Prefecture-level Cities In China Research Articles

The Influence of New-Type Urbanization and Environmental Pollution on Public Health: A Spatial Durbin Model Study

The rapid pace of urbanization in recent years, accompanied by the tension between urbanization and environmental pollution as well as public health, has become increasingly prominent, potentially constraining the normal pace of urbanization development, environmental sustainability and public health enhancement. This paper aims to clarify the relationship between new urbanization, environmental pollution and public health from both local and spatial perspectives, using a spatial Durbin model and a mediating effects model based on panel data from 275 prefecture-level cities in China from 2011 to 2020 and to test the existence of regional heterogeneity with a sub-sample of three major regions: eastern, central and western China. After incorporating environmental pollution as a variable across the entire scope of China, it was found that the new-type urbanization was related to public health in a ‘positive U-shaped’ form in terms of both local and spatial spillover effects (β2 = 14.5620, β3 = −17.8938, p < 0.05; θ2 = 19.2527, θ3 = −29.0973, p < 0.1) and environmental pollution exerts a negative impact on public health (β1 = 6.3704, θ1 = 2.5731, p < 0.05). A “reverse U-shaped” local effect was observed between new-type urbanization and environmental pollution (β2 = 0.6281, β3 = −0.5315, p < 0.05). Environmental pollution plays a partially mediating role in the impact mechanism of new-type urbanization on public health. There was regional heterogeneity in the relationship between new-type urbanization, environmental pollution and public health. The empirical results for the western regions and the whole of China were generally consistent, but the differences were significant between the eastern and central regions. In the eastern region, new-type urbanization and public health were related in an ‘inverted U-shaped’ form from the perspective of local and spatial spillover effect, and in the central region, there was an ‘inverted U-shaped’ form from the perspective of local effect. There was a threshold effect relationship between new-type urbanization and environmental pollution and between new-type urbanization and public health. At the same time, there was regional heterogeneity in the relationships between the three. Therefore, this paper argues that governments should formulate scientific urban planning and sustainable development policies that take into account the actual situation of each region and aim to promote sustainable urbanization, environmental quality and public health as a whole.

Can environmental regulation promote high-quality economic development?: Evidence from China

This study utilizes a dataset comprising 284 prefecture-level cities in China, covering the period from 2005 to 2020. Its objective is to empirically examine the influence of environmental regulation on the attainment of high-quality economic development. The assessment of urban environmental regulation and high-quality economic development is conducted in a rational manner. The results of the study indicate that the implementation of more stringent environmental regulations has the potential to improve the overall quality of urban economic growth. This conclusion provides support for Porter's theory. The primary objective of environmental regulation is to foster sustainable economic growth by encouraging the use of environmentally friendly manufacturing technologies, improving production efficiency, and attracting skilled individuals. The results of heterogeneity testing indicate that there are no significant regional disparities in the promotional impact of environmental regulation on the quality of economic development. This suggests that the government's environmental regulation plan can be successfully implemented to foster high-quality development. However, it is worth noting that the effectiveness of environmental regulation measures towards the end of governance appears to be somewhat limited in promoting high-quality development.

Can financial subsidy increase electric vehicle (EV) penetration---evidence from a quasi-natural experiment

Electric vehicles (EVs) are considered a promising solution for reducing emissions in urban transportation and addressing energy crises. Several countries, including China, have implemented direct financial subsidies to encourage the adoption of EVs. However, there is a lack of comprehensive evaluation regarding the effectiveness of these subsidies and their interaction with non-financial incentive policies. Additionally, the design of subsidy policies can be endogenous, potentially leading to biased estimations of their effects on EV penetration. To address these issues, this study utilizes a “quasi-natural experiment" approach, taking advantage of the gradual reduction of nationwide EV subsidies by the Chinese government due to financial constraints, rather than market conditions, thus mitigating the endogeneity problem. The study collects panel data from 224 prefecture-level cities in China and employs a modified panel data fixed effects model to quantify the impact of financial subsidies on EV sales and market shares. The analysis focuses on subsidy variations during six periods. The main empirical findings are as follows: (1) 1 % increase in purchase subsidies leads to a 1.36 % increase in EV sales and a 2.31 % increase in EV market share. (2) Non-financial policies, such as parking benefits, promotional goals, and restrictions on the number of vehicles, also contribute to boosting EV sales. (3) The effects of purchase subsidies vary across cities with different socio-economic conditions. (4) Some non-financial policies are found to enhance the positive effects of subsidy policies.

