The Closer the Better? Modeling Spatial Spillover Effects of Ecological Externalities in Coastal Mangroves

As an important part of ecological externalities, the spatial spillover effect has attracted the attention of researchers in the field of environmental economics. However, the traditional view that the spillover mechanism of ecological externalities generally decreases in line with increases in distance remains to be thoroughly proven. Effective ecological management requires an understanding of the relationship between the natural environment and human communities. In this study, the concept of geographical accessibility and a two-step mobile search model are introduced in order to connect ecosystems and humans by a spatial distance. This model can fully demonstrate the external spatial spillover effect of ecology. Based on research from the Beihai Wetland Reserve, Guangxi, China, this study found that the change in the ecological externality spillover mechanism is not only affected by spatial distance but is also affected by the pro-environmental attributes of individual residents around the region. Under the same conditions, residents with a high degree of interaction with ecological protection zones can display a stronger spatial spillover effect. The conclusion of this study provides a more accurate understanding of the changes in the spillover effect of ecological externalities, which in turn can help managers to formulate more adequate ecological protection policies that are based on the specific conditions of different residents. This is crucial for the successful management of protected ecological areas that are highly linked to human communities.

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Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

Tourism Economics ◽

10.1177/13548166211021175 ◽

2021 ◽

pp. 135481662110211

Author(s):

Honghong Liu ◽

Ye Xiao ◽

Bin Wang ◽

Dianting Wu

Keyword(s):

Economic Growth ◽

Spillover Effect ◽

Tourism Development ◽

Spillover Effects ◽

Policy Implications ◽

Long Term Effects ◽

Spatial Spillover ◽

Domestic Tourism ◽

Inbound Tourism ◽

Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

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Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index

Sustainability ◽

10.3390/su13148032 ◽

2021 ◽

Vol 13 (14) ◽

pp. 8032

Author(s):

Chengzhuo Wu ◽

Li Zhuo ◽

Zhuo Chen ◽

Haiyan Tao

Keyword(s):

Influencing Factors ◽

Information Flow ◽

Spillover Effect ◽

Spillover Effects ◽

Urban Agglomeration ◽

Coordinated Development ◽

Spatial Spillover ◽

Urban Agglomerations ◽

Search Index ◽

Spatial Spillover Effect

Cities in an urban agglomeration closely interact with each other through various flows. Information flow, as one of the important forms of urban interactions, is now increasingly indispensable with the fast development of informatics technology. Thanks to its timely, convenient, and spatially unconstrained transmission ability, information flow has obvious spillover effects, which may strengthen urban interaction and further promote urban coordinated development. Therefore, it is crucial to quantify the spatial spillover effect and influencing factors of information flows, especially at the urban agglomeration scale. However, the academic research on this topic is insufficient. We, therefore, developed a spatial interaction model of information flow (SIM-IF) based on the Baidu Search Index and used it to analyze the spillover effects and influencing factors of information flow in the three major urban agglomerations in China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in the period of 2014–2019. The results showed that the SIM-IF performed well in all three agglomerations. Quantitative analysis indicated that the BTH had the strongest spillover effect of information flow, followed by the YRD and the PRD. It was also found that the hierarchy of cities had the greatest impact on the spillover effects of information flow. This study may provide scientific basis for the information flow construction in urban agglomerations and benefit the coordinated development of cities.

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Ecological well-being performance and influencing factors in China: from the perspective of income inequality

Kybernetes ◽

10.1108/k-06-2021-0452 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Lijun Zhou ◽

Zongqing Zhang

Keyword(s):

