Prefecture-level Cities Research Articles

Impact of high-speed railway network improvement on consumption synergy in Beijing-Tianjin-Hebei region

This paper investigates the impact of high-speed rail (HSR) network improvement on the consumption synergy of the Beijing-Tianjin-Hebei region by using the panel data of 13 prefectural-level cities from 2006 to 2021. The results show that: (1) The improvement of the HSR network in the Beijing-Tianjin-Hebei region has a significant positive impact on raising overall regional consumption levels. (2) The HSR network improvement has a heterogeneous impact on consumption in different cities within the Beijing-Tianjin-Hebei region. (3) The promotional effect on peripheral cities is greater than on central cities, thereby promoting the coordinated consumption development of the Beijing-Tianjin-Hebei region. The findings of this study have important policy implications, confirming that the construction of the HSR network can narrow the consumption gap within the region and promote consumption synergy across the region.

Effect of smart city construction on an urban transition to a low-carbon economy: evidence from China.

China is currently in a new era of an urban transition to a low-carbon economy and digital economic development. Smart cities, as an advanced form of information-based urban development, may be the key to the urban transition to low-carbon emissions. This paper examined the effect of smart city construction (SCC) on urban low-carbon transitions and its transmission mechanisms in China from the dual perspectives of reducing urban total carbon emissions (TCE) and improving urban total-factor carbon emission efficiency (TFCEE). Utilizing a multi-period difference in differences (DID) method, this study was conducted based on panel data of 245 Chinese prefecture-level cities from 2003 to 2021. The results demonstrated that SCC both reduced TCE and enhanced TFCEE. The effects of SCC were stronger in cities with more stringent environmental regulations. SCC achieved the dual effect of reducing TCE and enhancing urban TFCEE by promoting green technological progress and a low-carbon transformation of city residents' lifestyles. Moreover, optimization of the industrial structure was also a transmission mechanism for SCC to improve TFCEE. These conclusions provide an empirical basis for the SCC to empower low-carbon transitions of cities and help countries in different regions to transform the extensive urban development mode and promote urban low-carbon economic development.

How Does Digital Infrastructure Development Affect Housing Prices? A Quasi-Natural Experiment Based on the “Broadband China” Program

Currently, digital infrastructure development, as a key driver of economic growth in the new era, provides a new perspective for alleviating the current tremendous downward pressure on China’s real estate market. Based on data from 255 prefecture-level cities in China from 2005 to 2020, this study takes the “Broadband China” Program as a quasi-natural experiment and uses the time-varying difference-in-differences (DID) model to investigate mechanisms of impact of digital infrastructure development on housing prices. The empirical results show that the “Broadband China” Program has a significant positive impact on housing prices, with an average treatment effect of 8%. This primarily occurs through population agglomeration, income enhancement, and technological innovation. It has also a positive spatial spillover effect on housing prices. Overall, digital infrastructure development is a “double-edged sword”: while improving the quality of life and convenience, it will also bring about rising housing prices. Therefore, we should pay more attention to how to guide digital infrastructure development, including broadband networks, to reasonably regulate housing prices to promote the healthy development of China’s real estate market.

Research on the impact of manufacturing servitization on environmental pollution: spatial econometric analysis of sulfur dioxide based on 284 prefecture-level cities

Using China’s regional input–output table, the paper constructs indicators of manufacturing servitization, matches manufacturing servitization at the regional level with city data, and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide (SO2) emissions within the classical Environmental Kuznets Curve (EKC) framework. The results show that manufacturing servitization can reduce SO2 emissions. Producer servitization and consumptive services can both significantly reduce industrial SO2 emissions. Transportation and warehousing servitization, information servitization, leasing, and commercial servitization, technology research and development servitization significantly reduce SO2emissions; technology research and development servitization, in particular, have the largest influence coefficient, while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant. The study also found that servitization reduced the SO2 emissions through technological innovation and industrial structure upgrading.

