Spatial Spillover Research Articles

Study on the impact of air pollution on residents' health expenditures in Guangdong, Hong Kong, and Macao Greater Bay Area

The Guangdong, Hong Kong, and Macao Greater Bay Area (GHMA) has experienced economic development and rapid growth of transportation infrastructure in recent years. However, the economic advancement is also accompanied by serious atmospheric pollution, which threatens the health of the residents, thus, it is of great significance to explore the impact of atmospheric pollution on the health expenditures of residents in the GHMA. The article establishes a spatial econometric model to study the impact of atmospheric pollution on residents' health expenditure in the GHMA based on panel data from 2014 to 2021, using nine prefectures in the GHMA as research objects. The results show that: (1) Atmospheric pollution in the GHMA has an obvious spatial agglomeration phenomenon and spatial spillover effect, and the impact of atmospheric pollution on the health of the residents is still very serious; (2) PM2.5 emissions are positively and significantly related to the actual health care cost per person, and the rise in air pollution is the main reason for the rise in public health spending; (3) Other factors also have different impacts on residents' health expenditures. Based on the above research, the article puts forward corresponding policy recommendations.

Carbon Abatement Effect of Low-Carbon City Pilot Policy: Insights from a Time-Varying DID Model

The low-carbon city pilot (LCCP) policy constitutes a crucial element in China’s endeavors to attain its carbon peak target. Thoroughly analyzing the carbon abatement effects and mechanisms of the LCCP policy is essential for supporting China’s goals of achieving low-carbon sustainability. We use panel data from 1997 to 2019, covering 249 Chinese cities, for a quasi-natural experiment. This study assesses the effect of the LCCP project on urban carbon emission intensity (CEI) using a difference-in-difference (DID) model. Furthermore, the article conducts analyses on policy coordination effects, impact mechanisms, and spatial spillover effects. Our research findings indicate that the LCCP policy substantially decreases urban CEI, a result that withstands a battery of robustness tests. The carbon abatement effect of LCCP policies is dynamic and typically endures for three years. Subsequent investigations unveil a cooperative impact between the LCCP policy and the carbon trading pilot policy. The decrease of urban CEI under the LCCP policy is primarily attributed to command and market tools, although the efficacy of voluntary tools remains unrealized. From the standpoint of adjacent nonpilot cities, our conclusions do not endorse the presence of spatial spillover effect for the LCCP project. The insights derived from our findings offer crucial guidance for policymakers exploring low-carbon models and pathways.

Spatial Spillover Effects of Digital Finance on Corporate ESG Performance

Spatial Spillover Effects of Digital Finance on Corporate ESG Performance

The spatial spillover impact and transmission mechanisms of logistics agglomeration on eco-efficiency: A case study in China

This study employs spatial durbin model (SDM) and spatial mediation model to empirically investigate the relationship between logistics agglomeration (LA) and logistics eco-efficiency (LEE), as well as the transmission mechanism role of technological innovation (TI) and advanced industrial structure (AIS), using panel data on inter-provincial logistics in China from 2008 to 2020. The findings indicate a U-shaped relationship between LA and LEE. The early development of LA in China was accompanied by environmental sacrifices. Further analysis of the curves reveals that LA has spatial spillover effect on LEE. That is, insufficient concentration of LA has a siphon effect on the LEE of surrounding areas, whereas appropriate concentration of LA has a radiation effect on the LEE of surrounding areas. Spatial mediation analysis indicates that enhancing TI and developing AIS are essential channels through which LA bolsters LEE. Additionally, this study innovatively incorporates topography ruggedness and altitude as instrumental variables to account for potential endogeneity issues in the empirical model. Theoretical and practical significance is attributed to this research for China's logistics industry, particularly shedding light on the optimization of efficiency and long-term improvement of LEE through spatial reform via agglomeration zones.

