Hierarchy Of Cities Research Articles

Assessment of carbon emission reduction potential in new-type urbanization policy: A perspective on carbon rebound effect

In this research, we utilize a refined model for carbon emissions, known as the Stochastic Frontier Approach (SFA), to measure the extent of the carbon rebound effect across a sample of 231 urban areas in China, spanning the years 2011 through 2019. Additionally, the study explores the impact that policies associated with the advancement of new urbanization have had on the aforementioned carbon rebound phenomenon. The findings of this thesis indicate that this policy can reduce carbon emission volumes effectively; however, there is also a significant carbon rebound effect, making the reduction less efficient than expected. After several robustness tests, the main conclusions remain consistent and reliable. Our investigation into the underlying mechanisms reveals that policies aimed at fostering new urbanization may attenuate the carbon rebound effect by enhancing the efficiency and composition of industrial sectors. However, technological advancements and the degree of energy efficiency remain pivotal in potentially escalating the carbon rebound effect. The analysis of variations across different scenarios demonstrates that the policy’s impact on the carbon rebound effect is subject to variation depending on several factors, including geographical contexts like provincial boundaries, the administrative hierarchy of cities, transportation infrastructure, and the constraints imposed by resource availability. As a multi-target policy, although this policy has a carbon rebound effect, it also has a significant social welfare effect, which coincides with the development goal of China. Ultimately, some suggestions are offered to enhance the role of this policy in promoting carbon emission reduction and to foster a virtuous interaction between this policy and economic growth.

Fiscal decentralization's impact on carbon emissions and its interactions with environmental regulations, economic development, and industrialization: Evidence from 288 cities in China

Given the global focus on climate change and sustainable development, understanding the impact of China's fiscal decentralization on carbon emissions is essential for supporting green transformation and achieving carbon peaking and neutrality targets. This study examines data from 288 Chinese cities between 2003 and 2021, using fixed effects, moderation effects, and threshold effects models to assess the relationship between fiscal decentralization and carbon emissions, alongside its interaction with environmental regulation, economic development, industrialization, and city hierarchy. The results show that fiscal decentralization significantly aids carbon reduction, but stronger environmental regulations have not effectively slowed emission growth, creating a "green paradox." Relaxed regulations prioritize short-term economic gains, leading to underinvestment and fragmented regulatory efforts, which weaken emissions control. As economic development advances, fiscal decentralization's impact on carbon emissions shifts from positive to negative. Additionally, with increasing industrialization, the negative influence of fiscal decentralization on emission intensity becomes more pronounced. In non-first-tier cities, weak regulatory enforcement and limited autonomy hinder effective carbon reduction policies. To address these issues, the central government should enhance guidance and oversight of local environmental policies, ensure strict enforcement, optimize fiscal resources for environmental investment, and promote green economic transformation. A tailored approach to fiscal decentralization is needed to balance economic growth with environmental protection, achieving mutually beneficial outcomes.

Do high administrative‐level cities promote firm technological innovation? A novel analysis based on patent applications

AbstractThis paper examines the impact of China's administrative hierarchy of cities on firm innovation through the incentive policies that mobilize local governments to promote firm innovation. Using difference‐in‐differences approach, this paper finds that high‐level cities significantly and robustly enhance the number of firm patents. The results also suggest that alleviating firm financing constraints and leveraging human capital advantages are important mechanisms. In addition, high‐level cities mainly facilitate non‐state enterprises and small firms, and the quality of utility model patents was significantly lower and the quality of invention patents was higher in high‐level cities. This paper also presents several policy implications.

Financing constraints of firms: Is there political favoritism in the economic resources given by the central government?

AbstractEconomic resources within the jurisdiction of local governments in China shape the external financing environment of enterprises. However, few studies have focused on China's unique political hierarchy, which results in differentiated access to economic resources for different levels of local governments and substantially affects local corporate financing constraints. This paper examines the impact of city political hierarchy on firm financing constraints among Chinese A‐share listed firms from 2004 to 2019. We use the 200,000 population criterion for delineating the political hierarchy of cities in 1927 as the cutoff for fuzzy regression discontinuity design to identify causal effects. The results show that the greater a city's political rank is, the lower its financing constraints are. The mechanism suggests that the central government provides more financial and political resources to high‐level cities, directly and indirectly influencing the financing constraints of firms. In addition, high‐level cities' government preferences, bank loans, debt financing costs, and business credit are vital channels at the firm level. However, this effect varies depending on the ownership and size of the firm.

