Prefecture-level Cities In China Research Articles

Impact of Low-Carbon City Pilot Policies on Regional Green Total Factor Productivity: A Study

Based on data from 246 prefecture-level cities in China spanning the years 2006 to 2019, this paper employs a multi-temporal double-difference model to empirically examine the effects of low-carbon pilot policies implemented since 2010 on green total factor productivity. Furthermore, the paper conducts a mechanism analysis and heterogeneity analysis to explore the policys impact mechanisms and effects on different regions. The study reveals that low-carbon pilot policies have enhanced Chinas green total factor productivity. Results from the mechanism analysis indicate that these policies increase green total factor productivity by promoting the agglomeration of productive service industries and the innovation of green technologies, with the mechanism test for manufacturing industry agglomeration showing non-significant effects. Heterogeneity analysis results suggest that the impact of low-carbon pilot policies on the improvement of green total factor productivity is significant in Chinas eastern and western regions as well as in non-resource-based cities.

Government digital transformation, resource curse and green total factor energy efficiency in Chinese cities

In the age of digitalization, Government Digital Transformation (GDD) stands out as a critical gauge of a nation's modernization drive. It reflects the extent of modernization within the governance framework and acts as a central catalyst for improving governance efficiency and the overall modernity of the system. Against this backdrop, this study empirically investigates the impact of GDD on green total factor energy efficiency (GTFEE) from 2011 to 2020, focusing on prefecture-level cities in China. Using a two-way fixed-effects model, we analyze how GDD influences GTFEE. Additionally, we explore the mediating effect and threshold models to elucidate the mechanisms underlying the resource curse (RC). The findings of the study are as follows: first, GDD has a promoting effect on GTFEE; second, the promoting effect of GDD on GTFEE is more obvious in southern cities and fourth-tier cities; third, the RC plays a mediating effect in the relationship between GDD and GTFEE, specifically, GDD promotes GTFEE by suppressing the RC effect and then promotes GTFEE; fourth, the present study also identifies a RC threshold effect; when RC < 0.5127, the energy efficiency promotion effect of GDD is relatively limited, while when RC ≥ 0.5127, the promotion effect of GDD on GTFEE is significantly enhanced. These findings are of great value for understanding and optimizing the strategic significance of GDD in enhancing GTFEE. They provide a scientific basis and directional guidance for formulating and implementing related policies.

China's environmental tax reform achieves the co-management of carbon and haze: the role of optimizing energy utilization

Environmental tax reform in China is an essential initiative to achieve carbon and haze co-management by shifting the Environmental Fee to Tax (EFT). Therefore, we employ a Coupling Coordination Degree (CCD) model to measure the level of carbon and haze co-management across three distinct scenarios in China. Treating the EFT policy as a quasi-natural experiment, the study explores its impact on carbon and haze co-management using data of 282 prefecture-level cities in China during 2015-2020. Furthermore, the study further analyzes the regional heterogeneity and the transmission mechanisms of optimizing energy utilization. The principal findings of this investigation are as follows. First, the co-management levels of carbon and haze in China show a discernible upward trend from 2015 to 2020. A heightened emphasis on carbon reduction is helpful in improving the co-management level of carbon and haze. Co-management levels of carbon and haze are lower within the treatment group compared to the control group, but their growth rates are higher. Second, the EFT policy in China significantly enhances the co-management level of carbon and haze. Third, the impact of China's EFT policy has a more pronounced effect in western China and a comparatively weaker effect in middle China, which may be attributed to variations in industrial infrastructure, supporting facilities, availability of clean energy resources, and prevailing policy inclinations across different regions of China. Finally, China's EFT policy is an instrumental factor in augmenting the co-management level of carbon and haze, primarily through pathways of upgrading energy structure and improving energy efficiency.

Distribution dynamics and quantile dynamic convergence of the digital economy: Prefecture-level evidence in China

The digital-substantive fusion is the realistic need to crack the problem of “out of the real to the virtual” in the real economy. Based on the panel data of 288 prefecture-level cities in China from 2011 to 2019, we use kernel density estimation and quantile convergence model to explore the distribution dynamics and convergence trend of the digital economy across the country and in the eastern, central, and western regions. In doing so, we unearth several key findings. First, the development of the digital economy in Chinese cities is on the rise, but absolute differences among cities still exist. Second, the overall development of the digital economy exhibits a dynamic q-σ convergence trend, but the development of the digital economy in the central region from the 0.75 to 0.95 quantiles shows a divergence trend. Third, our analysis reveals quantile heterogeneity and regional heterogeneity in the dynamic absolute q-β convergence of digital economy development. The tendency to converge is stronger in the extreme quantile regions than in other regions, while the convergence speed of central and western regions is higher than that of eastern regions. Finally, the dynamic conditional q-β convergence trend of digital economy development across the country and in the eastern, central, and western regions is stronger than the dynamic absolute q-β convergence, with the trend of convergence weakening only in the eastern high quantile regions. These findings provide empirical evidence for promoting regional coordinated high-quality development of digital economy, as well as theoretical references for vigorously promoting the construction of a modernized industrial system and accelerating the development of new-quality productive forces.