Comprehensive performance analysis of deep integration and innovative development of logistics and manufacturing industries: A comparison analysis between coastal and inland regions in China

In today's industry development, the integration of manufacturing and logistics industries has received increasing attention from the international community. The Chinese government has set a strategic agenda for the deep integration and innovative development of logistics and manufacturing industries (DIIDLMI). However, it is still unclear what impact DIIDLMI has on the development of two industries. Especially with significant differences in resource endowments, it is interesting to see whether such impacts vary between coastal and inland regions. Therefore, this study focuses on the regional collaborative development mechanism and analyzes the performance of DIIDLMI by using the Spatial Durbin Model with provincial data in China. The analysis result indicates that, first, DIIDLMI has positive local effect and positive spatial spillover effect on digital intelligence technology development of the two industries, positive spatial spillover effect on low-carbon transformation and profit level of the logistics industry, positive local effect on low-carbon transformation of the manufacturing industry, and positive local effect on profit level of the two industries. Second, we also obtain some counterintuitive results, i.e., DIIDLMI has no local effect on low-carbon transformation of the logistics industry, no spatial spillover effect on low-carbon transformation and profit level of the manufacturing industry. Third, compared to coastal regions, DIIDLMI in inland regions has a more positive local effect on digital intelligence technology development of the logistics industry, a more positive spatial spillover effect on low-carbon transformation of the logistics industry, a more positive local effect on low-carbon transformation of the manufacturing industry, and a more positive local effect on profit level of the manufacturing industry. Finally, based on these results, policy recommendations are presented for promoting the related industrial development.

Yesterday's solution: Do national economic and technological development zones promote industrial development in typical developing regions of China?

With the proliferation of special economic zones (SEZs) among emerging economies, their mixed performance has sparked discussions on contextual heterogeneity and underlying driving mechanisms. Characterized by an outward-oriented economy and industry-city interaction, the cross-stage establishment practice of China's national economic and technological development zones (ETDZs) is conducive to expanding existing research focused on cross-country analyses of SEZs. This study constructs difference-in-differences models to analyze the influence of national ETDZs on regional industrial development in the Yellow River basin, a typical developing region in China, from 2003 to 2019, evaluating their performance under a regional balanced development strategy and a within a lagging economic backdrop. The results indicate that (1) national ETDZs do not contribute to industrial growth and even exert a negative effect; (2) while they fail to perform better over time, their spatial spillover effect slightly benefits neighboring cities; (3) an optimal economic environment and proactive policy promotion can respectively mitigate and exacerbate their negative effects; (4) the inability to attract external enterprises and achieve industrial restructuring is the primary cause of the negative effect, highlighting a mismatch and discord between the economic and policy attributes of national ETDZs and evolving contexts. Based on these findings, recommendations are proposed to cultivate SEZs as suitable policy platforms and effective economic spaces.

Do high housing prices inhibit entrepreneurial activity?—Evidence from Yangtze River Delta cities, China

AbstractContrary to the existing literature that suggests the inhibitory or facilitating effect of housing prices on entrepreneurial dynamism, this paper explores the nonlinear effect of housing prices on entrepreneurship and countervailing effect of entrepreneurial dynamism on housing prices, in addition to investigating the spatial interaction between the two. This paper constructs a simultaneous equation model (SEM) to empirically test the interaction and spillover effects between housing prices and entrepreneurial dynamism. The results show that: (1) there is a two‐way interaction between housing prices and entrepreneurial dynamism; (2) the estimated coefficients of housing prices and the quadratic square term of housing prices (14.285 and −0.744, respectively) are consistent and significant as expected, indicating an inverted U‐shaped effect of housing prices on entrepreneurial dynamism; and (3) in geospatial terms, there are positive spatial spillovers and negative spatial interaction effects for both house prices and entrepreneurial dynamism in Yangtze River Delta cities.

Digital dividend or digital divide? – Evidence from China

ABSTRACT This paper examines the impact of the digital economy on the urban‒rural income gap. Based on Chinese provincial panel data from 2011 to 2022, this paper uses the entropy weight-TOPSIS method to construct a comprehensive index of the digital economy and explores the spatial spillover and heterogeneity of the impact of the digital economy on the urban‒rural income gap through the spatial Durbin model and partially linear functional-coefficient panel model. The results indicate that at the national level, the digital economy widens the urban‒rural income gap in the region and neighbouring regions. At the regional level, the digital economy contributes to widening the urban‒rural income gap in the eastern region and narrowing the gap in the western region. Furthermore, there is a nonlinear relationship between the digital economy and the urban‒rural income gap, and different dimensions of the digital economy have different impacts. This paper aims to provide insights and references for China and other developing countries to achieve integrated urban‒rural development with the support of the digital economy.