Associations between environmental perception and self-rated health in the city hierarchy of China: Findings from a national cross-sectional survey

Identifying environmental determinants of health and clarifying their variations is crucial for health promotion in different cities by providing tailored intervention strategies. Although the association between perceived urban environment and health (e.g., self-rated health) has been repeatedly explored, most studies have focused on cities of a specific size, and it is still unknown whether either significant environment variables or the magnitude of the association would vary across different-sized cities. This study investigated how perceived urban environment variables significantly associated with individuals’ self-rated health varied from small cities to mega cities in China, based on a national survey including 5963 valid respondents. The results showed that the relationship between self-rated health and city size was U-shaped, with respondents in medium and large cities reporting a low-level self-rated health. Perceived greenness, public facilities, housing supply, and medical services were positively and significantly associated with self-rated health, with the odds ratio (OR) of 1.37 (95%CI: 1.29–1.46), 1.27 (95%CI: 1.19–1.35), 1.14 (95%CI: 1.09–1.20), and 1.17 (95%CI: 1.10–1.24), respectively. Furthermore, the magnitude of the association was significantly larger in mega cities. These findings provide useful evidence for promoting public health in cities of different sizes for achieving health equity and indicate that smaller cities and their health-supportive environment need further attention.

The Interconnectivity and Spatio-Temporal Evolution of Rail Transit Network Based on Multi-Element Flows: A Case Study of Beijing-Tianjin-Hebei Urban Agglomeration, China

For intercity transportation within urban agglomerations, rail transit interconnectivity not only stimulates city-to-city interactions but also facilitates the networking of urban spaces. Crucially, comprehending the spatial network of urban agglomerations needs a focus on rail transit interconnectivity. Drawing on the space of flows theory, this study establishes a framework to evaluate rail transit interconnectivity and the spatial structure of urban agglomerations, utilizing the Beijing-Tianjin-Hebei urban agglomeration as a case study. The objective of this study is to explore the impact of rail transit interconnectivity on the spatial structure in the urban agglomeration. Firstly, it establishes a coupled concept of urban quality and line quality to elucidate the interaction between rail transits and urban development. Secondly, it employs the AHP-CRITIC-TOPSIS and modified gravity model to evaluate the interconnectivity degree of rail transits and visualize the network. Thirdly, based on the multi-element flows facilitated by rail transit interconnectivity, the evolution of the spatial structure within the urban agglomeration is quantified using social network analysis. The study findings are as follows: (1) From 2010 to 2021, the interconnectivity degree of rail transit in the Beijing-Tianjin-Hebei urban agglomeration experienced substantial growth, emphasizing the correlation between interconnectivity and the city hierarchy within the urban agglomeration. (2) The interconnectivity degree of the Beijing-Tianjin-Hebei urban agglomeration shows an uneven pattern of “three cores and numerous weak links,” characterized by spatial polarization. (3) Rail transit interconnectivity contributes to shaping the spatial structure of urban agglomerations in terms of interconnectivity, polycentricity, and integration, although the enhancement of polycentricity is limited. The framework developed in this study can be extensively employed to investigate the interplay between rail transit interconnectivity and the spatial structure of urban agglomerations, thereby promoting the sustainability of regional planning.

The impact of city size on income inclusive growth: A human capital perspective and evidence from China.

This paper methodically investigates the influence of inclusive income growth on city size, examining it through the dual lenses of "income" and "distribution." The analysis leverages meticulously collected panel data encompassing 276 Chinese cities at the prefecture level and above, spanning the period from 2005 to 2019. Theoretical analysis indicates that the effect of city size expansion on per capita income adheres to a 'U'-shaped trajectory, while its influence on the urban-rural income gap manifests an 'inverted U' pattern. Moreover, the inclusive income growth stemming from city size demonstrates notable heterogeneity across various geographic locations and city hierarchies. The findings reveal that human capital serves as the primary mechanism through which city size influences inclusive income growth. After decomposing the income inclusiveness index, it becomes evident that the expansion of city size exerts a more potent direct driving effect on the income of urban residents. On the one hand, city size expansion directly increases rural residents' income levels by improving labor productivity. On the other hand, it facilitates leapfrog income development by inducing the rural labor force to move to cities.