Steering toward sustainability: Can dual circulation development mitigate CO2 emissions? —Evidence from China

To reduce greenhouse gas emissions and achieve high-quality economic development, China has proposed another development pattern called dual circulation development (CIR), along with the goals of “carbon neutrality and carbon peaking”. Based on the data of prefecture-level cities and above from 2006 to 2021, the fixed-effects model, 2SLS model, mediation model, threshold model, and spatial Durbin model are used to discuss the role of CIR in affecting CO2 emissions. Results demonstrate that (1) the overall CO2 emissions exhibit a decreasing trend from 2006 to 2021, and the CIR presents an upward trend. CIR and CO2 emissions show apparent geographical differences. (2) CIR effectively reduces CO2 emissions, and this effect exhibits clear heterogeneity of different regions, resource endowment, and pilot free trade zone. CIR mitigates CO2 emissions by enhancing technological innovation and promoting human capital mobility. Market scale and industrial structure optimization act as a “magnifying glass”, amplifying the impact of CIR on reducing CO2 emissions. (3) The negative spatial spillover effect of CIR on CO2 emissions shows a “V” shape characterized by strengthening and then weakening in the range of 0–700 km. At this point, the 700 km mark represents the decay boundary. Findings suggest that the government should enhance the domestic market environment and improve the quality of foreign trade to fulfill the role of CIR in mitigating CO2 emissions. These empirical evidence and feasible measures are provided for some countries to reduce CO2 emissions while promoting economic development.

How does urban industrial structure upgrading affect green productivity? The moderating role of smart city development

The concept of the smart city, which has recently gained prominence as a new urbanization model, represents a practical approach to achieving a balance between economic development and environmental protection. This article analyzes the effect of upgrading urban industrial structures on green total factor productivity (GTFP) and addresses a gap in evaluating the mediating role of smart city development. Utilizing panel data from Chinese prefecture-level cities, the study finds that internal advancements and diversification in industrial structures significantly enhance GTFP, while industrial structure rationalization displays a complex, non-linear correlation with GTFP. Moreover, smart city development is found to positively moderate the relationship between industrial structure and productivity, particularly in terms of outer-advancement, diversification, and rationalization. The moderating effect is evident in green technical efficiency rather than green technological innovation. Cluster analysis reveals significant effects in regions characterized by irrational, diversified, and naturally rational industrial structures. Additionally, the study identifies five impact mechanisms facilitated by smart cities, namely ICT, finance development, digitalization, smart governance, and social trust. These conclusions are of material significance to promote high-quality urban development.

How digital finance and green finance can synergize to improve urban energy use efficiency? New evidence from China

Accelerating the greening and digital transformation of the energy industry to enhance energy efficiency is pivotal for constructing a new energy system. The high-quality development of the energy sector necessitates the support of emerging financial forces. This study utilizes panel data from 279 prefecture-level cities spanning from 2011 to 2021, employing mediation and moderation models to verify the synergistic impact of digital finance and green finance on energy efficiency. Findings indicate that the synergy between digital finance and green finance enhances energy efficiency. Mechanism analysis reveals that this synergy promotes energy efficiency through advancements in green and digital technology innovations. Climate policy uncertainty positively moderates the process by which digital finance and green finance synergistically improve energy efficiency, enhancing the intermediary effects of digital and green technologies. Environmental regulations similarly exert positive moderation on the joint impact of digital finance and green finance on energy efficiency, yet their effects vary heterogeneously, with market-based environmental regulatory tools demonstrating superior policy outcomes. Moreover, the impact of the synergy between digital finance and green finance on energy efficiency exhibits heterogeneity across geographic regions, development timelines, resource endowments, and policy trial effects.

Promoting corporate independent innovation through judicial protection of intellectual property rights

This study examines the impact of judicial protection of intellectual property rights on firms' independent innovation. Using a staggered difference-in-differences model with panel data from Chinese manufacturing listed businesses (2014–2021) and the successive establishment of intellectual property courts in Chinese prefectural-level cities as a quasi-natural experiment, we find that establishing intellectual property courts in China encourages businesses to accumulate more technology-based intangible assets. Mechanism analysis suggests that judicial intellectual property protection enhances enterprises' independent innovation capacity by establishing a conducive institutional framework. This stimulating effect is particularly significant for industry-leading companies with technological supremacy. Heterogeneity analysis reveals that judicial intellectual property protection increases the generation of patents and trade secrets, with a more pronounced effect on firms receiving higher government research and development subsidies and better tax incentives. This study offers valuable insights for policymakers to encourage corporate independent innovation.

The spatial effects of innovation agglomeration on air quality in China: from the perspective of industrial development

ABSTRACT This study aims to explore the impact of innovation agglomeration on air pollution and industrial transformation within the context of China’s green development transition. We developed a general equilibrium model to theoretically explore these effects and employed an econometric analysis using panel data from 284 prefecture-level cities in China between 2005 and 2019 to empirically validate our findings. The main results are as follows: (1) Innovation agglomeration can significantly improve air quality, with a strong spatial spillover effect. (2) Innovation agglomeration can significantly promote transformation and upgrading of industrial structure, and it may also lead to the convergence of some industrial structures. Moreover, industrial structure transformation and upgrading partially mediates the relationship between innovation agglomeration and air pollution. (3) There is a nonlinear relationship between innovation agglomeration and air pollution. As industrial complementarity is developed, the effect of innovation agglomeration on air pollution enhances. These findings suggest that fostering innovation clusters and encouraging industrial diversification are key policy strategies for achieving sustainable urban development and improving environmental outcomes.