High-speed rail and distribution of economic activities: Evidence from prefecture-level cities in China

Creating new subcenters around suburban transport nodes is a popular policy choice for urban development. In this study, we investigate how high-speed rail stations reshape economics activities in less populous cities. Employing night-light data at the pixel level, we demonstrate that the establishment of a new station has resulted in a flattened economic density gradient for Chinese prefecture-level cities. Notably, however, the gravitational core of urban economic activity does not exhibit a discernible shift towards the station area. This evidence suggests that the station area has not formed into a new subcenter; instead, it might have contributed to urban sprawl. We show that the formation of a new subcenter is tied to several pivotal determinants, which include the level of urban agglomeration, the distance to the original urban center, and government investment in the station area. Further analysis, grounded in a comprehensive dataset of land transactions, reveals that there has been no significant land price appreciation within the station area. This finding raises questions regarding the effectiveness of government-led new town development around the station area.

Does emission trading system improve the urban land green use efficiency? Empirical evidence from Chinese cities.

Maximizing socioeconomic and environmental benefits with minimal investment in urban land resources is a key concern for sustainable urban development. The emission trading system is an important strategy of the Chinese government to control environmental pollution and promote green development, but whether it improves urban land green use efficiency is still unclear. Combining the concept of green development with urban land use efficiency, this paper uses the super-efficiency slack-based measure (SBM) model with undesirable outputs to measure the land green use efficiency of 261 prefecture-level cities in China from 2003 to 2017. In addition, the propensity score matching difference-in-differences (PSM-DID) method and the mediating effect model were used to test the impact of the China's emission trading system on urban land green use efficiency and behind the mechanism. According to the findings, China's emission trading system has significantly improved urban land green use efficiency, compared with that in nonpilot cities, urban land green use efficiency in pilot cities has increased by 10.40%. Moreover, the policy effect of the emission trading system is more significant in resource-based cities and cities with a high intensity of environmental regulations. Further mechanism analysis reveals that green technology innovation and industrial structure upgrading are effective transmission mechanisms for China's emissions trading policy to improve urban land green use efficiency. The findings provide policy implications for promoting the sustainable use of urban land resources and advancing the coordinated development of urban socioeconomic and ecological environments.

Enhancing economic competitiveness analysis through machine learning: Exploring complex urban features.

Urban economic competitiveness is a fundamental indicator for assessing the level of urban development and serves as an effective approach for understanding regional disparities. Traditional economic competitiveness research that relies solely on traditional regression models and assumes feature relationship theory tends to fall short in fully exploring the intricate interrelationships and nonlinear associations among features. As a result, the study of urban economic disparities remains limited to a narrow range of urban features, which is insufficient for comprehending cities as complex systems. The ability of deep learning neural networks to automatically construct models of nonlinear relationships among complex features provides a new approach to research in this issue. In this study, a complex urban feature dataset comprising 1008 features was constructed based on statistical data from 283 prefecture-level cities in China. Employing a machine learning approach based on convolutional neural network (CNN), a novel analytical model is constructed to capture the interrelationships among urban features, which is applied to achieve accurate classification of urban economic competitiveness. In addition, considering the limited number of samples in the dataset owing to the fixed number of cities, this study developed a data augmentation approach based on deep convolutional generative adversarial network (DCGAN) to further enhance the accuracy and generalization ability of the model. The performance of the CNN classification model was effectively improved by adding the generated samples to the original sample dataset. This study provides a precise and stable analytical model for investigating disparities in regional development. In the meantime, it offers a feasible solution to the limited sample size issue in the application of deep learning in urban research.

THE IMPACT OF THE AGRICULTURAL PRODUCTIVE SERVICE INDUSTRY ON THE INCOME GAP BETWEEN URBAN AND RURAL RESIDENTS: EVIDENCE FROM 276 CHINESE PREFECTURE-LEVEL CITIES

Based on the panel data of 276 prefecture-level cities in China from 2009 to 2018, this paper explores the impact of the agricultural productive service industry on the income gap between urban and rural residents by constructing the spatial econometric model and threshold regression model. The results show that the development of the agricultural productive service industry has a significant spatial spillover effect, which has a significant restraining effect on widening the income gap between urban and rural residents in the neighboring areas. Developing the agricultural productive service industry in the eastern and central regions significantly narrows the income gap between urban and rural residents. There is a significant urbanization threshold effect on the impact of the agricultural productive service industry on the income gap between urban and rural residents. When the urbanization level crosses the threshold of 3.7469, the role of the agricultural productive service industry in reducing the income gap between urban and rural residents increases significantly. Therefore, this paper proposes accelerating the development of the agricultural productive service industry, improving the urban–rural integration mechanism, strengthening the coordinated development between regions and playing the external effects of the agricultural productive service industry.

