Positive Spatial Spillover Effect Research Articles

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.

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.

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.

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.

Does higher vocational education matter for rural revitalization? Evidence from China

The association between higher vocational education and rural revitalization is an essential economic and social issue, especially in a country with a large population and a developing education system like China. This study uses panel data from 30 provinces in China from 2007 to 2020 to explore the association between higher vocational education and rural revitalization. The empirical results show that, at the national level, both the scale and the quality of higher vocational education significantly promote rural revitalization; the effects of higher vocational education on rural revitalization vary by region: in the eastern and central regions, the scale of higher vocational education significantly promotes rural revitalization, while in the western regions, the quality of higher vocational education significantly promotes rural revitalization; the scale of higher vocational education has a positive spatial spillover effect on rural revitalization, while the quality of higher vocational education only has a significant positive effect on the local level of rural revitalization. Furthermore, the effects of higher vocational education on rural revitalization exhibit a threshold effect based on the economic development level and the urban-rural income gap. This study reveals relationships between higher vocational education and rural revitalization, providing references for policymakers and investors.

The spatial spillover effects of regional integration on carbon emissions

The Yangtze River Delta (YRD) region serves as the leading economic force of the Yangtze River Economic Belt (YREB) in China. It is crucial for the region to take a leadership role in regional integration to facilitate carbon emission reduction. This paper employs a spatial econometric model to examine the impact, spatial spillover effect, and mechanisms of regional integration on carbon emissions in the Yangtze River Delta, using data from 41 cities in the region from 2008 to 2019. The results indicate that there is an inverted U-shaped relationship between the level of regional integration and carbon emissions, with emissions initially increasing before decreasing. Additionally, the impact of regional integration on carbon emissions exhibits a positive spatial spillover effect and threshold characteristics, with carbon emissions inhibited and a positive spatial spillover observed once the threshold is exceeded. Moreover, regional integration reduces carbon emissions through the upgrading of industrial structures and the innovation of green technology. Implications for carbon emission reduction include: actively integrating into the Yangtze River Delta regional integration development; strengthening cross-regional carbon emission synergistic governance; and promoting carbon emission reduction through mechanisms such as promoting industrial upgrading and low-carbonization development, as well as incentivizing technological innovation.

The impact of digital economy on China’s green-oriented transition of energy: multiple mediation effects from a spatial perspective

With the continuous advancement of the new generation of information technology revolution, digital economy is gradually becoming an important driving force for energy transition while restructuring the new form of the economy. This paper selects panel data of 30 provinces in China from 2011 to 2021, empirically verifies the special impacts of digital economy on green-oriented transition of energy by using the spatial Durbin model, and further constructs a multi-intermediary model to verify its transition pathways. The main findings are as follows: First, the overall level of green-oriented transition of energy in China’s eastern coastal areas is relatively high, and the western regions have been more capable of catching up in recent years. Second, digital economy has played a significant role in promoting green-oriented transition of energy, and there is a positive spatial spillover effect. Third, digital economy could indirectly promote the green-oriented transition of energy by promoting the upgrading of industrial structure, improving the level of technological innovation and strengthening environmental regulations. This study provides empirical insights and reference for policymakers in accelerating the comprehensive green-oriented transition of energy.

Asymmetric spatial competition and dynamics in digitalization: Will public R&D support and marketization exacerbate spatial polarization?

This paper investigates the asymmetric spatial spillover effects of digital development across different types of cities. The results of the two-regime spatial Durbin models, using the panel data of 279 cities in China from 2011 to 2021, reveal the spatial polarization phenomenon in digitalization, where stronger cities such as smart cities, provincial capitals, and port cities become more dominant while weaker cities struggle to catch up. Increasing public R&D support leads to positive spatial spillover effects but exacerbates the spatial “Matthew effect” of digitalization. Additionally, marketization plays a moderating role by enhancing resource allocation efficiency and suppressing negative spatial spillover effects. Higher levels of marketization result in smaller digital gaps between cities. The findings provide valuable insights for decision-makers and stakeholders seeking to foster balanced and inclusive urban development in the digital age.