Income Inequality ◽

Influencing Factors ◽

Spillover Effect ◽

Well Being ◽

Spillover Effects ◽

Content Type ◽

Spatial Spillover ◽

Effective Decision ◽

The Impact ◽

Spatial Spillover Effect

PurposeChina's increasing income inequality might cause a series of problems, such as the slowdown of economic growth, social and economic tension, the decline of the ecological environment quality and the threat to citizens' health. Consequently, income inequality will inevitably affect the ecological well-being performance (EWP) level of China's provinces through the above aspects. Analyzing the impact of income inequality on EWP and its spatial spillover effects are conducive to improving the level of EWP in China. Therefore, the research purpose of this paper is to use China's provincial data from 2001 to 2017 to analyze the impact of income inequality on EWP and the spatial spillover effect based on the evaluation of the EWP value of each province.Design/methodology/approachAt first, this study utilizes the super efficiency slacks-based measure model (Super-SBM model) to calculate the EWP values of 30 provinces in China, which can evaluate and rank the effective decision units in the SBM model and make up for the defect that the effective decision units cannot be distinguished. Then this study applies the spatial Durbin model and Tobit regression model (SDM-Tobit model) to explore the impact of income inequality and other influencing factors on EWP and the spatial spillover effects in adjacent areas.FindingsFirstly, the average EWP in China fluctuated slightly and showed a downward trend from 2001 to 2017. In addition, the EWP values of the provinces in the western region are usually weaker than those in the eastern and central regions. Moreover, income inequality is negatively correlated with EWP, and the EWP has a spatial spillover effect, which means the EWP level in a region is affected by EWP values in the adjacent regions. Furthermore, the industrial structure and urbanization level are both negatively related to EWP, while technology level, investment openness, trade openness and education level are positively related to EWP.Originality/valueCompared with the existing research, the possible contribution of this research is that it takes income inequality as one of the important influencing factors of EWP and adopts the SDM-Tobit model to analyze the impact mechanism of income inequality on EWP from the perspective of time and space, providing new ideas for improving the EWP of various provinces in China.

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Direct Rebound Effect for Electricity Consumption of Urban Residents in China Based on the Spatial Spillover Effect

Energies ◽

10.3390/en12112069 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2069 ◽

Cited By ~ 1

Author(s):

Ying Han ◽

Jianhua Shi ◽

Yuanfan Yang ◽

Yaxin Wang

Keyword(s):

Energy Efficiency ◽

Rebound Effect ◽

Spillover Effect ◽

Electricity Consumption ◽

Spillover Effects ◽

Local Region ◽

Urban Residents ◽

Spatial Spillover ◽

Direct Rebound Effect ◽

Spatial Spillover Effect

Based on methods of price decomposition and spatial econometrics, this paper improves the model for calculating the direct energy rebound effect employing the panel data of China’s urban residents’ electricity consumption for an empirical analysis. Results show that the global spatial correlation of urban residents’ electricity consumption has a significant positive value. The direct rebound effect and its spillover effects are 37% and 13%, respectively. Due to the spatial spillover effects, the realization of energy-saving targets in the local region depends on the implementation effect of energy efficiency policies in the surrounding areas. However, the spatial spillover effect is low, and the direct rebound effect induced by the local region is still the dominant factor affecting the implementation of energy efficiency. The direct rebound effect for urban residents’ electricity consumption eliminating the spatial spillover effect does not show a significant downward trend. The main reason is that the rapid urbanization process at the current stage has caused a rigid residents’ electricity demand and large-scale marginal consumer groups, which offsets the inhibition effect of income growth on the direct rebound effect.

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Spatial Spillover Effects of Air Pollution on the Health Expenditure of Rural Residents: Based on Spatial Durbin Model

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18137058 ◽

2021 ◽

Vol 18 (13) ◽

pp. 7058

Author(s):

Bo Sun ◽

Bo Wang

Keyword(s):

Air Pollution ◽

Direct Effect ◽

Health Expenditure ◽

Spillover Effect ◽

Spillover Effects ◽

Spatial Durbin Model ◽

Rural Residents ◽

Spatial Spillover ◽

The Impact ◽

Spatial Spillover Effect

Background: Air pollution is one source of harm to the health of residents, and the impact of air pollution on health expenditure has become a hot topic worldwide. However, few studies aim at the spatial spillover effects of air pollution on the health expenditure of rural residents (HE-RR), including the impact on the health expenditure in neighboring areas. Objective: Based on the existing research, this paper further introduces the spatial dimension and uses the Spatial Durbin model to discuss the impact of environmental pollution on the health expenditure of rural residents (HE-RR). Methods: Based on provincial panel data during 2002–2015 in China, the Spatial Durbin model was used to investigate the spatial spillover effect of the average annual concentration of PM2.5 (AAC-PM2.5) on the health expenditure of rural residents (HE-RR). Results: There was a significant positive correlation between AAC-PM2.5 and health expenditure of rural residents (HE-RR) in neighboring areas at a significant level of 5% (COEF: 2.546, Z:2.340), that is, AAC-PM2.5 has a spatial spillover effect on PC-HE-RR in neighboring areas, and the spatial spillover effect is greater than the direct effect. The migration and diffusion of PM2.5 pollution will affect the air quality of neighboring areas, leading to the health risk not only from the local PM2.5 pollution but also the nearby PM2.5 pollution. Conclusion: The results show a significant positive relationship between air pollution and HE-RR in neighboring areas, and the spatial spillover effect is greater than the direct effect.