The effects of sub-central development on the economic growth of provincial capitals: A study based on the DID and PSO-RF models

As a core component in deepening reforms and expanding the strategy of dual circulation development, the importance of developing sub-centers for the economic growth of provincial capitals is self-evident. This paper, based on panel data from 300 prefecture-level cities in China from 1998 to 2020, constructs a progressive double-difference (DID) model to assess the impact of sub-central development on the economic growth of provincial capitals. The research reveals that the development of sub-centers at the provincial level significantly promotes the economic growth of provincial capitals. Moreover, the policies of sub-center cities have a more pronounced stimulating effect on the economic growth of provincial capitals in the central and western regions. Additionally, the more sub-center cities there are, the more apparent the effect on promoting the economic growth of provincial capitals. Subsequently, this paper employs the Particle Swarm Optimization - Random Forest (PSO-RF) model through machine learning to validate the above conclusions, confirming the validity of the findings.

The Impact of the Digital Economy on Urban Ecological Resilience: Empirical Evidence from China’s Comprehensive Big Data Pilot Zone Policy

The present study examines the effects of China’s comprehensive big data pilot zone policy on urban ecological resilience. This is achieved through the utilization of a quasi-natural experiment, employing panel data from 217 prefecture-level cities in China spanning the years 2010 to 2021. The research revealed that China’s extensive policy on big data pilot zones has a notable and favorable influence on the ecological resilience of urban areas. This impact is both constant and subject to variation across different regions. The aforementioned impact is attained by means of progressions in industrial structure and the introduction of innovative green technologies. Furthermore, the strategy exerts a beneficial impact on the ecological resilience of urban areas in adjacent regions by means of spatial spillover effects.

Transportation infrastructure upgrading and green development efficiency: Empirical analysis with double machine learning method

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as ‘dimensional curse’ and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading.

Energy and environment: How could energy-consuming transition promote the synergy of pollution reduction and carbon emission reduction in China?

In order to attain the mutually reinforcing advantages of pollution reduction and carbon emissions, it is imperative to give precedence to the prevention and control of carbon pollution from its source, hence promoting a forward-thinking approach to governance. Hence, there is an urgent need for theoretical explanation and empirical verification to determine whether the energy-consuming right trading system, which serves as a conventional method for preventing and controlling pollution, has effectively achieved the desired outcome of reducing carbon emissions and promoting a mutually beneficial outcome. This study employs a panel data analysis of 266 prefecture-level cities in China spanning the years 2011 to 2020. The objective is to investigate the influence and underlying mechanism of the energy-consuming right trading system on the synergistic effects of pollution reduction and carbon emissions. At the same time, the heterogeneity analysis is carried out at three levels, including geographical location characteristics. The findings indicate that the energy-consuming right trading system has a substantial impact on enhancing the synergistic effects of pollution reduction and carbon emissions. In comparison to cities that did not implement the system, the pilot cities experience a reduction of 84.8% in CO2 and 34.5% in SO2. Eco-environment attention, clean energy substitution, energy consumption structure, and green technology innovation are the key transmission mechanisms of the energy-consuming right trading system affecting the synergistic effects of pollution reduction and carbon emissions. In addition, the effect is significantly different in different cities.

Digital inclusive finance, green technological innovation, and carbon emissions from a spatial perspective

Based on the panel data of 276 prefecture-level cities in China from 2011 to 2020, this study explores the impact of digital inclusive finance (DIF) on carbon emissions and the intrinsic mechanism of green technological innovation from a spatial perspective by constructing a spatial econometric model, a mediating effect model, and a threshold model. The results show that DIF significantly inhibits carbon emissions, exhibiting a spatial spillover effect. The transmission mechanism from a spatial perspective shows that green technological innovation plays a partial mediating role between DIF and carbon emissions, with the mediating effect accounting for approximately 59.47%. The heterogeneity analysis suggests that the impact of DIF on the reduction of carbon emissions is more pronounced in large and medium-sized cities and eastern regions. Further discussion reveals that the carbon reduction effect of DIF is also influenced by green technological innovation and industrial structure upgrading, showing threshold effects with marginal decreases and gradual increases, respectively.

