading and environmental pollution: evidence from China

PurposeThe purpose of this study is to explore the impact of environmental pollution and industrial structure upgrading on environmental pollution in different stages based on the temporal and spatial heterogeneity of economic development level and industrial structure upgrading level in eastern, central and western regions of China and discuss whether there is adjustment effect and threshold effect in the process of economic growth affecting environmental pollution, and finally realizes sustainable economic development.Design/methodology/approachBased on panel data from 30 provincial-level administrative regions of China (excluding Tibet and Hong Kong, Macao and Taiwan) from 2000 to 2019, this paper uses the environmental Kuznets curve, regulating effect model and panel threshold model to analyze the impact of economic growth and industrial structure upgrading on environmental pollution.FindingsThe results present that the uneven distribution of natural resources leads to different levels of economic development and industrial structure upgrading in eastern and western regions, and its impact on environmental pollution is also different. Economic growth and industrial structure upgrading have a positive effect on environmental pollution, and the relationship between economic growth and environmental pollution is inverted U-shaped. At present, the eastern, central and western regions of China are at the right end of the inverted U-shaped relationship. In general, industrial structure upgrading in eastern, central and western regions has a significant inhibitory effect on environmental pollution. Industrial structure upgrading has a negative moderating effect on the relationship between economic growth and environmental pollution, and the regulating effect is most significant in the central region, followed by the eastern region, and not significant in the western region. The results of panel threshold model show that the industrial structure upgrading can slow down the positive impact of economic growth on environmental pollution and strengthen the negative moderating effect of industrial structure upgrading on economic growth and environmental pollution.Originality/valueThe innovation of this study is to bring economic growth, industrial structure upgrading and environmental pollution into a unified analytical framework, analyze the impact of economic development and industrial structure upgrading levels in different periods on environmental pollution, and select industrial structure upgrading as the moderating variable and threshold variable. It provides a thought for the influence mechanism of different levels of industrial structure upgrading on economic growth and environmental pollution. Based on the panel data in China, this study emphasizes the concept of sustainable development, adheres to green development and proposes relevant policies to improve environmental pollution. And this paper proposes relevant policies to improve environmental pollution from the perspective of transforming economic growth mode and optimizing industrial structure in China, which also has reference significance for developing countries to realize sustainable economic development.

Causes and Evolution Characteristics of Green Innovation Efficiency Loss: The Perspective of Factor Mismatch under Local Government Competition

The objective of this paper is to measure the efficiency loss of green innovation caused by local government competition and explore its causes and evolution characteristics. Based on the equimarginal principles such as the deviation of the allocation of green innovation output factors, this paper uses the panel data of China’s provinces (excluding Tibet, Hong Kong, Macao and Taiwan) from 2000 to 2020 and employs the spatial panel measurement model and the Kernel density estimation. The study finds that first, local government competition causes the mismatch of local innovation factors not only locally but also in neighboring regions. Second, the mismatch of innovative talents and capital caused by local government competition lowers the green innovation efficiency. Third, the shortage of innovative talents caused by local government competition is the main reason for the loss of green innovation efficiency in Beijing, Tianjin, and Shanghai. Fourth, the degree of efficiency loss of green innovation at the provincial level in China is heterogeneous in government competition strategies, and the loss due to tax competition is the most significant. Fifth, although the loss of green innovation efficiency generally decreases yearly, in the future, the institutional competition will still hinder the improvement of green innovation efficiency in the eastern, central and western regions of China. Our policy suggestions include promoting regional cooperation and cultivating innovative talents to further improve the efficiency of green innovation.