The carbon emission reduction effect and mechanism analysis of digital economy: Evidence of prefecture-level cities in China

ABSTRACT This study investigates the impact and mechanisms of carbon emission reduction associated with digital economy development, utilizing data from 265 prefecture-level cities in China during the period of 2003 to 2019. The comprehensive index of digital economy development at the prefecture level is evaluated using the entropy method, followed by empirical analysis employing the dual fixed effect model. The findings confirm a significant improvement in urban carbon emission reduction resulting from the digital economy. Mechanism analysis reveals that the digital economy enhances the carbon emission reduction effect in cities by promoting urban green innovation and reducing energy consumption intensity. Additionally, heterogeneity analysis demonstrates that the carbon reduction effect of digital economy development is influenced by factors such as city location, population size, and development type. By shedding light on the relationship between the digital economy and carbon emission reduction, this study offers valuable insights into the mechanisms through which the digital economy contributes to sustainable urban development.

Can digital economy improve employment structure?-Mediating effect based on a spatial Durbin model.

Based on the panel data of 283 prefecture-level cities in China from 2011 to 2019, this study constructed an index measurement system of digital economy, economic agglomeration, innovation and entrepreneurship, and employment structure. The index of digital economy was developed by entropy weight method, and the double-fixed spatial Durbin model was constructed based on the intermediary effect from the spatial perspective to determine the direct effect, indirect effect, and total effect of the digital economy, economic agglomeration degree, and innovation and entrepreneurship on employment structure. The results indicated a significant spatial correlation between the three aspects, i.e., digital economy can significantly optimize the employment structure, with an evident spillover effect. The mechanism analysis revealed that the level of innovation and entrepreneurship poses a stronger intermediary effect than the degree of economic agglomeration, and the digital economy in the eastern region directly impacts the urban employment structure; however, the influence of digital economy on the employment structure is significantly higher in small- and medium-sized cities than in large-sized cities.

Analysis of the impact of local government debt policy on the financial ecological environment-based on debt level and debt structure perspectives

This paper employs panel data from 227 prefecture-level cities in China spanning the period from 2000 to 2020 to investigate the effects and influences of local government debt policies on the financial ecological environment. Considering regional economic foundation, financial development, government governance, and the construction of the social credit system, our analysis reveals the following outcomes regarding debt level and debt structure: Firstly, we find that higher debt levels and an increased proportion of hidden debt at the local government level have impacts on various dimensions of the financial ecological environment. Specifically, debt expansion facilitates regional economic foundations and financial development but hampers government governance and the construction of the social credit system, leading to a deterioration in the development of the financial ecological environment. Furthermore, employing a threshold regression model, we have not identified a significant nonlinear relationship in this context. Secondly, local government debt exhibits a reverse spatial spillover effect on the financial ecological environment of surrounding regions, contrasting with the effects observed within the local area. This effect manifests as the enhancement of the financial ecological environment in neighboring areas.

Whether the agricultural energy rebound offsets the governance effectiveness of the China's natural resource audit policy?

Due to the absence of a Chinese agricultural environmental trading market and the national government's "dual carbon" goal, government audit reform has been an important central government tool to ensure parallel economic and environmental performances and promote the green transformation of agriculture; however, in practice, the energy rebound effect may offset this effort. Based on panel data from 206 prefecture-level cities in China from 2011 to 2019, this study took China's leading official accountability audit of natural resources (LOAANR) pilot as a standard natural experiment to explore the policy effects and action paths of LOAANR on the agricultural direct energy rebound (DAER) and the indirect energy rebound (IAER), for which a spatial difference-in-difference (SDID) model was used. The results show that the LOAANR resulted in an agricultural energy rebound (AER) in the pilot cities and also had positive spillover on the AER in neighboring cities through demonstration, imitation, and training effects. It was also found that this effect was strongest in developed and agricultural non-focus cities. Finally, the mechanism test found that the LOAANR positively promoted AER in the pilot cities and negatively affected the AER in neighboring cities through agricultural energy efficiency (ATFEE). Therefore, several policy recommendations that can refine the LOAANR policy audit checklist and promote the green transformation of agriculture were presented.