Identifying Relationship between Regional Centrality and POI Facilities: A Case Study of Seoul Metropolitan Area

While understanding the dynamic urban network through the concept of regional centrality has provided various implications on the structure and hierarchy of cities, the macroscopic focus of previous studies has largely overlooked the small-scale physical and social urban entities in central places. Meanwhile, recent advances in real-time Point-of-Interest (POI) data have quickly replaced much of traditional urban facility data, emerging as a new representation of urban activities and demands. Therefore, this study proposes a method to identify the relationship between regional centrality and the distribution of POI facilities, particularly focused on the Seoul metropolitan area of South Korea. To this end, this study conducts a correlation analysis between regional centrality results derived from social network analysis and POI indices obtained from POI distribution analysis. The results indicate that a statistically significant relationship exists between regional centrality and the distribution of urban facilities, with a particularly strong correlation exhibited in specific POI categories. The results also demonstrate the effectiveness of the method in capturing disparities in the provision of facilities concerning growing commuting centers. The findings of the study provide pragmatic implications for prioritization and planning of facility development, as well as making informed decisions in real estate and facility investment.

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.

Political hierarchy spillovers: Evidence from China

AbstractThis paper explores the impact of the political hierarchies of cities in China from different perspectives. First, we examine the economic disparities between prefectural cities and municipalities. Furthermore, this paper draws upon a quasi‐ experiment to analyze the impact of upgrading Chongqing to a municipality in 1997 using the synthetic control method. The city‐upgrading policy significantly increased Chongqing's gross domestic product (GDP) in the following 4 years. Finally, we find that the policy increased GDP in treated cities within 1200 km of Chongqing by about 10%–13% relative to the control cities.

How to determine city hierarchies and spatial structure of a megaregion?

ABSTRACT Megaregion has emerged as a global urban form, typically based on the polycentric strategy to enhance regional development. How to measure megaregional spatial structure and discriminate different roles of cities has become increasingly important to enrich the knowledge of the formation of a megaregion. Meanwhile, various indices have been used to identify vital nodes in the field of complex network. Which indices, however, are suitable for megaregion analysis remain unsolved. To address this requirement, this study first reviewed the typical indices for identifying vital nodes in the complex network theory, and pointed out that in a weighted city network scenario, weighted degree centrality, hub & authority score, and S-core decomposition (which represent network centrality, connectivity, and structures, respectively) are suitable for analyzing megaregional spatial structures. Then, we explored the city hierarchies and spatial structure in Guangdong Province, China, using the three indices. The hierarchical structure of the weighted city network in Guangdong Province had been identified using S-core decomposition. From the perspective of polycentric structure, Guangzhou and Shenzhen have the strongest node degrees and strength of mobility flows, while the Guangzhou-Dongguan-Shenzhen corridor has been identified via the hub & authority score which is designed to evaluate the connectivity in a weighted network. Moreover, we conducted a comparison analysis of three indices. The findings of this study not only enrich the understanding of city hierarchies and the structure of a megaregion, but also highlight that although various indices are available, they should be applied selectively in accordance with the study context.

Review of “Emerging global cities: origin, structure and significance”

The authors challenge the “global city literature” school of urban studies thought advanced by such authors as Saskia Sassen, which empirically rank-orders world cities based on their concentration of business activity and confers higher power and importance to cities atop this hierarchy. The book advances a critique of the global city literature alongside scholars such as Neil Brenner and Jennifer Robinson, arguing that such hierarchical conceptions of world cities ignore third world or Global South cities, instead treating higher-ranked cities as ideal and merely reproducing North American and Eurocentric views of urban life. As opposed to the orthodoxy of global city literature, the authors suggest that “emerging global cities” such Dubai, Miami, and Singapore emerged from a position of insignificance to prominence, without “sponsorship” from the supposed global elite cities atop the world city hierarchy. The book contributes a novel set of characteristics explaining this ascendance, which can most directly benefit global urban studies focused on cities in the Global South: a legal system that investors are confident with, a pro-business yet non-corrupt government bureaucracy, local political leaders motivated to make their city globally competitive, including the use of city branding, and the inward migration of foreign labor to fuel growth in globalizing formal economic sectors. These factors contribute novel criteria missing from the global city literature to explain the flexibility for peripheral cities to ascend.

Who earns more? City hierarchy of earning returns to education among migrant workers in urban China

According to urban economic theories, workers in more developed regions should have higher educational returns. However, studies on urban workers in China have shown mixed results on whether earning returns to education are higher in regions experiencing more economic growth. Meanwhile, there is a lack of evidence on this issue among migrant populations, which have rapidly increased in number during China's economic transition. To fill this void, this study investigated how educational returns among migrant workers are related to local economic development levels and industrial structures. Specifically, we used individual-level data obtained from 286 cities through the 2018 China Migrants Dynamic Survey and city-level data to conduct a multilevel linear regression analysis with random slopes. We thus found that earning returns to education were higher in cities under two conditions, including higher development and higher shares of tertiary industry. Moreover, this association was more pronounced among high-skill migrant workers than low-skill ones. As higher income is a primary driving force in migration, we suggest that future policies should further promote industrial restructuring rather than using discriminative administrative rules to guide migration flows.