The impact of institutional proximity on digital technology innovation linkages: empirical evidence on the Guangdong-Hong Kong-Macao greater bay area of China

ABSTRACT Promoting digital technology innovation connections is crucial to establishing an international science, technology, and innovation hub in the Guangdong-Hong Kong-Macao Greater Bay Area, and institutional disparities influence the clustering and flow of digital technology as an innovation factor. Promoting digital technology links and cooperation across cities is a practical strategy to improve the region's innovation efficiency and capacity. However, detailed research on the flow of innovation determinants such as digital technology and there is no evidence of the influence of institutional proximity on digital technology innovation connections. Based on the patent transfer data of the National Key Industry Patent Information Service Platform from 2010 to 2021, this paper constructs a new institutional proximity indicator applicable to the Guangdong-Hong Kong-Macao Greater Bay Area and other cross-system regions, applies a spatial econometric model to investigate direct and spatial spillover effects of institutional proximity on the digital technological innovation linkages. It is proved that institutional proximity has significant positive direct and spatial spillover effects on digital technological innovation linkages. The study has significant theoretical and practical implications for increasing the association and collaboration of digital technology and other innovation elements across institutional boundaries.

Unlocking a greener future: The role of digital finance in enhancing green total factor energy efficiency

The development of digital finance provides new opportunities for improving energy efficiency and promoting green development. This paper calculates green total factor energy efficiency (GTFEE) using the super-efficiency SBM model and examines the impact of digital finance on GTFEE. Digital finance has a significant positive impact on GTFEE. Under a bank-dominated financial structure, the positive impact of digital finance on GTFEE is quite significant. In regions with intense banking competition, a large amount of green credit, and lower resource dependence, digital finance is conducive to enhancing GTFEE. Optimizing the allocation efficiency of production factors is an essential mechanism for digital finance to encourage improvements in GTFEE. Digital finance alleviates distortions in factor markets and enhances the matching of the marginal output and the price of capital, labor, and energy factors, thereby facilitating improvements in GTFEE. Further analysis indicates that digital finance has a significant, positive spatial spillover effect on GTFEE, enhancing GTFEE levels in both local and neighboring regions. This study enriches the research on the relationship between digital finance and energy efficiency and provides theoretical foundations and policy references for how digital finance can better serve the green transition of the economy.

The Relationship between the Construction of Transportation Infrastructure and the Development of New Urbanization

Transport infrastructure plays a crucial role in facilitating the high-quality development of new urbanization. Based on the provincial panel data of 31 provinces in China from 2013 to 2020, this study empirically analyzed the impact and mechanism of transportation infrastructure on the high-quality development of new urbanization from multiple perspectives. The results showed that transportation infrastructure can significantly promote the development of new urbanization, and the promoting effect was significantly positive in the eastern and western regions, while it was positive but not significant in the central region. Transportation infrastructure can promote the development of new urbanization by promoting industrial agglomeration. When the population density is lower than the corresponding threshold value, the transport infrastructure can significantly promote the development of new urbanization; when the population density is higher than the corresponding threshold value, the transport infrastructure will significantly hinder the development of new urbanization. Transport infrastructure has a significant positive spatial spillover effect on the development of new urbanization, and the positive spatial spillover effect has been significant in the eastern, central and western regions.

Impact of green finance on China's pollution reduction and carbon efficiency: Based on the spatial panel model

Green finance is an important means to promote the construction of ecological civilization and plays an important role in promoting the coordinated governance of pollution and carbon reduction. Based on the panel data of 277 cities at or above the prefecture level in China from 2006 to 2021, this study calculates the development level of green finance and the synergistic efficiency of pollution and carbon reduction. In addition, this study constructs the driving distance matrix. The study uses the spatial Durbin model to conduct an empirical test on the spatial effect and transmission mechanism of green finance on the synergistic efficiency of pollution and carbon reduction. Results show that: (1) A significant spatial difference exists between the development level of green finance and the collaborative efficiency of pollution and carbon reduction in China from 2006 to 2021. Moreover, the high-value areas of the two are concentrated in the eastern and southeast coastal areas, respectively; (2) The development of green finance has a positive spatial spillover effect on the collaborative efficiency of pollution and carbon reduction. The conclusion remains after a series of robustness tests, that is, green finance has a significant positive promoting effect on the collaborative efficiency of pollution and carbon reduction between the city and its neighboring cities; (3) The development of green finance can promote the improvement of the collaborative efficiency of pollution and carbon reduction by improving the level of green technology innovation and the advanced level of industrial structure, that is, the two play an intermediary effect. The conclusions of this study provide experience for an in-depth understanding of the environmental governance effect of green finance and actively guide financial resources to participate in the collaborative governance of carbon pollution.