Does green innovation reduce carbon emission intensity of Chinese cities? Analysis based on GS2SLS

ABSTRACT In the 14th Five-Year Plan, China’s economic and social development aims to focus on carbon peaking and carbon neutrality. On the basis of panel data of 284 prefecture-level cities in China from 2011 to 2020, this study uses the generalized spatial two-stage least squares method (GS2SLS) to analyse empirically the relationship and mechanism between the green innovation and carbon emission intensity（CEI） of Chinese cities. The research reveals several findings. (1) The CEI of Chinese cities has a significant spatial spillover effect. Moreover, green innovation has reduced the CEI of Chinese cities. The robustness and endogenous tests further verified this conclusion. (2) The carbon emission reduction effect of green innovation shows significant regional heterogeneity, which is more significant in eastern regions and cities with high innovation capabilities. In contrast, this outcome is not significant in regions with weaker innovation capabilities and in the central and western regions. (3) Green innovation mainly reduces the CEI of Chinese cities by promoting the upgrading of industrial structures. A higher level of digital economy development will also have a significantly positive catalytic effect on green innovation to inhibit CEI.

Has China’s Free Trade Zone policy promoted the upgrading of service industry structure?: Based on the empirical test of 185 prefecture-level cities in China

As the pillar industry of China’s national economy, the service industry has always experienced a lag in structural upgrading. As an important measure of China’s institutional innovation, China’s Free Trade Zone (FTZ) policy is of great significance for promoting the development of the service industry. Based on the panel data of 185 prefecture-level cities in China from 2010 to 2019, this paper empirically tests the impact of the FTZ policy on the upgrading of service industry structure by using the progressive difference-in-differences model. The results show that the FTZ policy can promote the upgrading of service industry structure, and the effect is enhanced with the extension of time. The heterogeneity test shows that the impact of the FTZ policy on the structural upgrading of the service industry is mainly reflected in promoting the development of the information service industry as well as the leasing and business service industry. The transmission mechanism test shows that the FTZ policy can promote the structural upgrading of the service industry by improving the level of trade facilitation and investment facilitation.

Carbon intensity constraint, economic growth pressure and China's low-carbon development

Within the context of promotion tournaments among local governments, the management of economic growth goals plays a crucial role in China's economic development. Despite China's rise as the second-largest economy globally, it has also emerged as the largest emitter of carbon emissions. Since the implementation of the 12th Five-Year Plan in 2011, the Chinese central government has made carbon intensity targets mandatory indicators for national economic development. This has prompted local governments to pursue low-carbon growth and adjust their economic growth targets (EGT) to comply with carbon intensity constraints. In this study, a sample of 282 prefecture-level cities in China is used to empirically examine the impact of carbon intensity constraints on total factor carbon emission efficiency (TCE) using the intensity difference-in-differences (DID) framework. The study also emphasizes the role of the transmission channel for economic growth pressure (EGP). The findings of the study reveal several key results. Firstly, the implementation of carbon intensity constraints leads to an average increase of 8.24% in total factor carbon emission efficiency (TCE), which is supported by robustness tests, parallel trend analysis, and placebo tests. Secondly, these constraints result in an average decrease of 0.1828 in local governments' economic growth targets (EGT) and a reduction of 0.1269 in economic growth pressure (EGP). Thirdly, cities with a higher proportion of secondary industry experience a more significant mitigation effect, although the promotion of provincial EGT hinders this effect. Fourthly, synergistic policies can effectively promote low-carbon development, and government expenditure on technology and marketization can facilitate a positive relationship between carbon intensity constraints and TCE. Lastly, the effects of carbon intensity constraints vary across the east, middle, and west regions, suggesting the presence of heterogeneity. The article proposes a shift in the assessment of lower governments by superior governments, from growth assessment to low-carbon growth assessment.

The Carbon Emission Reduction Effect of Carbon Emission Trading Policy in China

The carbon emission trading policy attributes carbon dioxide emission rights to commodities, representing an important exploration to reduce carbon emissions by the market mechanism. Since 2013, China has implemented the carbon emission trading policy. In order to study whether the carbon emission reduction effect of emission trading policy in pilot areas and what is the pathway, this paper uses multi-period difference-in-differences method and the medintion effect method. An empirical analysis of panel data from 283 prefecture-level cities in China between 2006 and 2019.The research findings demonstrate that: (1) The policy about carbon emission trading significantly reduced carbon emissions,which is still valid after a series of robustness tests, and had a synergistic effect. (2) The policy primarily promotes carbon dioxide emission reduction through innovation in green technology and adjustments in industrial structure. (3) In comparison to the eastern and western regions, the policy performs better in central regions. Furthermore, the effectiveness of emission reduction depends on the intensity of environmental regulations, thus, stricter regulations are more conducive to carbon reduction. This paper provides strong evidence to the expansion of carbon emission trading pilots, and guides the operation of carbon emission trading market in China.