Learning urban region representations with POIs and hierarchical graph infomax

We present the hierarchical graph infomax (HGI) approach for learning urban region representations (vector embeddings) with points-of-interest (POIs) in a fully unsupervised manner, which can be used in various downstream tasks. Specifically, HGI comprises several key steps: (1) training category embeddings as the initial features of POIs; (2) interconnecting POIs with a graph structure and performing graph convolution to capture the uniqueness of each POI based on its spatial context; (3) aggregating POIs to the regional level using multi-head attention mechanisms, to consider the multi-faceted influence from POIs to regions; (4) performing graph convolution at the regional level to generate region representations, to incorporate the similarities between adjacent regions; (5) aggregating region representations to produce an embedding at the city level. The model is finally trained through maximizing the mutual information among the POI – region – city hierarchy, which facilitates the information from local (POIs) and global (city) scales flowing to the learned region representations, making them both locally and globally relevant. We perform extensive experiments on three downstream tasks, i.e., estimating urban functional distributions, population density, and housing price, in the study areas of Xiamen Island and Shenzhen, China. The results indicate that HGI considerably outperforms several competitive baselines in all three tasks, which proves that HGI could produce meaningful and effective region representations. In addition, the learned region representations based on POIs can potentially be used for reinforcing data representations from other modalities, e.g., remote sensing data. The implementation of HGI can be found at https://github.com/RightBank/HGI.

Migrating up the World City Hierarchy: Seoul as a World City of ‘Transfer’ for the Latin American Creative Class

This paper focuses on the world city of Seoul as an alternative, temporary destination for creative class migrants from Latin America. The creative class is a concept developed by Richard Florida to describe, "creative individuals whose economic function is to create new ideas, technology and/or creative content." In this research, world city of ‘transfer’ refers to world cities ranked by the Globalization and World Cities Research Network (GaWC) that are of high middle (Alpha) to lower ranking and that become ‘temporary stops’ for the migrating creative classes, whose ultimate destinations are the Alpha+ and Alpha++ world cities. This research namely asks: (1) From the perspective of creative migrants from developing countries, what causes them to leave world ‘transfer’ cities, such as Seoul, and not settle there long term? and (2) What kind of policies can be applied to help creative migrants stay in these cities permanently? Social integration policies should be implemented when trying to further develop a world city’s quality of place. Qualitative research methods such as in-depth interviews with Latin American creative people were employed to demonstrate Seoul’s need for social integration policies aimed at retaining global talent and not just attracting it.

The Role of Proximity in Transformational Development: The Case of Resource-Based Cities in China

Proactive integration into the national city network and the improvement of the level of openness to the outside world is important for the new period to promote the high-quality transformational development of resource-based cities. Based on the gravity model and social network analysis methods, the role of geographical proximity and network proximity (non-spatial proximity) in the high-quality transformation of resource-based cities is systematically analyzed. The impact of geographic proximity, network proximity, and their interactions on the transformation of resource-based cities was also empirically tested by constructing an econometric model. It is found that: (1) The cities with the highest gravitational values and gravitational values among the neighbouring cities of resource-based cities did not change significantly from 2001 to 2019, and cities with better transformation are mostly dominated by RBC-non–RBC combinations, with the gravitational values of neighbouring cities at the middle level. (2) The hierarchy of resource-based cities in both the national organizational network and investment network increased significantly during 2001–2019, but the difference is that the organizational network is centered on Beijing. (3) While there is an inverted U-shaped relationship between geographical proximity and transformation in resource-based cities, there is a linear positive relationship between network investment proximity and transformation. However, there is a substitution and complementary effect between the two, and they work together to promote the high-quality transformation of resource-based cities.

The end of urban sprawl? Internal migration across the rural-urban continuum in Switzerland, 1966-2018.

In high-income countries, migration redistributed populations from congested city centres into the sparsely populated outskirts, raising challenges to environmental and population health and the conservation of biodiversity. We evaluate whether this periurbanisation process came to a halt in Switzerland by expecting a decline in internal migration and a renewed residential attractiveness of urban agglomeration centres (i.e., re-urbanisation)-two recent trend changes observed in Europe. Relying on data from censuses, registers and surveys, we describe trends in the intensity, geography and sociodemographic differentials of migration across consistently defined urban agglomeration density zones between 1966 and 2018. Although the overall intensity of migration declined, the rate increased among the working age population in part because of the societal diffusion of tertiary education. The dominant urban-bound migration flows are increasingly confined within agglomerations over time. After the diffusion of periurbanisation down the city hierarchy between 1966 and 1990, we observe the emergence of re-urbanisation in some agglomerations and sociodemographic groups around 2000. However, this phenomenon has been temporarily inflated by period-specific transformations in Swiss society. More recently, the process of periurbanisation intensified again and expanded more and more beyond official agglomeration borders.