The impact of China’s total carbon emission control policy on low carbon total factor productivity

ABSTRACT The evaluation of the policy effect of total carbon emission control policy (TCP) is crucial to achieve high-quality economic development in China. This paper measures the low-carbon total factor productivity (LCTFP) of 282 Chinese cities from 2010 to 2021, and examines the impact of TCP on LCTFP through differences-in-differences (DID) method. The results show that TCP can effectively improve LCTFP in policy implementation areas. TCP has a stronger LCTFP promotion effect on eastern cities, resource-based cities and higher-level cities. Technological progress effect and industrial structure effect are important channels for TCP to improve LCTFP. TCP has a negative spatial spillover effect on LCTFP. This paper provides valuable references to promote the implementation of TCP in China.

Towards more resilient cities-analyzing the impact of new-type urbanization on urban resilience: Considering spatial spillover boundaries

This paper examines the New-type Urbanization pilot policy (NTUP) and its influence on urban resilience, offering insights into how NTUP fosters a human-centric, sustainably coordinated, and inclusive model of urban development distinct from traditional approaches. This model plays a key role in enhancing urban capacities to confront economic, social, and environmental challenges, aiding in building more resilient cities. Notably, existing literature scarcely explores the relationship between NTUP and urban resilience, marking a significant gap this research aims to fill. Utilizing a multi-period DID model to examine panel data across 281 Chinese cities from 2006 to 2020, this study delves into NTUP's direct effects on urban resilience, its mechanisms, and spatial spillover boundaries. Findings reveal that: (1) NTUP enhances urban resilience, confirmed by a series of robustness tests. (2) NTUP significantly improves economic, infrastructure, and institutional resilience, while its influence on social resilience is minimal, and it detrimentally impacts ecological resilience. (3) Urban technology innovation and economic agglomeration are the primary mechanisms through which NTUP promotes urban resilience. (4) NTUP has a positive spatial spillover effect on the resilience of neighboring cities up to 350 km, with this effect shifting from a "radiation effect" to a "siphoning effect" as geographical distance increases.

Spatial spillover effects in the labour market in a middle-income country

ABSTRACT Most macroeconomic labour literature on estimating matching functions does not consider spatial spillover effects. However, job search and vacancy-filling processes often involve neighbouring locations, as local workers can search for and fill vacancies in nearby labour markets. We estimate a spatial spillover model using annual data for a middle-income country in Latin America. Our findings show that unemployment has a positive spatial spillover effect because an increase in the labour supply raises the probability of filling a vacancy. In contrast, vacancies have a negative spillover effect because local and neighbouring vacancies compete to be filled by workers in both markets.

Analysis of the Current Situation of the Construction Industry in Saudi Arabia and the Factors Affecting It: An Empirical Study

The construction industry in Saudi Arabia has been modernized through the implementation of green building technologies and intelligent building systems, which have facilitated the sustainable development of the construction industry in Saudi Arabia. However, there is a paucity of research on the current situation of the construction industry in Saudi Arabia. In this study, the super-efficient epsilon-based measurement (EBM)–Malmquist model was used to measure the static and dynamic efficiency of the construction industry in the administrative areas of the 13 provinces of Saudi Arabia from 2013 to 2022, and the Tobit model was used to empirically analyze the factors affecting the efficiency of the industry. In addition, the spatial autocorrelation of the efficiency of the industry was analyzed using Moran’s Index (MI) to study the characteristics of the spatial distribution of industrial efficiency as well as the effectiveness of resource allocation. The study shows that Saudi Arabia’s construction industry is at a low level of development; the population, GDP, and carbon dioxide emissions have a significant impact on the efficiency of the industry; and the development of the industry can help to reduce carbon dioxide emissions, thus promoting environmental sustainability; Saudi Arabia’s construction industry has a spatial spillover effect but does not have a significant agglomeration effect. This study accurately identifies the current situation of the development of the construction industry in Saudi Arabia and proposes several countermeasures and opinions, which are expected to provide a theoretical basis for realizing its sustainable development.