Towards Carbon Neutrality in Agglomeration: Impact of Eco-Industry Development on Urban Carbon Emission Efficiency

Ecological industrial parks (EIPs) play a pivotal role as primary drivers of China’s industrial green transformation, facilitating the enhancement of urban carbon emission efficiency (UCEE) and the realization of green sustainable development. This study empirically investigates the effects of EIP policies on UCEE through quasi-natural experiments, utilizing data from 282 prefecture-level cities in China spanning from 2006 to 2021. Employing a multi-period difference-in-difference (DID) method, the findings are as follows: (1) The implementation of EIP policies leads to a 2.5% average increase in UCEE. (2) Event analysis reveals certain lagging characteristics in the promoting effect of EIP policies on the carbon emission efficiency of pilot cities. (3) EIP construction primarily enhances UCEE by reinforcing agglomeration effects and elevating innovation ability. (4) The promoting effect of EIP construction is more pronounced in the eastern and central regions, as well as in non-resource-based cities within different regions. Drawing from the empirical results, this study provides pertinent recommendations for EIP construction, offering theoretical guidance to policymakers and managers in crafting sustainable development strategies.

The Influence of Digital Economy on The Vitality of Urban Double Innovation

Under the new development pattern, the rapid development of digital economy is becoming the core force to change the global economic and social structure. At the same time, China is speeding up the conversion of old and new kinetic energy, and how to activate China's dual-innovation vitality is the focus of attention from all walks of life. Based on this, this project, based on the panel data of 285 prefecture-level cities in China from 2011 to 2019, studies the influence of regional digital economic development index on urban innovation vitality through two-way fixed effect model and intermediary effect model. It is found that the digital economy can promote the promotion of urban innovation vitality, and this conclusion is still valid after replacing the robustness test of the explained variables. The further mechanism test shows that the upgrading of industrial structure is an important intermediary variable for the digital economy to enhance the dual-innovation vitality of cities, and the digital economy can promote the dual-innovation vitality of cities through the upgrading of industrial structure.

Impact of industrial policy on urban green innovation: empirical evidence of China’s national high-tech zones based on double machine learning

Effective industrial policies need to be implemented, particularly aligning with environmental protection goals to drive the high-quality growth of China’s economy in the new era. Setting up national high-tech zones falls under the purview of both regional and industrial policies. Using panel data from 163 prefecture-level cities in China from 2007 to 2019, this paper empirically analyzes the impact of national high-tech zones on the level of urban green innovation and its underlying mechanisms. It utilizes the national high-tech zones as a quasi-natural experiment and employs a double machine learning model. The study findings reveal that the policy for national high-tech zones greatly enhances urban green innovation. This conclusion remains consistent even after adjusting the measurement method, empirical samples, and controlling for other policy interferences. The findings from the heterogeneity analysis reveal that the impact of the national high-tech zone policy on green innovation exhibits significant regional heterogeneity, with a particularly significant effect in the central and western regions. Among cities, there is a notable push for green innovation levels in second-tier, third-tier, and fourth-tier cities. The moderating effect results indicate that, at the current stage of development, transportation infrastructure primarily exerts a negative moderating effect on how the national high-tech zone policy impacts the level of urban green innovation. This research provides robust empirical evidence for informing the optimization of the industrial policy of China and the establishment of a future ecological civilization system.

Understanding China's CO2 emission drivers: Insights from random forest analysis and remote sensing data

China has become the world's largest emitter of carbon dioxide, putting significant pressure on the government to reduce emissions. This study analyzes the driving factors of carbon emissions in 281 prefecture-level cities in China from 2003 to 2019, based on carbon emission data matched with the locations of thermal power stations and nighttime light data. Firstly, we compare the accuracy of multivariate linear regression and random forest models, finding that the random forest regression yields superior results. Then, we rank the impact of various factors using the random forest method, revealing that population, economic development, and industrialization are the top three influencing factors. The interaction between population and economic development explains 68.5% of carbon emissions, with regional variations in the ranking of influencing factors. The main policy implications of this study are as follows: firstly, there is no need to overly concern about the impact of population growth on carbon emissions, and policies regarding fertility can be adjusted flexibly; secondly, controlling urbanization to a certain extent is conducive to achieving efficient low-carbon cities; thirdly, during the process of industrialization, carbon emissions inevitably increase, and it is advisable to accelerate industrialization to reach a turning point as soon as possible.

