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

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.

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

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.

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

Kybernetes ◽  
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.

scholarly journals Spatial Spillover Effect of New Energy Development on Economic Growth in Developing Areas of China—An Empirical Test Based on the Spatial Dubin Model

2020 ◽  
Vol 12 (8) ◽  
pp. 3249 ◽  
Author(s):  
Jun Bai ◽  
Shixiang Li ◽  
Nan Wang ◽  
Jianru Shi ◽  
Xianmin Li
Keyword(s):  
Economic Growth ◽  
Empirical Test ◽  
Spillover Effect ◽  
Ordinary Least Squares ◽  
Energy Development ◽  
Moran’S I ◽  
Moran's I ◽  
Spatial Spillover ◽  
New Energy ◽  
Spatial Spillover Effect

The development of new energy in developing areas should not only consider the effect on local economic growth, but also give some attention to its spillover effect for economic growth in neighboring areas and take a new path of cluster-style development and cooperative governance. On the basis of Moran’s I and the Spatial Dubin Model (SDM), this paper analyzes the spatial spillover effect of new energy development on economic growth of 21 developing areas in China from 2000 to 2017. The results show that: (1) According to the Moran’s I, there are significant economic agglomeration characteristics in the spatial distributions among different areas in the study area. (2) A comparative study using the mixed Ordinary Least Squares (OLS) method and SDM shows that new energy has a negative spillover effect on the economic growth of neighboring areas when considering spatial factors, but this negative effect is underestimated in the mixed OLS method. (3) In addition to the core explanatory variable, the spatial spillover effect of new energy on economic growth is also affected by control variables, but the degree of impact varies. The results imply that some effective policy measures, such as sustainable development mechanisms, industrial distribution, and comparative innovation, should be taken to encourage new energy development for the high quality growth in developing areas on the national, regional, and global scale.

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

2021 ◽  
Vol 8 ◽  
Author(s):  
Han Wang ◽  
Xiaoyu Yang ◽  
Shuang Li ◽  
Qiwen Zheng ◽  
Xin Nie
Keyword(s):  
Environmental Economics ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Spatial Distance ◽  
Spatial Spillover ◽  
Ecological Protection ◽  
Environmental Attributes ◽  
High Degree ◽  
Geographical Accessibility ◽  
Spatial Spillover Effect

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.

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

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2069 ◽  
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.

scholarly journals Impact of Financial Development and Its Spatial Spillover Effect on Green Total Factor Productivity: Evidence from 30 Provinces in China

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Junhao Zhong ◽  
Tinghui Li
Keyword(s):  
Total Factor Productivity ◽  
Financial Development ◽  
Spillover Effect ◽  
Policy Implications ◽  
Pollutant Emissions ◽  
Factor Productivity ◽  
Spatial Spillover ◽  
Surrounding Areas ◽  
The Relationship ◽  
Spatial Spillover Effect

The relationship between financial development and green economic growth has received much attention in recent years. Research on the relationship between financial development and green total factor productivity (GTFP) is of great importance to China and other countries. This study has attempted to reveal the spatial distribution of China’s provincial GTFP and impact of financial development on GTFP by using the method of GML index based on SBM-DDF and the spatial Durbin model (SDM) during the period 1996–2015. Innovation is added to the SDM to reflect the influencing mechanism of financial development on GTFP. The empirical results show the following: (1) The mean of China’s provincial GTFP showed a U-shaped curve in 1996–2015. (2) China’s provincial financial development promotes the growth of GTFP through innovation channel. The reason is that financial development boosts eco-friendly innovation and the introduction of energy saving technology, leading to a decrease in energy consumption and pollutant emissions. (3) Increasing the level of financial development in the surrounding areas will restrain local GTFP. Our results provide new evidence that China’s regional financial development has a spatial spillover effect. (4) China’s provincial GTFP has a significant spatial positive correlation. Finally, several policy implications can be summarized to China’s 30 provinces.

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

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.

scholarly journals The Moderating Effect of Innovation on the Relationship between Urbanization and CO2 Emissions: Evidence from Three Major Urban Agglomerations in China

2019 ◽  
Vol 11 (6) ◽  
pp. 1633 ◽  
Author(s):  
Yanwen Sheng ◽  
Yi Miao ◽  
Jinping Song ◽  
Hongyan Shen
Keyword(s):  
Co2 Emissions ◽  
Spillover Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Policy Implications ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
The Yrd ◽  
The Relationship ◽  
Spatial Spillover Effect

This study investigates the relationship between urbanization, innovation, and CO2 emissions, with particular attention paid to the issue of how innovation influences the effect of urbanization on CO2 emissions in urban agglomerations, considering the spatial spillover effect between cities. Therefore, based on panel data on 48 cities in the three major urban agglomerations in China from 2001–2015, a spatial econometric model is used to estimate the effect of urbanization and innovation on CO2 emissions. The empirical results indicate that the relationship between urbanization and CO2 emissions follows a U-shaped curve in the Beijing-Tianjin-Hebei (BTH), an N-shaped curve in the Yangtze River Delta (YRD) and an inverted N-shaped pattern in the Pearl River Delta (PRD). Additionally, innovation shows a significantly positive effect on reducing CO2 emissions in the YRD, but does not exert a significantly direct effect on CO2 emissions in the BTH and the PRD. More importantly, innovation played an important moderating role between urbanization and CO2 emissions in the YRD and PRD, suggesting that reducing the positive impacts of urbanization on CO2 emissions depends on innovative development. In addition, urban CO2 emissions presented a clearly negative spatial spillover effect among the cities in the three urban agglomerations. These findings and the following policy implications will contribute to reducing CO2 emissions.

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