Quantify the Effect of China’s Emission Trading Scheme on Low-carbon Eco-efficiency: Evidence from China’s 283 Cities

The establishment of a carbon trading market is crucial for China to fulfil its carbon emission commitments through a market mechanism. As a market-based environmental regulation instrument, Emission Trading Scheme (ETS) has been attracted increasing attention worldwide, while the effect of ETS on low-carbon economy efficiency (LEE) has not been fully investigated, thus inspiring us to fulfil this research gap. Using the panel data of China’s 283 selected prefecture-level cities during 2006–2017, we adopted the difference-in-differences (DID) model, propensity-score-matched DID (PSM-DID) model, and the spatial DID model to model the direct and indirect effects of China’s ETS on LEE at national, regional, and local (resource-based cities with different development stages) levels. The robust results yield that ETS directly and significantly improved China’s LEE at the national level. Still, the LEE in ETS pilot region will increase by approximately 4.3% compared with untreated cities, while the spatial heterogeneity of this effect is captured at regional and local levels, which emphasises the necessity of a completed market construction and classified supervision. The results of this paper provide important insights for strengthening the policy design of a nationwide carbon market, and a reference point for other regions and countries, especially developing countries, in refining a carbon trading market.

Exploring Local Government Financing Strategies in China: A Capital Structure Perspective

This study analyzes how local governments use external financing instruments to adjust their capital structure. External financing instruments (public debt and public-private partnership [PPP]) have become critical options for most local governments to deal with budget constraints. We construct an indicator of the external financing ratio (EFR) to measure local governments’ dependency on external financing instruments. Based on the pecking order and tradeoff capital structure theories, we utilize city-level panel data in China between 2015 and 2019 to investigate the financing strategies of local governments. We report two main findings. First, the financing strategies of China’s local governments follow the pecking order theory. In other words, internal financing has priority over debt and then PPP. Second, consistent with the tradeoff theory, China’s local governments continuously adjust to a target EFR. In addition, compared with debt financing, the adjustment of PPP financing is relatively inelastic. Our study emphasizes the importance of public financial management reinforced by local governments to prevent fiscal risks in the context of intensified financial stress.

Digital Inclusive Finance Data Mining and Model-Driven Analysis of the Impact of Urban-Rural Income Gap

Digital inclusive finance, rural human capital, and agricultural green total factor productivity are simultaneously incorporated into the framework of urban-rural income gap analysis. Based on digital inclusive finance indices from several provincial panel data in China, a systematic generalized moment estimation method is used to the moderating effect of rural human capital and the mediating role of agricultural green total factor productivity. Annual time series data of foreign trade indicators and urban-rural income gap indicators are estimated by building a state-space model and applying Kalman filter to investigate the effects of these factors on the urban-rural income gap. The results show that the impact of urban-rural fixed asset investment ratio and foreign trade indicator on the urban-rural income gap in China tends to increase gradually, while the impact of rural financial development indicator is decreasing but still positive. The study finds that the development of digital inclusive finance significantly contributes to the reduction of the income gap between urban and rural residents; the breadth of coverage of digital inclusive finance and the degree of digitalization help to suppress the widening of the income gap between urban and rural residents; and rural health-based human capital, education and training-based human capital, and migration-based human capital not only have a convergence effect on the income gap between urban and rural residents themselves.

Economic Growth Targets and Carbon Emissions: Evidence from China.

Carbon emissions have become a new threat to sustainable development in China, and local government actions can play an important role in energy conservation and emission reduction. This paper explores the theoretical mechanisms and transmission paths of economic growth targets affecting carbon emissions from the perspective of economic growth targets and conducts an empirical analysis based on 30 provincial panel data in China from 2003 to 2019. The results show that: economic growth targets are positively correlated with carbon emissions under a series of endogeneity and robustness; there are regional heterogeneity, target heterogeneity and structural heterogeneity in the impact of economic growth targets on carbon emissions; after economic growth targets are set, government actions can influence carbon emissions by affecting resource mismatch and industrial restructuring; It is further found that there is a “U” shaped relationship between economic pressure and carbon emissions. Based on the above findings, this paper further proposes that a high-quality performance assessment mechanism should be developed to bring into play the active role of local governments in achieving carbon reduction goals, and thus contribute to high-quality economic development.

