Does China’s transportation infrastructure have an impact on employment in the service sector?

Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2737-2753
Author(s):  
Hui Wang ◽  
Meiqing Zhang
Keyword(s):  
Large Scale ◽  
Service Industry ◽  
Spillover Effect ◽  
Transportation Infrastructure ◽  
Content Type ◽  
Inland Waterways ◽  
Spatial Spillover ◽  
Positive Effects ◽  
The Impact ◽  
Spatial Spillover Effect

Purpose The large-scale construction of China’s transportation infrastructure has driven the flow of elements between regions, which has provided convenient conditions for the accumulation of advantageous resources. Design/methodology/approach Based on the panel data of 31 provinces in China in the past 2003-2017 years, this paper applies the spatial econometric model and partial differential method and empirically analyzes the spatial spillover effect of transportation infrastructure on employment in the service industry under four spatial weighting matrices. Findings The results show that for every 1 per cent increase in the level of transportation infrastructure, the employment density of the service industry in the region can be increased by 0.1274 per cent. It is worth noting that roads promote the employment of the service industry more than railways and inland waterways. However, inland waterways have not shown positive effects. The results on spatial spillover of transportation infrastructure indicate that railway has obvious promotion effect on the employment level of service industry in the surrounding area, while the highway has hindered the effect. The spatial spillover effect of inland waterway is not obvious. Originality/value The value of this paper is to consider the impact of China’s transportation infrastructure on employment in a particular industry, especially in the service industry. The research will help to provide empirical evidence for policymakers. The government needs to invest and build transportation infrastructure based on the stage and development potential of the employment development of the regional service industry.

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-Temporal Effects of PM2.5 on Health Burden: Evidence from China

2019 ◽  
Vol 16 (23) ◽  
pp. 4695 ◽  
Author(s):  
Zeng ◽  
Du ◽  
Zhang
Keyword(s):  
Direct Effect ◽  
Spatial Clustering ◽  
Spillover Effect ◽  
Spatial Spillover ◽  
Regulatory Policies ◽  
Health Burden ◽  
Lag Effect ◽  
Pm2.5 Exposure ◽  
The Impact ◽  
Spatial Spillover Effect

By collecting the panel data of 29 regions in China from 2008 to 2017, this study used the spatial Durbin model (SDM) to explore the spatial effect of PM2.5 exposure on the health burden of residents. The most obvious findings to emerge from this study are that: health burden and PM2.5 exposure are not randomly distributed over different regions in China, but have obvious spatial correlation and spatial clustering characteristics. The maximum PM2.5 concentrations have a significant positive effect on outpatient expense and outpatient visits of residents in the current period, and the impact of PM2.5 pollution has a significant temporal lag effect on residents’ health burden. PM2.5 exposure has a spatial spillover effect on the health burden of residents, and the PM2.5 concentrations in the surrounding regions or geographically close regions have a positive influence on the health burden in the particular region. The impact of PM2.5 exposure is divided into the direct effect and the indirect effect (the spatial spillover effect), and the spatial spillover effect is greater than that of the direct effect. Therefore, we conclude that PM2.5 exposure has a spatial spillover effect and temporal lag effect on the health burden of residents, and strict regulatory policies are needed to mitigate the health burden caused by air pollution.

scholarly journals Can Green Finance Optimize Energy Structure: A Spatial Econometric Analysis based on China's Traditional and Renewable Energy Consumption

2021 ◽  
Author(s):  
Hui Wang ◽  
Lili Jiang ◽  
Hongjun Duan ◽  
Yifeng Wang ◽  
Yichen Jiang
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Spillover Effect ◽  
Energy Structure ◽  
Renewable Energy Consumption ◽  
Spatial Spillover ◽  
Consumption Structure ◽  
Green Finance ◽  
The Impact ◽  
Spatial Spillover Effect