The impact and spatial spillover effect of traditional culture on urban green innovation: Empirical evidence from China

The issues of resource scarcity and environmental pollution has become huge challenges that all of humanity faces together. To resolve the issue, promoting urban green innovation capacity is important. This study uses 189 prefecture-level cities and above in China from 2011 to 2020 as samples, and empirically test the impact and spatial spillover effect of traditional culture on urban green innovation. This study finds that: (1) Traditional culture can improve the local green innovation and positively impact the green innovation in neighboring cities by radiation effect, and the conclusion remains valid after robustness tests; (2) Talent flow and data flow negatively moderate the positive impact of traditional culture on green innovation in local cities. In addition, from a dynamic perspective, traditional culture has a negative impact on green innovation in neighboring cities because of the siphon effect; (3) The spatial spillover effect of traditional culture on urban green innovation shows distinct heterogeneity due to the different regions and whether it is a low-carbon pilot city. This study verifies the important value of Chinese traditional culture in urban sustainable development, which is of great significance for the protection and inheritance of traditional culture and the improvement of urban green innovation.

What determines the synergy among urban systems? Evidences from the Yangtze River economic belt over 20 years

China's urbanization has reshaped landscapes, economies, and societies nationwide at unprecedented paces, yet inconsistent march among these processes has resulted in insufficient and unbalanced urban development. Here, we constructed a Population-Land-Economic-Social urbanization (PLESU) system with multiple elements and interaction flows, and explored the spatiotemporal dynamics and influencing factors of the coupling coordination degree (CCD) among PLESU system in 110 prefectural-level cities of Yangtze River Economic Belt (YREB) from 2000 to 2020. Results indicated that the CCD evolution exhibited significant path dependence during the past two decades, with considerable room for improvement. A key finding was that the low-quality development of land urbanization and social urbanization subsystems was the main factor for the lack of synergy among PLESU system, with land finance dependence and municipal investment confirmed to have significant impact on this. Furthermore, results also highlighted narrowing inter-regional differences in the CCD among downstream, midstream and upstream, revealing clustering of CCD in urban agglomerations, yet differing in their internal differentiation patterns and drivers. Exploring the synergy among urban systems will raise policymakers’ awareness of the necessity for embracing a holistic approach toward better sustainability by considering the insufficient and unbalanced nature of urbanization.

Can the ‘21st Century Maritime Silk Road’ initiative improve the opening-up of China’s coastal provinces?

The Belt and Road Initiative (BRI) serves as China’s blueprint and major strategy for opening-up in the new era. This study theoretically examines three mechanisms of the ‘21st Century Maritime Silk Road’ (CMSR) to promote the opening up of provinces and cities along the line, including the allocation, integration, and circulation mechanisms. Using 2009–2021 data from prefecture-level cities, this study designed a quasi-natural experiment based on the CMSR by combining propensity score matching (PSM) and differences-in-differences (DID) methods. The study findings show CMSR significantly promoted China’s opening-up. Various robustness tests demonstrate that our findings are robust. Mechanism analysis shows that CMSR improved China’s opening-up by promoting the flow of production factors, integrating domestic and international product markets, and accelerating circulation. Heterogeneity analysis shows that CMSR strongly influences large, coastal, and nonprovincial cities. These findings provide a new perspective for evaluating the policy effects of the 21st CMSR.

High-speed rail, resource allocation and haze pollution in China

The transport sector is crucial in influencing anthropogenic pollution. By employing Chinese prefecture-level city data from 2003 to 2019 and a sample of 443124 observations of industrial firms from 2003 to 2013, this paper treats the opening of high-speed rail (HSR) as a quasi-natural experiment and uses a multi-period difference-in-differences (DID) method to investigate the impact of HSR on haze pollution. The findings reveal that (1) HSR has a significant negative effect on cities' PM2.5 concentrations, and the result is held after a series of robustness checks; (2) the analysis based on Chinese industrial firm data also yields significant results in reducing smoke and dust emissions by HSR, providing micro-level understanding for the main conclusion; (3) at the firm level, heterogeneity derives from firm ownership, location, and industry; (4) the reduction in industrial firms' labor and capital distortion and resource misallocation play a crucial role in the HSR's impact on mitigating haze pollution; (5) at the city level, HSR reduces haze pollution by improving overall resource allocation across cities, and promoting the flow of capital to cities that are more developed and have higher returns. These results indicate that recognizing the causal relationship between HSR and haze pollution and the impact mechanism poses policy implications for inter-city transportation infrastructure development and pollution control.