Beggar-thy-neighbor: Carbon leakage within China's pilot emissions trading schemes

The differences in the market liquidity of eight pilot emissions trading schemes (ETS) and the economic development of cities within the provincial-level ETS raise carbon leakage risks among the pilot cities. Utilizing panel data and DID models for 266 prefecture-level cities in China from 2006 to 2019, the empirical analysis reveals several key findings. Firstly, at the provincial level, the Tianjin pilot is found to have significantly increased CO2 emissions, potentially linked to carbon spillover from Beijing. Additionally, at the prefecture-level city level, certain cities in Guangdong Province and Fujian Province exhibit significant increases in CO2 emissions, indicating carbon transfer within the pilot ETSs. Secondly, all three spatial spillover effect tests demonstrate a notable carbon spillover effect between pilot cities. Lastly, the analysis of the moderating effect suggests that administrative intervention within the ETS and market mechanisms have limited impact on carbon spillover between pilot cities, while administrative intervention outside the ETS significantly enhances carbon leakage between pilot cities, primarily driven by carbon transfer resulting from state-owned enterprises' support for government emission reduction actions.

Migrants Subjective Well-being in Big Cities of China: Based on Self-rating Social Status and Social Integration

Promoting subject well-being of migrants could give full play to the advantages of talent's resource. Social position and social inclusion of migrants could be the key to pursue a people-centered, new type of urbanization and bring about rural migrants settling in cities. There is a lack of studies focusing on social comparison and social inclusion of migrants with the point of geographical features. Using the data collected from China Migrants Dynamic Survey in 2014, the relations among object socioeconomic status and self-rating social status as well as subject well-being of migrants in one municipal district and seven prefecture-level cities of China was examined by adopting multilevel linear regression model, which includes both mediating variables and moderating variables. Several conclusions are drawn as follows: 1) Migrants subjective well-being is affected by their objective socioeconomic status. Whilst migrants comparing themselves with local relatives and colleagues, as we call it self-rating social status, plays a part in mediating relations between object socioeconomic status and subject well-being, especially when the object socioeconomic status refers to migrants household monthly income, certain types of occupations (including civil servants, clerks and the self-rated) and homeowners in the host city. 2) When compared their socioeconomic status with locals in the host cities, including economic status and respect for themselves, the deeper the migrants are merging into cities and social networks, the weaker the relationship between self-rating social status and subjective well-being will be. In other words, social inclusion among migrants do negatively regulates the relations above. 3) However, there is no evidence that the higher the acceptance degree of local residents in host cities to migrants, the deeper the impact of the respect for migrants on subjective well-being will be. Obviously, the acceptance degree of local residents could not significantly moderate the relations between respect for migrants and their subject well-being. Based on the above research conclusions, this paper suggests that for building a harmonious society and improving the quality of urbanization, equal treatment of migrants and locals should be identified and dealt with. Furthermore, Therefore, we must speed up migrants to blend into the society in the cities.

Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities

Clean air policy is an important mechanism for improving the urban environment and promoting green economic development. Green total factor productivity (GTFP) is an important way to measure these impacts. We apply the super-efficiency slack-based measure model, considering undesirable output, and the Global Malmquist-Luenberger index to measure the GTFP of 278 prefecture-level cities in China from 2005 to 2020. We find that GTFP growth is driven by both green technology progress (GTC) and green technology efficiency change (GEC). The traditional total factor productivity is overestimated, because energy and environmental factors are not considered. GTFP growth is higher in the cities in the eastern coastal regions compared to the western regions. We analyze the effect of clean air policy on GTFP using a difference-in-differences model and spatial-difference-in-differences model, and further conduct a heterogeneity analysis and mechanism analysis. The results show that clean air policy promotes GTFP growth. In addition, there is a significant negative spatial spillover effect with respect to the impact of clean air policy on GTFP. The heterogeneity analysis results show that the impact of clean air policy on GTFP growth is lower in resource-based cities and cities in the northern region, compared with non-resource-based cities and cities in the southern region. Further, the impact of clean air policy on GTFP growth is mainly achieved through GTC, GEC, innovation, and financial development. In resource-based cities and cities in the northern region, clean air policy decreases GTFP by inhibiting GTC, innovation, and financial development.