Abstract This paper studies the impact of the development of green finance on China’s energy consumption structure. In terms of the construction of the green finance index (GFI), this paper selects 17 basic indexes from the three aspects of economy, finance, and environment, uses the improved entropy weight method to construct the GFI, and studies the spatial spillover effect of the GFI of China's provinces. This paper further studies the impact of green finance on traditional and renewable energy consumption. We first uses panel regression to determine that the development of green finance has a positive effect on the slowdown of traditional energy consumption and acceleration of renewable energy consumption, and then further studies the spatial characteristics of green finance development on energy consumption by using spatial Durbin model. The results show that there is a positive spatial spillover effect in the development of green finance among provinces in China. The development of green finance contributes to the conversion of traditional to renewable energy consumption. The effect of green finance on the transformation of energy consumption structure is mainly reflected in the direct effect. Therefore, the government should support the green finance, reduce traditional energy consumption and increase renewable energy consumption.

scholarly journals Will Policy Uncertainty Deteriorate Haze Pollution? A Spatial Spillover Perspective

2021 ◽  
Vol 18 (19) ◽  
pp. 10229
Author(s):  
Xiulin Qi ◽  
Xin Wang ◽  
Xiao Jin ◽  
Zhenyu M. Wang ◽  
Beibei Zhang ◽  
...  
Keyword(s):  
Direct Effect ◽  
Local Level ◽  
Spillover Effect ◽  
Sustainable Growth ◽  
Policy Uncertainty ◽  
Severe Problem ◽  
Spatial Spillover ◽  
Haze Pollution ◽  
The Impact ◽  
Spatial Spillover Effect

Haze has been a severe problem in China for some time, jeopardizing air quality, public health and sustainable growth. This paper examines the direct effect and spatial spillover effect of policy uncertainty on haze pollution with a spatial panel model, using prefecture-level data from 2004 to 2016. This study shows that: (1) policy uncertainty has increased the level of local haze pollution and has a significant spatial spillover effect on surrounding areas; (2) although local policy uncertainty has increased the haze pollution in geographically adjacent cities, it only affects the cities within the province with similar economic distances; and (3) the policy at the central level can effectively alleviate the impact of policy uncertainty at the local level on haze pollution, especially in relation to the spatial spillover effect, but still has limitations in eliminating the direct effect, which is due to the ineradicable nature of policy uncertainty.

scholarly journals Spatial Spillover Effect of Heterogeneous Environmental Regulation On Ecological Welfare Performance in China

2021 ◽  
Author(s):  
guo bing nan ◽  
tang li ◽  
jia ru ◽  
lin ji
Keyword(s):  
Spatial Distribution ◽  
Environmental Regulation ◽  
Regional Differences ◽  
Environmental Regulations ◽  
Spillover Effect ◽  
Voluntary Participation ◽  
Spatial Spillover ◽  
Different Types ◽  
The Impact ◽  
Spatial Spillover Effect

Abstract This paper constructs a theoretical model to deduce the mechanism of environmental regulation on ecological welfare performance, selects the panel data of 30 provinces in China from 2005 ~ 2019, uses the Super-SBM model to measure the ecological welfare performance of China, and the influence of heterogeneous environmental regulation on ecological welfare performance in China is empirically tested by spatial Durbin model. The results show: (1) there are regional differences in the ecological welfare performance of different provinces in China, which illustrates an unbalanced spatial distribution; (2) there is significant positive spatial correlation between market incentive, command -control and voluntary participation environmental regulation and ecological welfare performance; (3) The impact of different types of environmental regulations on the performance of ecological welfare in China is heterogeneous. Command-control and market incentive environmental regulations can improve the performance of ecological welfare, while voluntary participation environmental regulations have no significant impact on the performance of ecological welfare; (4) From the perspective of spatial spillover effect, command-control environmental regulation is not conducive to the ecological welfare performance of neighboring regions, while market incentive environmental regulation is conducive to the improvement of ecological welfare performance of adjacent areas. The spatial spillover effect of voluntary participation environmental regulation on ecological welfare performance in adjacent areas is not significant.

scholarly journals The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242425
Author(s):  
Wenchao Li ◽  
Jian Xu ◽  
Zhengming Wang ◽  
Jialiang Yang
Keyword(s):  
Technology Innovation ◽  
Spillover Effect ◽  
Low Carbon ◽  
Promotion Effect ◽  
Spatial Spillover ◽  
Sar Model ◽  
The Impact ◽  
Auto Regression ◽  
Spatial Spillover Effect