The coordinated development among economy, society, energy, and environment and their impacts on public health in China's cities

As China's urban areas rapidly developed, prefecture-level cities faced challenges in the coordinated development of the economy, society, energy, and environment (ESEE), which could impact public health. Previous research had examined the interactions between the various ESEE systems and their effects on public health. However, relatively few studies had conducted comprehensive analyses across different systems and regions. This paper aimed to conduct an in-depth analysis in this field. First, it calculated the ESEE development levels using principal component analysis, the entropy method, and data from 278 Chinese cities between 2012 and 2021. Next, it employed a coupling coordination degree model, which reflects the degree of coordinated development between different systems, to explore the coordinated development levels and trends of the four ESEE systems in each prefecture-level city. Furthermore, this paper innovatively used a spatial Durbin model, incorporating ESEE coordination levels to investigate their impact on public health in local and surrounding areas. The results indicated that the positive impact of ESEE coordinated development on local public health was 0.5082, while the impact on surrounding areas was 2.0240. This influence was more pronounced in smaller cities, suggesting the need to enhance regional cooperation, balance developmental disparities, and promote ESEE coordinated development to improve public health.

Spatial spillover effect and driving factors of urban carbon emissions in the Yellow River Basin using nighttime light data

Yellow River Basin (YRB) is a pivotal region for energy consumption and carbon emissions (CEs) in China, with cities emerging as the main sources of regional CEs. This highlights their critical role in achieving regional sustainable development and China’s carbon neutrality. Consequently, there is a pressing need for a detailed exploration of the urban spillover effects and an in-depth analysis of the complex determinants influencing CEs within the YRB. Remote sensing data provide optimal conditions for conducting extensive studies across large geographical areas and extended time periods. This study integrates DMSP/OLS and NPP/VIIRS nighttime light datasets for a longitudinal analysis of urban CEs in the YRB. Using a harmonized dataset from DMSP/OLS and NPP/VIIRS nighttime light from 2007 to 2021, this study quantifies CEs of 58 prefecture-level cities in the YRB. By combining ESDA, STIRPAT model and spatial econometric model, this investigation further clarifies empirically the spatial spillover effects and driving factors of urban CEs. The analysis delineates a phase-wise augmentation in urban CEs, converging towards a distinct spatial distribution characterized by “lower reach > middle reach > upper reach”. The spatial autocorrelation tests unravel a complex interplay between agglomeration and differentiation patterns within urban CEs, underscored by pronounced spatial lock-in phenomena. Significantly, this study demonstrates that urbanization, economic development, energy consumption structure, green coverage rate, industrial structure, population, technological progress, and FDI each exhibit varied direct and indirect effect on urban CEs. Furthermore, it elaborates on potential policy implications and future research directions, offering crucial insights for formulating CEs mitigation strategies to advance sustainable development.

Development of an Internet-based Product-related Child Injury Textual Data Platform (IPCITDP) in China.

Internet-based media stories provide valuable information for emerging risks of product-related child injury prevention and control, but critical methodological challenges and high costs of data acquisition and processing restrict practical use by stakeholders. We constructed a data platform through literature reviews and multi-round research group discussions. Developed components included standard search strategies, filtering criteria, textual document classification, information extraction standards and a keyword dictionary. We used ten thousand manually labelled media stories to validate the textual document classification model, which was established using the Bidirectional Encoder Representation from Transformers (BERT). Multiple information extraction methods based on natural language processing algorithms were adopted to extract data for 29 structured variables from media stories. They were evaluated through manual validation of 1000 media stories about product-related child injury. We mapped the geographic distribution of media sources and media-reported product-related child injury events. We developed an internet-based product-related child injury textual data platform, IPCITDP, consisting of four layers - automatic data search and acquisition, data processing, data storage, and data application - concerning product-related child injury online media stories in China. Each layer occurred daily. External validation demonstrated high performance for the BERT classification model we established (accuracy = 0.9703) and the combined information extraction strategies (accuracy >0.70 for 25 variables). As of 31 December 2023, IPCITDP collected 35 275 eligible product-related child injury reports from 13 261 news media websites or social media platform accounts which were geographically located across all 31 mainland Chinese provinces and covered over 97% of prefecture-level cities. The injury cases in IPCITDP were typically reported several months or years earlier than official announcements about the product-related child injury risks. Our data platform added data concerning 15 supplementary variables that the national product-related injury surveillance system lacks. Two examples demonstrate the value of IPCITDP in supplementing existing data and providing early epidemiological detection of emerging signals concerning product-related child injury: magnetic beads and electric self-balancing scooters. Our data platform provides injury data that can support early detection of new product-related child injury characteristics and supplement existing data sources to reduce the burden of product-related injury among Chinese children.