Can digital economy development contribute to urban carbon emission reduction? - Empirical evidence from China

In the context of global digitalization, fostering the expansion of the digital economy holds immense importance in promoting energy efficiency and reducing emissions. Utilizing a sample of 281 prefecture-level cities in China from 2003 to 2019, this research analyzes the impact of the digital economy on urban carbon emissions in China. This study employs various methods, including principal component analysis, fixed-impact model, and mediating effect model. Based on the research findings, the development of the digital economy has the potential to significantly reduce carbon emissions in metropolitan areas. Moreover, these effects are especially noticeable in cities located to the east of the Hu Huanyong Line. These cities are characterized by limited reliance on resources and a high level of marketization. Further research reveals that promoting technical innovation and modernizing industrial structures can reduce the intensity of carbon emissions in metropolitan areas. This study provides empirical evidence supporting the effective reduction of carbon emissions in developing countries during the evolution of the digital economy. It acts as a crucial cornerstone for guiding policies and executing strategies aimed at fostering top-tier economic development in the future. The findings of this study confirm the inhibitory effect of the digital economy on urban carbon emission intensity. However, this study has limitations in data samples, research scope, and depth of mechanism analysis, which prevent a full exploration of the spatial spillover effect of the digital economy and other factors. Therefore, the conclusions drawn in this study can only provide empirical evidence for identifying the relationship between the digital economy and carbon emission intensity to a certain extent. Future research should aim to expand on these aspects.

Analysis of the impact factors of industrial structure upgrading on green total factor productivity from the perspective of spatial spillover effects

Green development has already been a vital part of China's high-quality economic progress in the future, and accelerating the restructuring and improvement of the industrial structure plays a crucial roll in promoting a regional green economy. In this article, based on the data of 278 prefecture-level cities in China from 2011 to 2020, the SBM directional distance function and Malmquist-Luenberger (ML) index are used to gauge regional green total factor productivity (GTFP). The spatial Durbin model is also introduced to investigate the spatial spillover mechanism of GTFP and its influencing factors under the optimized and upgraded industrial structure. The study indicates that the optimization of the industrial structure have an important effect in promoting the growth of GTFP. Specifically, industrial structure integration has a greater bearing on the increase in GTFP, while there is a difference in the effectiveness of industrial structural advancement and rationalization of GTFP. Economic growth level inhibits the enhancement of GTFP, and urbanization level and industrial agglomeration have a significant negative impact on the enhancement of GTFP in the spatial dimension. On a different hand, foreign investment degree and government intervention level have a significant positive affect on regional GTFP. In addition, this study fills the research gap of the regional industrial structure upgrading influence on GTFP, which has great theory and practice value for promoting China's high quality growth of green economy.

Has green finance policy promoted ecologically sustainable development under the constraints of government environmental attention?

This study aimed to reveal how China's green finance reform and innovation demonstration zone policy affects ecologically sustainable development under the constraints of government environmental attention. Employing multi-period DID (Difference-in-Difference) and DDD (Difference-in-Difference-in-Difference) as the base model, the study tested the mechanism of the policy's effect on ecologically sustainable development, using panel data from 277 prefecture-level cities in China from 2006 to 2020. Endogeneity tests including Two-Stage Least Squares (2SLS), counterfactual tests, and other robustness checks, were employed to enhance the study's validity. The research findings are as follows: (1) The policy effectively promotes ecologically sustainable development, and this conclusion remained valid even after conducting several robustness tests. (2) The more pronounced the government's emphasis on environmental preservation, the greater its efficacy in fostering ecologically sustainable development. (3) The stimulating effect of the policy on ecologically sustainable development is more pronounced in cities with higher ecological quality and a larger population. This study not only offers new analytical perspectives for comprehensively investigating the green finance policy but also emphasizes that enhanced policy outcomes hinge on the implementation of green financial reforms and innovations tailored to local conditions. Additionally, it provides valuable policy insights for optimizing the government's role in fostering ecologically sustainable development. (e.g., optimizing the governmental role in fostering ecologically sustainable development, enhancing both the scope and intensity of green finance policy, and harnessing the synergies between green finance policy and environmental protection policy).

Nexus between carbon emissions and local debt risk: Evidence from China's prefecture-level cities

Debt risk is an externality of carbon emissions in the greening transformation process. Based on panel data of 171 prefecture-level cities in China from 2012 to 2020, this article empirically analyzed the influence and mechanism of carbon emissions on local debt risk. The results can be concluded as follows: (1) Carbon emissions will significantly induce local debt risk. After considering the endogenous problem and serial robustness tests, the conclusions above are still valid. (2) Local debt risk itself has a cumulative expansion effect stimulate by carbon emissions. And carbon emissions will strengthen the depth of local debt risk with the increase of local debt risk. (3) The moderating impact of carbon emissions on local debt risk has heterogeneous characteristics, with different industrialization processes, developmental level of scientific and technological innovation, and corporate environmental management regulation. This article not only provides a new evidence for carbon emissions externality from local debt risk perspective, but also provides a useful reference for local governments to enhance debt risk governance, and orderly implement reduction action of carbon emissions.