Assessing the Sustainable Development Level of the Tourism Eco-Security System in the Chengdu-Chongqing Urban Agglomeration: A Comprehensive Analysis of Dynamic Evolution Characteristics and Driving Factors

Based on the DPSIR framework, this study constructed an evaluation index system to assess the sustainable development levels of the tourism eco-security system (TESS-SDL) present in the Chengdu-–Chongqing urban agglomeration and synthesized multi-dimensional analysis methods to explore its spatiotemporal evolution characteristics and driving factors to provide an important theoretical and practical basis for promoting the sustainable development of the regional tourism eco-security system. The results showed the following: (1) From 2011 to 2021, the regional TESS-SDL was generally at a medium level and showed a trend of steady growth. Although the gap between cities was widening year by year, the speed of the TESS-SDL exceeded the speed of the widening gap, promoting the coordinated development of the regional TESS-SDL. (2) The spatial spillover effect of the regional TESS-SDL was obvious; however, the siphoning effects of Chongqing and Chengdu were strong, and the demonstration effect was insufficient. (3) The dynamic evolution process of the TESS-SDL shows a strong self-locking effect. The risk of downward development (lower sustainability) is greater than the potential for upward development (higher sustainability) and is significantly influenced by neighboring cities. (4) In terms for assessing the driving factors, open-door and green-development policies show positive facilitating effects, while the positive influencing capacities of information technology, economic development, and tourism are moving toward having negative effects; the influencing effect of technological innovation has transitioned from positive to negative.

Spatial spillover effect of service industry agglomeration on industrial structure upgrading: Evidence from China

The industrial structure upgrading is a significant indicator in the High-quality economic development. Despite the crucial role that the cluster of service sectors play in improving the industrial system, the research on the impact of service industry agglomeration on industrial structure upgrading is scant, especially the spatial correlation between them. This paper aims to discuss this objective. The current study employs the Spatial Durbin Model to examine the association between service industry gathering and the advancement of industrial systems based on the panel data of Chinese provincial units for the years 2000 to 2020. Findings from the empirical analysis disclose that the concentration of service-related activities in the same province plays a notable role in the optimization of the industrial framework. Moreover, service industry agglomeration demonstrates a noteworthy spatial spillover effect. The gathering of the service industry breaks through geographical constraints and facilitates the enhancement of industrial framework in adjacent regions through radiation effect. Subsequently, the enhancement of the industrial framework in neighboring areas further stimulates the local industrial configuration through spill-over impacts. This research provides a theoretical framework for analyzing the spatial correlation between the service industry group and the enhancement of the industrial framework, and presents practical reference for local authorities to foster the transformation of industrial structure.

Carbon emission intensity measurement and spatial effect of high energy consuming industries: evidence from China

<p style="text-indent:20.0pt"><span style="font-size:10.5pt"><span style="font-family:"Times New Roman",serif"><span style="color:black"><span class="fontstyle01" style="font-family:仿宋"><span style="color:black"><span lang="EN-US" style="font-size:10.0pt"> High energy consumption industry is an important source of carbon dioxide emissions, and reducing pollution and carbon is an important measure for China to achieve the goal of "2030 carbon peak 2060 carbon neutral". Based on the improvement of the traditional calculation method of IPCC carbon emission intensity, this paper measures the carbon emission intensity, selects the data of high energy consuming industries in 30 provinces in China from 1997 to 2022 as samples, uses the stipat model and Moran index to analyze the correlation of the influencing factors of carbon emission, and uses the spatial measurement model to study the spatial effect of carbon emission intensity. The results show that: first, the overall carbon emission intensity of high energy consuming industries shows a downward trend, with typical spatial heterogeneity. During the sample period, the carbon emission intensity of high energy consuming industries in 30 provinces in China was calculated based on the IPPC method, with the overall decline. Second, the carbon emission intensity of high energy consuming industries has significant spatial autocorrelation characteristics. According to the global Moran index, the center of gravity moves from east to West as a whole. Third, the carbon emission intensity of high energy consuming industries is affected by multiple environmental factors. Industrial structure (INS), regional gross domestic product (GDP) and regional economic development (ECO) have a significant impact. Fourth, the carbon emission intensity of high energy consuming industries has a significant spatial spillover effect. According to the regression results of spatial Dobbin model with double fixed effects, the direct and indirect effects of carbon emission intensity of high energy consuming industries are significant.</span></span></span></span></span></span></p>