Effects of Environmental Regulation Competition and Public Participation on Enterprise Location Selection Under Climate Change in COVID-19 Pandemic Conditions: An Analysis Based on the Chinese Provincial Spatial Panel Model

The deterioration of environmental quality has attracted the attention of the Chinese government and the public. The Chinese government has delegated part of the power of environmental regulation to local governments. To fulfill the KPI, local governments tend to loosen environmental regulations to attract more settlement of enterprises, thus leading to an increasingly fierce local environmental regulation competition. The improvement of people’s living standards makes it possible for the public to participate in environmental regulation. This article seeks to carry out the empirical study to interpret the relationship between local environmental regulation competition, public participation, and enterprise location selection through a random effects (RE) spatial Durbin model with 29 provincial panel data in China from 2004 to 2017. The results show that the provincial spatial spillover effect of enterprise location selection is significant. More intensified local environmental regulation competition can attract more investment but may harm sustainable economic development. Active public participation can effectively avoid the excessive investment caused by local environmental regulation competition and sustain economic development. Therefore, we should establish and improve the local environmental prevention and regulation system and establish an information disclosure mechanism to ensure public participation. The local government’s environmental regulation and public participation mechanism should be effectively coordinated.

Spatial-temporal characteristics and driving factors of the chemical fertilizer supply/demand correlation network in China.

The rational allocation of chemical fertilizer resources is of strategic importance in mitigating agricultural source pollution and achieving agricultural green development. The spatiotemporal correlation of chemical fertilizer supply/demand and its determinants remains unclear. In this study, based on the inter-provincial chemical fertilizer supply/demand panel data of China from 1994 to 2018, an improved gravity model was employed to determine provincial chemical fertilizer supply/demand correlations. Finally, the chemical fertilizer supply/demand evolution and its driving factors were analyzed using social network analysis and a quadratic assignment procedure. The results indicated that (1) the intensity of the spatial relationship of inter-provincial chemical fertilizer supply/demand increased in a fluctuating fashion, but there was still room for improvement. The network structure presented good stability, and the spillover effect exhibited multiple superposition characteristics; (2) the spatial correlation network of inter-provincial chemical fertilizer supply/demand presented a "core-periphery" distribution pattern of the supply, demand, and balance areas. The division of blocks in the network changed in time and space, and some provinces changed their roles and positions in the network during development; (3) chemical fertilizer-related policies (e.g., Exemption Agricultural Tax, Notice on the resumption of value added tax policy on fertilizers, and Rural Revitalization Strategy) have played a positive role in the formation and development of the interprovincial spatial correlation network of chemical fertilizer supply/demand in China; (4) natural conditions and socioeconomic factors interact to promote the formation of the spatial correlation network of chemical fertilizer supply/demand. The differences in the scale of the rural labor force, the scale of agricultural mechanization, the agricultural planting structure, the populations, and urbanization levels all had a significant impact on it. The identification of the spatial characteristics of chemical fertilizer supply/demand correlation networks offers a new perspective on taking various measures to realize the cross-regional coordination of chemical fertilizer resources, strengthen the protection and utilization of agricultural resources, and promote green agricultural development.

Analysis of the decoupling state and driving forces of China’s construction industry under the carbon neutrality target

The essential to achieving the 2060 carbon neutrality target in China lies in the performance of the construction industry. Decoupling economic development from CO2 emissions is the main strategy for reducing emissions in the construction industry. This paper is based on panel data for China and its 30 provinces during 2009-2019. A Tapio decoupling model is constructed to analyze the decoupling state of economic development and CO2 emissions in the construction industry. The logarithmic mean Divisia index model is constructed to continue the decomposition of the drivers of the decoupling state and CO2 emissions. The results show that (1) the economic development level of most provinces is positively correlated with their CO2 emissions; (2) Beijing and Jiangsu reach the ideal strong decoupling state, and Heilongjiang has the worst decoupling state. The same type of decoupling state shows a certain aggregation phenomenon in space; (3) economic output plays a critical role in promoting CO2 emissions and decoupling of the construction industry in China and the provinces. The main driver of decoupling is indirect carbon intensity; (4) energy intensity has a greater impact on CO2 emissions reduction in regions with more developed economic levels. Understanding the drivers of the decoupling state in China's construction industry provides a valuable basis for energy efficiency and emission reduction efforts in China and other countries.