Convergence Analysis and Testing of Regional Effects of Green Finance on The Growth of Renewable Energy

ABSTRACT A paradigm shift in energy production and use is essential in the pursuit of carbon peaking and neutrality, and the expansion of renewable energy is a cornerstone of such a shift. This article first proposes an index that comprehensively measures renewable energy development in 30 provinces in China from 2010 to 2022. Then, the σ and β convergence models are applied to investigate the uniformity of renewable energy development. Furthermore, a spatial Durbin model is estimated to examine the spatial impact of green finance on renewable energy development. The results show that from 2010 to 2020, China has witnessed a significant increase in renewable energy use in its eastern, central and western regions, with the western region accelerating faster than its counterparts. During the same period, a remarkable trend of high convergence in renewable energy development has been observed, despite a slowdown in the spatial convergence rates between the central, eastern, western and national levels. The positive spatial spillover effect of renewable energy has increased significantly. The growth of renewable energy in the region and its surrounding areas is positively influenced by the growth of green finance.

Evolutionary Characteristics, Regional Differences and Spatial Convergence of China’s Sustainable Agricultural Development Level

Sustainable agricultural development is a fundamental requirement and a crucial goal of modern agriculture. It is also a significant means of enabling farmers to increase their incomes. This paper analyses the evolutionary characteristics, regional differences and spatial convergence of the level of sustainable agricultural development using kernel density estimation, Dagum’s Gini coefficient and the spatial convergence model based on panel data from 30 provinces in China from 2012 to 2021.The results show that: (1) At the level of development, the level of sustainable agricultural development at the national level and in the three major regions has shown an upward trend with fluctuations, with the average level of development in the eastern and central parts of the country higher than the national average, and in the western part of the country lower than the national average; however, the growth rate in the western part of the country is the highest among the three major regions. (2) In terms of evolutionary characteristics, the level of sustainable agricultural development in the country and the three major regions is characterised by spatial agglomeration, with varying degrees of polarisation. (3) In terms of regional differences, the Gini coefficients for the country as a whole, within the three major regions and between regions, generally show a downward trend, with interregional differences remaining the main source of overall differences. (4) In terms of spatial convergence, there is σ-convergence and β-convergence in the level of sustainable agricultural development across the country and the three major regions, and there is a positive spatial spillover effect. The conditional β convergence results show that the eastern region has the fastest rate of convergence. The above findings provide a scientific basis for the formulation of policies related to sustainable agricultural development in China.

Spatial spillover effects of the digital economy on the green total factor productivity of China’s manufacturing industry

The rapid expansion of the digital economy has garnered significant attention because of its potential to drive high-quality advancement in traditional sectors, particularly manufacturing. This study examines the spatial dynamics and potential spatial disparities between the digital economy and green total factor productivity (GTFP) in China’s manufacturing sector. We utilize a novel set of indicators to assess the advancement of the digital economy during Chinese provinces and apply spatial econometric models to investigate its spatial influence on GTFP. The main research content and conclusions of this study are as follows. (1) By employing a novel index system to quantify the digital economy’s advancement level within the manufacturing sector across various provinces in China, and utilizing it as the primary explanatory variable, the index system demonstrates significant efficacy in empirical analysis and is both scientifically robust and methodologically sound. (2) Using the spatial Dubin model, this study analyzes the spatial effects of the digital economy on the GTFP of the manufacturing sector and finds that it has a dominant positive spatial spillover effect on the GTFP of the manufacturing industry nationwide. (3) The results show that the effects of digital economy advancement on GTFP in the manufacturing industry have a positive spatial spillover effect in the eastern and central area, whereas it is negative in the western area. This study extends the applicability of the new economic geography and imperfect competition theories to the digital economy era, thereby contributing to these academic fields. Moreover, it introduces a novel analytical framework for assessing the digital economy’s influence on manufacturing advancement. The findings provide valuable insights and policy recommendations for fostering the development of the digital economy advancement across diverse regions in China.

Role of scientific and technological innovations on industrial upgradation in China: A spatial econometric analysis.

China is in a phase of high-quality development, where scientific and technological innovations are serving as the primary driving force for its development strategy. This emphasis on innovations is expected to fuel the upgrading of the industrial structure. This study investigates the role of scientific and technological innovations in industrial upgradation in China using spatial econometric analysis. Leveraging the data of 31 provinces of China from 2005 to 2022, we employed a spatial Durbin model to determine the spatial spillover effects of scientific and technological innovations on industrial upgradation. Our findings reveal the significant positive spatial spillover effects, indicating that provinces with higher levels of scientific and technological innovations tend to experience greater industrial upgradation, which in turn contributes to regional economic development. Furthermore, the findings suggest a strong spatial correlation between innovation and the upgrading of industrial structures, indicating that regional innovations have the potential to drive China's industrial upgradation. These results underscore the critical role of scientific and technological innovations in promoting industrial upgradation and regional development in China.