Green economic efficiency and productivity for sustainable development in China: A ray epsilon-based measure model analysis

Improving green economic efficiency (GEE) and productivity are crucial for China to realize sustainable development goals. However, the economic growth of China has followed an extensive development model with high energy consumption and heavy pollution. This study conducts data envelopment analysis (DEA) to evaluate the GEE of China. First, we introduce the polar coordinates theory in the epsilon-based measure (EBM) model to construct a Ray epsilon-based measure (REBM) model. In addition to the merits of EBM model, the REBM model accounts for the weak disposable relationship between undesirable and desirable outputs. Second, based on REBM model, a REBM-Malmquist-Luenberger (REBM-ML) index is constructed to evaluate the green total factor productivity (GTFP). Finally, we conduct spatial econometric analysis to reveal the dynamic evolution of GTFP. According to the empirical results, the GEE of China is generally low, and the urban agglomerations located at coastal regions own higher GEE. However, the GTFP made progress overall, mainly benefited from the technical progress. Accordingly, in the process of sustainable development, China still faces the challenge of energy saving and emission reduction. The spatial econometric analysis reveals that the GTFP of China existed a significant divergence trend and there was spatial spillover effect between cities, as well as urban agglomerations. Furthermore, we provide policy implications and suggestions for Chinese sustainable development.

Human activities and ecosystem health: A historical analysis of Poyang Lake

Urbanization, industrialization, land development, and other human activities have led to ecological issues such as shrinking lake wetlands, fragmented cropland, and reduced biodiversity. Taking the Poyang Lake urban agglomeration as the study area, the textual analysis method was used to analyze the typical facts of the historical succession of human activities since 1949, and then the index method and the spatial analysis method were adopted to characterize the spatial and temporal evolution of the ecosystem health and human activities in the period of 2003–2020. On this basis, the spatial spillover effects of human activities on ecosystem health were investigated based on the spatial Durbin model in four dimensions. The results of the study show that since 1949, human activities in the Poyang Lake area have gone through the management path from “agricultural retreat and fishery advancement” and “dike reclamation” to “sand ban” and “returning the lake”. Ecological protection has gone through the sublimation from “enlightenment” to “full implementation” to “strengthening and upgrading”. The ecosystem health of Poyang Lake urban agglomeration from 2003 to 2020 has been in the range of 0.37709 ∼ 0.3709 ∼ 0.3709. 0.37709 ∼ 0.48485, with the spatial characteristics of “low in the center and high in the periphery”. The city expansion and agricultural activities in the county are generally distributed in the pattern of “high center, low periphery”, while the spatial distribution of water body area is characterized by “near-lake” and “near-river”, and the newly registered enterprises show a change from “point” to “surface”. The spatial distribution of water body area is characterized by “proximity to the lake” and “proximity to the river”, and the newly registered enterprises show changes from “point” to “surface”. There is a significant spatial competition effect on the effects of city expansion on ecosystem health, while there is a significant negative spatial collaboration effect on the effects of industrial activities, and agricultural activities show a significant spatial spillover effect. The results of the study can provide more detailed empirical support for the regulation and management of ecosystem health in global lakeside urban agglomerations.

Can low-carbon transportation construction improve urban green total factor productivity? A quasi-natural experiment based on 282 prefecture-level cities in China.