Repel or attract? Effects of urban digital infrastructure on labor migration: Evidence from urban China

As a key feature of digital economy, digital infrastructure plays a prominent role in influencing labor migration across regions. To examine the impact of urban digital infrastructure development on labor migration in China, we first propose the theoretical mechanism of urban digital infrastructure affecting labor migration. Using the conditional logit model, we further analyze the impact based on the data of 165,866 individual data from 2013 to 2018 and the data of 240 prefecture-level cities in China. Empirical results indicate that urban digital infrastructure development has a significant inverted U-shaped effect on labor migration. The individual heterogeneity of the inverted U-shaped effect is significant in the labor migrants. Urban digital infrastructure development is more attractive to labor migrants with low education levels, labor migrants with the rural hukou, as well as female and new-generation individuals. Further research shows that the mechanisms that the inverted U-shaped effect depends on the comprehensive effects of mediating effects including the employment creation, the productivity, the employment substitution, and moderating effects as employment quality. Our findings are helpful to guide the orderly labor migration in the context of the accelerated development of digital infrastructure.

Influence of dialect diversity on level of urban innovation—Empirical evidence based on 276 cities in China

Diversity is influential and integral in innovation and economic growth. Despite the extensive research on the relationship between diversity and innovation, little attention has been paid to dialect diversity. The paper fills the research gap by investigating the impact and mechanism of dialect diversity on urban innovation in China. Also, this paper confirms the potential role of language as a non-institutional factor in urban innovation. Based on data from 276 prefecture-level cities in China, we find that dialect diversity impedes urban innovation. Moreover, in mechanism, it is not the communication barriers, but rather the identity from dialectal diversity that reduces regional trust to constrain urban innovation. Finally, we find that the negative impact of dialect diversity on urban innovation is continuous and more pronounced in eastern and southern cities. The conclusions not only enrich the theoretical research on innovation but also provide insights on how to promote language diversity governance and urban innovation for China and other countries.

Can the construction of smart cities promote the capital allocation efficiency: Evidence from China

Based on the panel data of 284 prefecture-level city in China from 2005 to 2019, this paper measures the urban capital allocation efficiency and takes smart city construction as a quasi-natural experiment. The multi-period difference-in-differences (DID) model has been built to verify the internal mechanism and practical effect of smart city construction driving the optimal allocation of capital. The results show that the construction of smart cities has significantly improved the efficiency of capital allocation, and the conclusion remains valid after a series of robustness tests; Mechanism analysis shows that strengthening environmental regulations and improving innovation capabilities, together with the construction of smart cities, have promoted the improvement of capital allocation efficiency; The heterogeneity analysis indicates that the effect of smart city construction on capital allocation efficiency is influenced by the administrative level and regional heterogeneity characteristics of the city. This paper provides empirical evidence for the policy effectiveness of smart city construction and provides policy enlightenment on how to optimize capital allocation.

How the digital economy can contribute to green manufacturing efficiency

In response to the global call to promote green production and achieve sustainable development, the proper use of the digital economy plays an important role. The deepening development of the digital economy has led to changes in the input of manufacturing factors and the structure of product demand, which in turn has led to corresponding changes in the level of green and sustainable development. This study employs a factor input-output non-expectation SBM-DEM model to assess the green manufacturing efficiency of 273 prefecture-level and higher cities in China. The relationship between the digital economy and green manufacturing efficiency is analyzed based on this model. The rise of the digital economy is found to contribute to the increase in green manufacturing efficiency, albeit with a non-linear “inverted U-shaped” trend. At the same time, the current level of digital economy development is slowly improving but has not yet reached the inflection point of the “inverted U-shaped” curve, and digital economy development still has a positive impact on green manufacturing efficiency at the current level of development. Furthermore, government intervention is critical in moderating the inverted U-shaped link between the digital economy and green manufacturing efficiency, which has a major weakening effect.