The spillover effects of China’s carbon trading policy on coordinated emission efficiency

The significance of carbon trading policy (CTP) for China’s carbon reduction goals cannot be overstated. Examining the practical impacts and inherent features of this policy is crucial for fostering its healthy development and effectiveness. This study utilizes the directional SBM super-efficiency model to calculate the combined emission efficiency (CEE) of greenhouse gases and atmospheric pollutants across 30 provinces and cities in China from 2005 to 2020. Through spatiotemporal analysis of the CEE evolution using hotspot analysis, it is evident that hotspots gradually shift towards the southeast coastal areas over time, while cold spots shift towards the northwest. Additionally, employing the differences-in-differences (DID) model and conducting robustness tests, the study finds that the CTP significantly enhances the CEE development. Spatial econometric analysis reveals that the CEE primarily follows a distribution pattern characterized by low-low (LL) and high-high (HH) regions, with positive spatial spillover effects. However, due to the incomplete state of early green development in China, the CTP temporarily exhibits negative spatial spillover effects. Finally, considering the current state of China's carbon trading policy, corresponding policy recommendations are proposed in this paper.

A spatial perspective on the impact of digital financial inclusion on the employment structure of the labour force: Evidence from Chinese cities

Abstract In the context of big data, the rise of digital inclusive finance is driving the digital transformation of various industries, which in turn, has a profound impact on labour employment. Based on the panel data of 258 prefecture-level cities in China from 2011 to 2021, this article evaluates the impact of digital financial inclusion on the employment structure of the labour force and investigates its spatial spillover effects by constructing a spatial Durbin model and a mediation model. The study finds that: (1) Digital financial inclusion increases the employment demand for high-skilled and low-skilled labour and decreases the employment demand for middle-skilled labour, that is, the employment structure of the labour force shows a polarisation trend. (2) There is a positive spatial spillover effect of the impact of the development of digital financial inclusion on the demand for high- and low-skilled labour. (3) Financial digitisation plays an intermediary role in the process of digital financial inclusion affecting the employment structure of the labour force. Taking advantage of the dividends brought about by the development of digital inclusive finance and formulating policies according to the actual situation of each region indicate an undeniable choice for achieving full employment.

Identifying determinants of spatial agglomeration of healthcare resources by using spatial econometric methods: a longitudinal study in China.

Healthcare resources are necessary for individuals to maintain their health. The Chinese government has implemented policies to optimize the allocation of healthcare resources and achieve the goal of equality in healthcare for the Chinese people since the implementation of the new medical reform in 2009. Given that no study has investigated regional differences from the perspective of healthcare resource agglomeration, this study aimed to investigate China's healthcare agglomeration from 2009 to 2017 in China and identify its determinants to provide theoretical evidence for the government to develop and implement scientific and rational healthcare policies. The study was conducted using 2009-2017 data to analyze health-resource agglomeration on institutions, beds, and workforce in China. An agglomeration index was applied to evaluate the degree of regional differences in healthcare resource allocation, and spatial econometric models were constructed to identify determinants of the spatial agglomeration of healthcare resources. From 2009 to 2017, all the agglomeration indexes of healthcare exhibited a downward trend except for the number of institutions in China. Population density (PD), government health expenditures (GHE), urban resident's disposable income (URDI), geographical location (GL), and urbanization level (UL) all had positive significant effects on the agglomeration of beds, whereas both per capita health expenditures (PCHE), number of college students (NCS), and maternal mortality rate (MMR) had significant negative effects on the agglomeration of institutions, beds, and the workforce. In addition, population density (PD) and per capita gross domestic product (PCGDP) in one province had negative spatial spillover effects on the agglomeration of beds and the workforce in neighboring provinces. However, MMR had a positive spatial spillover effect on the agglomeration of beds and the workforce in those regions. The agglomeration of healthcare resources was observed to remain at an ideal level in China from 2009 to 2017. According to the significant determinants, some corresponding targeted measures for the Chinese government and other developing countries should be fully developed to balance regional disparities in the agglomeration of healthcare resources across administrative regions.