Tourism, urbanization, and urban income inequality in China

Despite the persisting interest in the nexus of tourism and income inequality, the relationships between tourism and urban income inequality remain unknown. In the past few decades, tourism, urbanization, and urban income inequality are all prominent social and economic phenomena in China. This study investigates such relationships and the underlying influence mechanism of urbanization based on provincial panel data in China between 1995 and 2019. The results show that tourism significantly increases urban income inequality. Moreover, there exists a Kuznets curve between tourism and urban income inequality. When the ratio of tourism revenue to GDP reaches the value of 0.416, the positive influence of tourism on urban income inequality reaches its maximum. Most of China’s provinces currently face the positive influence of tourism on urban income inequality. Besides, urbanization partially mediates tourism’s effects on urban income inequality. Heterogeneity analysis indicates that in high-urbanization, high-income, and low economic levels regions, tourism increases urban income inequality to a greater extent. This article enriches the knowledge of the association between tourism and income distribution.

Does agricultural mechanisation promote agricultural TFPG? Evidence from spatial panel data in China

ABSTRACT Does the promotion of agricultural mechanization level have spatial driving effects on the agricultural total factor productivity growth (TFPG)? Based on spatial panel data from 2000 to 2019, we begin by measuring agricultural TFPG, then incorporating spatial econometric models as well as carrying out spatial regression to first explore the influence agricultural mechanization level has on the agricultural TFPG. Meanwhile, we also perform decomposition of the spatial regression results to further study the spatial spillover effects performed by agricultural mechanization. The study suggests that the promotion of agricultural mechanization level has exerted significant spatial spillover effects on the agricultural TFPG, especially in the eastern and northeast regions of China, demonstrating obvious radiation effects, whereas the central and western regions may not produce such intense spatial spillovers due to the pattern of agricultural development. The results could not only enhance the understanding of agricultural mechanization on the agricultural TFPG but also produce constructive implications for optimizing the spatial layout of agricultural mechanization development, promoting agricultural development according to local conditions and formulating reasonable agricultural economic development policies.

Assessing the role of environmental regulations in improving energy efficiency and reducing CO2 emissions: Evidence from the logistics industry

Environmental regulations are an important means for government managers to manage the environment. The motivation of this article is to investigate the influence mechanism of incentive and mandatory environmental regulations on energy efficiency and carbon dioxide (CO2) emissions in the logistics industry. The quantile regression can estimate the comprehensive effect of explanatory variables on dependent variables, including maximum, minimum, and median. Based on the panel data of China's 30 provinces from 2005 to 2019, this paper adopts quantile regression to simulate the impact of environmental regulations on CO2 emissions and energy efficiency. The empirical results obtained are as follows: (1) incentive environmental regulations make a greater contribution to CO2 emission reduction in Ningxia, Qinghai, and Hainan provinces, due to their more aggressive levy of pollution fees. (2) Mandatory environmental regulations contribute the most to CO2 emission reductions in the 25th-50th percentile provinces, since these provinces issue more environmental decrees. (3) Incentive environmental regulations produce a greater influence on the energy efficiency in the 50th-75th, 75th-90th and upper 90th percentile groups, due to their greater R&D investment. (4) Mandatory environmental regulations have a greater impact on energy efficiency in Xinjiang, Heilongjiang, and Yunnan provinces. The findings can provide empirical support for the government to formulate effective environmental policies.