Smart city construction and urban green development: empirical evidence from China

Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions.

Is prefecture-level city a “city” in China: a critical review

ABSTRACT The definition and boundaries of cities often determine how research is undertaken due to the areal units used to provide geo-located data and thus affect the research findings. Prefecture-level cities are popular city-equivalent statistical units in China, particularly in studies of inter-city mobility. Most prefecture-level cities in China have been delineated as meso-scale administrative divisions for territorial governance through various approaches of administrative annexation. This study takes a critical look at the city definition in China and summarizes two critical challenges that emerge when prefecture-level cities are adopted as city-equivalent statistical units. The first challenge is that the population and other socioeconomic statistics of different prefecture-level cities are incomparable since a large amount of land administered by such cities is functionally rural. The second challenge is that, because prefecture-level cities cannot represent the real functional areas that are based on a daily labor-shed concept, the estimation of inter-city mobility could be largely erroneous by conflating the real inter-city travel with the de facto intra-metropolitan travel such as daily commuting. While the first challenge has long been addressed by scholars and eventually by the national government of China in 2008, the second challenge remains to be solved. These two challenges demand rigorous attempts to delineate cities in China considering integrated economic and social units. This study sheds light on how delineation of administrative boundaries affects our understanding of city hierarchy and spatial interactions. Its implications are not limited to China but applicable to other countries and regions.

Does the Collaboration of Digitalization Foster Regional Green Development?

The collaboration of digitalization refers to a comprehensive digital governance system that achieves cross-regional digital industrialization and deep integration of industrial digitization through the construction of digital infrastructure, which paves the way toward regional sustainability. However, little is known about whether and to what extent regional digital collaboration contributes to green development. Furthermore, the specific role of digital collaboration in greening the regional economy and society remains unexplored. Thus, this paper tests the relationship between digital collaboration, business environment, and regional green development by using data from 285 prefecture-level cities in China from 2008 to 2022. The findings suggest that: (1) the hysteresis phenomenon of the “green dividend effect” response to regional digital collaboration is present; (2) digital collaboration in eastern cities positively impacted (but lagged) the greening of the economy and society, but cities in central and western regions negatively impact this process; (3) the business environment mediates the relationship between the lagged digital collaboration and regional green development, and it positively moderates the relationship between both the current and lagged digital collaboration and regional green development. By elucidating the relationship between digital collaboration, business environment, and regional green development, contributions have been made to previous digital innovation literature, and management insights have been provided for how regions can promote green development in the digital age.

How do local government fiscal revenue targets affect green technology innovation in China?

ABSTRACT The process of economic development in China cannot be separated from the ‘shadow’ of government target intervention. Under the Chinese system of fiscal decentralization, constraints created by local government fiscal revenue targets (CCFRTs) will have a series of influence on development economically and socially. Based on the fiscal revenue target data revealed in the government work reports of 281 prefecture-level cities in China from 2006 to 2019, this paper explores the influence of CCFRTs on green technology innovation (GTI). The findings are as follows: first, CCFRTs significantly inhibits GTI. Second, Spatial Durbin model analysis shows that CCFRTs has significant negative spatial spillover effect on GTI. Third, CCFRTs can affect GTI through the optimization of industrial structure, the level of human capital, and the degree of opening-up, technological progress and economic growth. Fourth, CCFRTs has an obvious threshold effect on GTI. Finally, the influence of CCFRTs on GTI has regional heterogeneity in central, eastern and western China. In the western and central regions, CCFRTs significantly restrains GTI significantly, while in the eastern region, CCFRTs significantly promotes GTI.

Carbon Emission, Air Pollution, and Total Factor Productivity: Evidence from Prefecture-Level Cities in China

Based on the instrumental variable method and the panel data of 283 prefecture-level cities in China from 2004 to 2016, we explore the relationship between carbon emission, air pollution, and total factor productivity (TFP). The results show that: (1) Both carbon emission-induced and air pollution-induced environmental regulations positively promote TFP. For every 1% increase in the two indicators of the intensity of environmental regulation, carbon emission, and air pollution, TFP will increase by 1.7150 percentage points and 0.6366 percentage points respectively. (2) Carbon emission-induced and air pollution-induced environmental regulation have similar coefficients on TFP, indicating that the effects of the two are synergistic. Carbon emission has a greater impact on TFP, so enhancing environmental regulation on carbon emission can better promote the improvement of TFP. (3) Financial scale and government intervention have a significant intermediary effect between environmental regulation in both aspects and TFP.