Research on spatial structure and resilience of complex urban network: A case study of Jing-Jin-Ji Urban Agglomeration

With the long-term impact of economic globalization, the accelerated cross-border flow of resource elements between cities is increasingly important for the development of urban regions. In this context, the central place theory, which emphasizes the vertical hierarchical relationship between cities, has obvious limitations in interpreting urban interaction. This paper takes the Beijing Tianjin Hebei Urban Agglomeration (including Beijing, Tianjin. and 11 prefecture-level cities in Hebei Province) as the research object, constructs three complex networks of economy, information, and economic information coupling connection, and analyzes the resilience of the network structure. The research results show that: 1) The spatial distribution of the three network structures of Jing-Jin-Ji Urban Agglomeration presents a spatial pattern with Beijing as the core and radiating outward. 2) In terms of weighted degree distribution, Beijing, as an arrow city, has strong competitiveness in the economy and information network, but the hierarchy of cities with balanced information economy development is low. 3) In terms of weighted degree correlation, among the three networks, the cities with a high weighted degree prefer to connect with cities with a low weighted degree, and the mismatch is ranked as information network > information economy coupling network > economic connection network. 4) In terms of network transmission, information network > economy connection network > information economy coupling network, and Beijing and Tianjin have a greater impact. The above results have strong guidance and practical significance for the formulation and adjustment of territorial spatial planning and regional optimization.

A spatial interaction model of vote dispersion

How do votes disperse through a territory? Studies of spatial voting patterns have largely focused on the influence of local factors on voting. The “Friends and Neighbors” model (Key (1949)) explains the advantage of candidates running for office in the locality with which they are associated (Arzheimer and Evans (2012, 2014): Collignon and Sajuria (2018); Horiuchi et al. (2018); Jankowski (2016); Hunt (2020); Munis (2021)), and the “neighbor” effect helps to explain why votes spread. More recent studies have found that the dispersion of votes decreases with distance (Put et al. (2020); Arzheimer and Evans (2012)). However, we know little about how spatial patterns of voting emerge or the mechanism behind the neighbor effect. We argue that this effect depends on the neighbors’ access to information about a candidate, which is constrained by the way information flows. Although scholars have argued that information is a relevant driver explaining the dispersion of votes (Bowler et al. (1993); Arzheimer and Evans (2012); Evans et al. (2017); Campbell, Cowley, Vivyan, and Wagner (2019)), no research has examined the relevance of the network through which information flows. We propose that a spatial interaction model (Wilson (1971)) allows us to predict where this information flows or the voting pattern that will form. Taking advantage of a quasi-natural experiment in Brazilian legislative elections in 1974 and 1978, we show that votes spread through areas of influence created by a hierarchy of cities based on the flows of exchanges among them, including information. We then use our spatial interaction model to predict voting patterns in the elections of 1978 using data from the 1974 elections. Our findings show that the spatial interaction model results fit the data quite well and can help predict spatial patterns of voting.

Interstitiality in the smart city: More than top-down and bottom-up smartness.

The critical research agenda on smart cities has tended to assume a largely top-down orientation in which powerful actors like the state and corporations enact programmes to embed Information & Communication Technologies (ICT) in the urban landscape. Because of the way research has framed this relation of power, the dominant response has been to seek social justice by either contesting these top-down exercises of (digital) power or by reconceptualising the smart city 'from below'. In this paper, we join a growing chorus of voices recognising the importance of interstitial actors that influence the ways in which the smart city manifests. We draw on a five-year ongoing study in Calgary, Alberta, to examine two actor groups that are, properly, neither top-down nor bottom-up, but play an important role in envisioning, implementing and contesting how 'smartness' is framed. The first set of actors, situated between the top and bottom of the smart city hierarchy, are most prominently community associations, non-profit organisations and ad-hoc task groups. The second group is comprised of groups with different digital practices, whose spectre of marginalisation influences how digital systems are articulated and pursued. These actors strategically move between different interstices in order to enact particular kinds of political influence, and often influence smart cities by virtue of their absence, profoundly impacting urban political geographies of smartness.