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Measuring the Spatial Spillover Effects of Multimodel Transit System in Beijing: A Structural Spatial Vector Autoregressive Approach

Journal of Advanced Transportation ◽

10.1155/2020/8870449 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Honghai Li ◽

Xiaolei Ma ◽

Xian Zhang ◽

Xin Li ◽

Weihan Xu

Keyword(s):

Spillover Effect ◽

Spillover Effects ◽

Transport Systems ◽

Traffic Patterns ◽

Transit System ◽

Vector Autoregressive ◽

Spatial Spillover ◽

Passenger Flow ◽

Study Results ◽

Spatial Spillover Effect

Changes in local transit passenger flow may cause a spatial spillover effect across the involved regions and affect traffic patterns in other regions. To identify the affected areas and the traffic patterns, this study develops an enhanced spatial vector autoregressive (SpVAR) model to investigate relations in public transport systems in the case of sudden large passenger flow impact. The proposed model captures the interacted correlation within different transit models in separated regions. Three representative commuting regions in Beijing, namely, Zhongguancun, Guomao, and Huilongguan, are employed for empirical study. Results confirm the existence of spatial spillover effect in the commuter regions and reveal heterogeneous effects of multimodal transit system on regions with different distances.

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Spatial Spillover Effect of Financial Flexibility on Investment in China’s Convention and Exhibition Listed Companies

Mathematical Problems in Engineering ◽

10.1155/2020/3926747 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Xiaoqun Liu ◽

Liuchun Yu ◽

Yuchen Zhang ◽

Youcong Chao

Keyword(s):

Spillover Effect ◽

Spillover Effects ◽

Spatial Dimension ◽

Financial Flexibility ◽

Spatial Spillover ◽

The Impact ◽

Exhibition Industry ◽

Different Levels ◽

Spatial Spillover Effect

Financial flexibility is an important research issue in corporate finance. This paper utilizes the Spatial Durbin Model (SDM) to analyze the impact of financial flexibility on the investment of Convention and Exhibition companies listed on the New Third Board from 2014 to 2016. The empirical results show the following. Firstly, the greater the financial flexibility, the more investment the firm will make. Secondly, the enhancement in financial flexibility would lead to an increase in investment of companies in the Convention and Exhibition industry in the local provinces, indicating that the financial flexibility has a significant positive intraregional spatial spillover effect on investment. On the other hand, financial flexibility has spatial spillover effects, and its rise will reduce the investment in other provinces, which could be explained by the competition effect between enterprises. Overall, we have further elucidated the role of different levels of financial flexibility on the investment of the Convention and Exhibition listed enterprises from the spatial dimension, thereby enriching the existing research on corporate financial flexibility and corporate value to some certain extent.

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Empirical Study of the Spatial Spillover Effect of Transportation Infrastructure on Green Total Factor Productivity

Sustainability ◽

10.3390/su13010326 ◽

2020 ◽

Vol 13 (1) ◽

pp. 326

Author(s):

Xi Liang ◽

Pingan Li

Keyword(s):

Total Factor Productivity ◽

Spillover Effect ◽

Spillover Effects ◽

Transportation Infrastructure ◽

Factor Productivity ◽

Spatial Durbin Model ◽

Spatial Spillover ◽

Spatial Spillover Effects ◽

Dynamic Spatial Durbin Model ◽

Spatial Spillover Effect

Transportation infrastructure promotes the regional flow of production. The construction and use of transportation infrastructure have a crucial effect on climate change, the sustainable development of the economy, and Green Total Factor Productivity (GTFP). Based on the panel data of 30 provinces in China from 2005 to 2017, this study empirically analyses the spatial spillover effect of transportation infrastructure on the GTFP using the Malmquist–Luenberger (ML) index and the dynamic spatial Durbin model. We found that transportation infrastructure has direct and spatial spillover effects on the growth of GTFP; highway density and railway density have significant positive spatial spillover effects, and especially-obvious immediate and lagging spatial spillover effects in the short-term. We also note that the passenger density and freight density of transportation infrastructure account for a relatively small contribution to the regional GTFP. Considering environmental pollution, energy consumption, and the enriching of the traffic infrastructure index system, we used the dynamic spatial Durbin model to study the spatial spillover effects of transportation infrastructure on GTFP.

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