Study on the Impact of Financial Development on Carbon Emissions: Empirical Tests Based on Provincial Panel Data in China

With the goal of “carbon peaking” and “carbon neutrality”, an effective financial system can guide the allocation of funds to green industries, accelerate the adjustment and optimization of industrial and energy structures, and achieve green development. Based on the panel data of 30 provinces in China from 2003 to 2019, this paper constructs a two-way fixed-effect panel model to investigate the impact of China's financial development level on carbon emissions and the differences between regions with different economic conditions and stages of financial development. The following conclusions are obtained from the empirical tests: In general, China's financial development suppresses on carbon dioxide emissions. The impact of financial development on carbon emissions is also regionally heterogeneous within China. The financial development exerts a more significant inhibitory effect on carbon emissions in the western region, which has relatively poorer economic conditions and higher levels of carbon emissions, but not in the eastern region. After China experienced the financial crisis in 2008, thanks to the reform and improvement of the financial system, the suppression effect of financial development on carbon emissions is more significant and stronger.

Evaluation of China's OFDI Efficiency in Key Countries along "the Belt and Road" Based on DEA Model and Malmquist Index

With the continuous promotion and development of "the Belt and Road" construction, the economic cooperation and exchanges between China and the countries along "the Belt and Road" have been gradually deepened, and outward foreign direct investment (OFDI) is one of the important channels of economic exchanges between China and other countries. Therefore, the efficiency of outward investment is also getting more and more attention from all walks of life. Based on the panel data of China's direct investment in 26 key countries along "the Belt and Road" from 2014 to 2020, this paper uses DEA model and Malmquist index to conduct a comprehensive analysis and evaluation of China's OFDI efficiency. From the results of the DEA model, China's OFDI efficiency to key countries along "the Belt and Road" is low to medium, and the country differences in investment efficiency are mainly caused by the low scale efficiency (SE). From the results of the Malmquist index, China's investment in key countries along " the Belt and Road" in 2014-2020 is on a declining trend, and the investment efficiency will decrease significantly in 2019-2020 due to the impact of the COVID-19 pandemic. Therefore, we shall further improve the scale efficiency of OFDI, strive to develop advanced technology, encourage innovation, improve the technical progress index, optimize the choice of regional investment, and stimulate its vitality.

Study on Local finance and government debt scale

Based on the scholar’s research on the influencing factors of local government debt, this paper argues that the local government financial resources, degree of decentralization and local government investment enthusiasm in local finance are the significant factors that influence the form of local government debt. This paper also chooses the panel data of China’s 31 provinces (cities) except Hong Kong, Macao and Taiwan from 2010 to 2019, to analyze the influencing factors of local government debt scale and the relationship of local government debt scale in different regions and demonstrates the correctness of the hypothesis proposed in this paper. The analyze result shows that the local government financial resources significantly inhibit the growth of local government debt. The degree of local decentralization is an essential factor to enlarge the scale of local government debt. There is a significant positive correlation between the enthusiasm of local government investment and the scale of local government debt.

Digital Economy Empowers Common Prosperity: Theoretical Basis, Mechanism and Space-Time Evolution

Based on the provincial panel data of China from 2011 to 2020, we first fit the common prosperity index by using entropy weight method, then establishes a benchmark regression to explore the relationship between digital inclusive finance and common prosperity, and conducts a spatial expansion. The research results show that digital inclusive finance can help promote common prosperity, among which the dimension of coverage breadth is still the main driving force. However, at current stage, the development of digital inclusive finance in other provinces can only manage to improve the level of common prosperity in their own provinces, and cannot yet produce positive spillover effects on other provinces. Therefore, in order to achieve coordinated regional development and bridge the "digital divide", the development of digital inclusive finance should be transformed from the breadth of coverage to the depth of use as soon as possible, and while the western region is vigorously building digital infrastructure, the digitalization of the eastern region should be enhanced.

Decoupling Analysis of Rural Population Change and Rural Electricity Consumption Change in China.