Total factor productivity in the green economy is a major step forward in fostering robust growth in the economy. Urban green total factor productivity (GTFP) may be increased and carbon emissions decreased through the low-carbon transformation of the transportation sector. To analyze how the pilot policy of low-carbon transportation system construction affects urban GTFP, this study builds a DID model and a spatial Durbin model using panel data from 282 Chinese cities between 2006 and 2021. The findings show that low-carbon transportation systems boost urban GTFP. In addition, the mechanism test shows that low-carbon transportation development increases urban GTFP by optimizing urban industrial structure, expediting economic agglomeration, and encouraging technological innovation. Lastly, the geographical correlation test shows that GTFP is geographically associated and that spatial spillover reduces the impact of low-carbon transportation growth on GTFP. The findings affirm the need to vigorously promote low-carbon transportation systems to aid in the achievement of the carbon neutrality target.

Unravelling habituation for COVID-19-related information: A panel data study in Japan.

This study examines people's habituation to COVID-19-related information over almost three years. Using publicly available data from 47 Japanese prefectures, I analyse how human mobility responded to COVID-19-related information, such as the number of COVID-19-infected cases, the declaration of a state of emergency (DSE), and several doses of vaccine using an interactive effects model, which is a type of panel data regression. The results show that Japanese citizens were generally fearful and cautious during the first wave of the unknown infection. As such, a 1% week-on-week increase in the number of infected cases results in a decrease in human mobility by 1.09-percentage-point (pp) week-on-week. However, they gradually became habituated to similar infection information during the subsequent waves, which is reflected in 0.71 pp and 0.29 pp decreases in human mobility in the second and third waves. Nevertheless, the level of habituation decreased in response to the different types of the infection, such as new variants in the fourth wave, with 0.50 pp decrease. By contrast, regarding the DSE, it is more plausible to consider that human mobility responds to varying requests rather than habituate them. Whereas a rapid vaccination program could alleviate people's concerns. I also find spatial spillovers of infection information on human mobility using a spatial weight matrix included in the regression model. However, there is no evidence of DSE or vaccination spatial spillovers, likely because both are valid only in one's own prefecture. The implementation of flexible human mobility control policies by closely monitoring human mobility can prevent excessive or insufficient mobility control requests. Such a flexible policy can efficiently suppress infection spread and prevent economic activity reduction more than necessary. These implications are useful for evidence-based policymaking during future pandemics.

Digital Economy and Green and Low-Carbon Transformation of Land Use: Spatial Effects and Moderating Mechanisms

The green and low-carbon transformation of land use (GLTLU) is a pressing global issue that requires urgent attention. The digital economy has emerged as a new driver for the GLTLU. However, current research mainly focuses on the measurement and environmental effects of the digital economy, with less exploration of how the digital economy influences the spatial effects and regulatory mechanisms of GLTLU, particularly regarding the differential impacts and specific mechanisms at the regional level. This study uses panel data from 283 cities in China from 2011 to 2019, employing the spatial Durbin model (SDM) and the panel threshold model to examine the spatial and regulatory mechanisms of the digital economy’s impact on GLTLU. The findings reveal that digital economy promotes GLTLU not only within cities but also in surrounding regions. Robustness analyses support this conclusion. Notably, the digital economy’s positive impact on GLTLU in surrounding areas is confined to the central region of China. In contrast, the Yangtze River Delta urban agglomeration experiences a significant negative impact on GLTLU in nearby regions due to the digital economy. The study also identifies that the positive spatial spillover effect of the digital economy on GLTLU reaches its peak at a distance of 450 km. Additionally, the digital economy’s ability to promote GLTLU is contingent upon financial agglomeration levels exceeding 9.1728. Moreover, the local government’s emphasis on the digital economy and intellectual property protection enhances the digital economy’s impact on GLTLU. The promotion effect is maximized when these factors surpass the thresholds of 27.8054 and 3.5189, respectively. Overall, this study contributes to the understanding of how the digital economy influences sustainable land development, highlighting the critical role of regional factors and regulatory mechanisms in amplifying the digital economy’s positive effects on GLTLU.