China has conducted a long-term low-carbon technology innovation (LCTI), but there was a faster increase of CO2 emission in 2017 and 2018 than in 2016, which has lead scholars to doubt the effect of LCTI on CO2 emission. This paper builds a spatial auto regression (SAR) model with provincial panel data from 2011 to 2017 to calculate the spatial spillover effect of China's LCTI on regional CO2 emission. The results show that regional LCTI can reduce the local CO2 emission, but will increase the CO2 emission of adjacent regions due to spatial spillover effect. This produces the uncertainty of the promotion effect of LCTI on China's low-carbon transformation. Therefore, this paper suggests innovation resources should be appropriately and evenly distributed among regions to avoid their agglomeration in few regions.

scholarly journals Reexamining the Impact of Industrial Structure on Haze Pollution Based on the Yangtze River Delta

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 613
Author(s):  
Lu Wang ◽  
Shumin Jiang ◽  
Hua Xu
Keyword(s):  
Yangtze River ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Inhibitory Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Spatial Spillover ◽  
Haze Pollution ◽  
The Impact ◽  
Spatial Spillover Effect

In this study, the static and dynamic spatial Durbin model between industrial structure and haze pollution in Yangtze River Delta is constructed. Later, the spatial spillover effect and time lag effect of haze pollution in Yangtze River Delta are analyzed. The impact of rationalization and upgrading of industrial structure on haze pollution and its spatial spillover effect are discussed. The results show that: (i) PM2.5 has a significant positive spatial spillover effect and time lag effect; (ii) in the short run, the rationalization and upgrading of industrial structure has no inhibitory effect on haze pollution, while the rationalization and upgrading of industrial structure of surrounding cities has an inhibitory effect on local haze pollution; (iii) in the long run, the rationalization and upgrading of industrial structure of surrounding cities have an inhibitory effect on local haze pollution; (iv) economic growth, FDI, the number of Industrial Enterprises above Designated Size, and population density also have spatial spillover effects on haze pollution. Therefore, considering the spatial spillover effect of haze pollution from the perspective of urban agglomeration and long-term, strengthening the joint prevention and control and comprehensive treatment among cities, further promoting the rationalization and upgrading of industrial structure is conducive to reducing haze pollution.

Effects of government supports and credits on Turkish agriculture

2019 ◽  
Vol 9 (4) ◽  
pp. 391-401 ◽  
Author(s):  
Ahmet Ali Koç ◽  
T. Edward Yu ◽  
Taylan Kıymaz ◽  
Bijay Prasad Sharma
Keyword(s):  
Spillover Effect ◽  
Value Added ◽  
Spillover Effects ◽  
Data Set ◽  
Agricultural Output ◽  
Content Type ◽  
Spatial Spillover ◽  
Percent Increase ◽  
Spatial Spillover Effects ◽  
The Impact

Purpose Domestic supports on Turkish agriculture have substantially increased over the past decade while empirical evaluation of their output impact is limited. Also, the existing literature often neglects potential spatial spillover effects of agricultural policies or subsidies. The purpose of this paper is to quantify the direct and spillover effects of Turkish agricultural domestic measures and agricultural credits use on the added agricultural value. Design/methodology/approach This study applied a spatial panel model incorporating spatial interactions among the dependent and explanatory variables to evaluate the impact of government support and credit on Turkish agricultural output. A provincial data set of agricultural output values, input factors and government subsidies from 2004 to 2014 was used to model the spatial spillover effects of government supports. Findings Results show that a one percent increase in agricultural credits in a given province leads to an average increase of 0.17 percent overall in agricultural value-added per hectare, including 0.05 percent from the direct effect and 0.12 percent from the spillover effect. Contrary to agricultural credits, a one percent increase in government supports in a province generates a mixed direct and spillover effects, resulting in an overall reduction of 0.13 percent in agricultural value-added per hectare in Turkey. Research limitations/implications This study could be extended by controlling for climate, biodiversity and investment factors to agricultural output in addition to input and policy factors if such data were available. Originality/value This study fills the gap in the literature by determining the total effect, including direct and spatial spillover effect, of domestic supports and credits on Turkish agricultural value. The findings provide crucial information to decision makers regarding the importance of incorporating spatial spillover effects in the design of agricultural policy.

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