With the accelerated development of urbanization in China, rural permanent population has declined, while rural electricity consumption has increased, resulting in a significant waste of electricity resources. Based on the provincial panel data of China from 2007 to 2020, this paper comprehensively used the decoupling model and the coordination degree model to analyze the temporal change characteristics, spatial distribution characteristics, and the degree of deviation of rural permanent population and rural electricity consumption. Firstly, according to the decoupling model, the type of decoupling between rural electricity consumption and rural permanent population was strong negative decoupling. At the provincial level, Beijing and Tibet belonged to expanding negative decoupling. Tianjin and Liaoning belonged to recession link. The other 27 provinces, including Hebei, Shanxi, and Shandong, belonged to strong negative decoupling. Secondly, according to the coordination degree model, the coordination type of the national rural permanent population and rural electricity consumption was uncoordinated. The areas that can be coordinated include 20 provinces, including Shanghai, Inner Mongolia, Jilin, Jiangsu, Anhui, Fujian, and Jiangxi. The basic coordination areas included Beijing and Tibet. Finally, according to the comprehensive measurement model, the provinces with strong negative decoupling included Shanxi, Zhejiang, and Chongqing. Sichuan, Hebei, Shandong, and Shaanxi belonged to moderately strong negative decoupling groups.

Digital Economy, R&D Investment, and Regional Green Innovation—Analysis Based on Provincial Panel Data in China

The digital economy plays an important role in promoting regional green innovation. Based on the panel data of 30 provincial administrative regions in mainland China (except Tibet) from 2011 to 2018, this paper constructs a comprehensive development index of the digital economy and explores the potential path of the digital economy affecting regional green innovation through factor analysis and regression analysis. The results show the following: Firstly, the digital economy can effectively promote regional green innovation capability. The causal relationship is mainly realized through scientific research funds and human resources. Secondly, in terms of regional heterogeneity, the role of the digital economy in promoting green innovation and R&D investment in eastern China is stronger than that in central and western China. Thirdly, further analysis showed that the digital economy has a significant nonlinear influence on regional green innovation capability. This feature is mainly reflected in the influence of R&D personnel on regional green innovation. Therefore, the rational allocation of R&D resources is conducive to the development of regional green innovation. Finally, it is suggested to improve the two mechanisms of R&D funds and personnel investment to actuate regional green innovation development.

Research on the Impact of Host Country Environmental Eegulations on China's OFDI under Different Investment Motivations——Empirical Research based on Panel Data of Asian Countries

This paper takes the panel data of China's OFDI in 28 Asian countries from 2008 to 2019 as a sample to empirically verify the impact of host country environmental regulations on OFDI under different investment motivations from a macro perspective. The empirical results show that: (1) China has obvious market seeking motivation, natural resources seeking motivation, and efficiency-seeking motivation for OFDI of Asian countries; (2) The host country's environmental regulations have a significant inhibitory effect on China's natural resource-seeking and efficiency-seeking OFDI in Asian countries, and have a significant promotion effect on innovative asset-seeking OFDI, but have little impact on market-seeking OFDI; (3) In the long run, the impact of host country's environmental regulations on China's OFDI shows a significant U-shaped relationship.

Marketisation and rural energy poverty: Evidence from provincial panel data in China

Under the advancement of market-oriented reforms, China's economy has achieved rapid growth, but rural energy poverty has also become a topic widely discussed in academic circles in recent years. This paper examines whether marketization can effectively reduce rural energy poverty in China. To this end, we build a nonlinear analysis framework, including the quantile panel model and panel threshold model, to investigate the impact mechanism of marketization on rural energy poverty using China's provincial data. The results suggest the following. (i) The effects of marketization on rural energy poverty are heterogeneous across China's provinces based on energy poverty. (ii) There is an inverted U-shaped relationship between marketization and rural energy poverty for provinces with different energy poverty levels. The impact of marketization on rural energy poverty changes from promotion to suppression when market-oriented reform is advanced to a certain level. (iii) There is a new threshold effect of marketization on energy poverty in the right part of the inverted U-curve. This indicates that marketization can reduce energy poverty more in provinces with “higher marketization” than in provinces with “lower marketization”.