Research on the Spatial Effect of Green Economic Efficiency in China from the Perspective of Informatization

2020 ◽  
Author(s):  
Xinbao Tian ◽  
Chuanhao Yu
Keyword(s):  
Industrial Structure ◽  
Spillover Effect ◽  
Coordination Mechanism ◽  
Green Economy ◽  
Spatial Econometric ◽  
Index Method ◽  
Spatial Spillover ◽  
Regional Coordination ◽  
Comprehensive Index Method ◽  
Spatial Spillover Effect

Abstract Background: Green economy has been paid more and more attention in the information age. Informatization plays an important role in the development of green economy by the transmission of industrial structure rationalization and upgrading. Because of the spatial mobility of information, it is necessary to study the spatial spillover effect of information on the efficiency of green economy. In this paper, the non-radial directional distance function and the comprehensive index method are used to evaluate the efficiency of green economy and informatization respectively. On this basis, the spatial characteristics of the two are analyzed. Finally, the spatial econometric model is used to analyze the spatial impact of informatization on the efficiency of green economy. Results: The following findings can be drawn: (i)The spatial distribution of the green economy efficiency and informatization are unbalanced; (ii) There is a significant spatial spillover effect in the efficiency of green economy; (iii) The development of informatization plays an important impact on the efficiency of green economy. Conclusions: It can be seen that informatization plays an important role in the development of green economy, so we can get the following suggestions: (i) Developing green economy according to different conditions of different places. (ii) Establishing regional coordination mechanism of green economic development. (iii) Using informatization to promote the development of green economy.

scholarly journals The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shen Zhong ◽  
Hongli Wang
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Factor Productivity ◽  
Spatial Econometric ◽  
Spatial Spillover ◽  
Negative Case ◽  
Forestry Industry ◽  
The Impact ◽  
Spatial Spillover Effect

AbstractForestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions.

scholarly journals Effect of Complex Road Networks on Intensive Land Use in China’s Beijing-Tianjin-Hebei Urban Agglomeration

Land ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 532
Author(s):  
Chen Zeng ◽  
Zhe Zhao ◽  
Cheng Wen ◽  
Jing Yang ◽  
Tianyu Lv
Keyword(s):  
Land Use ◽  
Road Network ◽  
Spillover Effect ◽  
Urban Agglomeration ◽  
Land Use Intensity ◽  
Spatial Econometric ◽  
Spatial Spillover ◽  
The Road ◽  
Intensive Land Use ◽  
Spatial Spillover Effect

Coupled with rapid urbanization and urban expansion, the spatial relationship between transportation development and land use has gained growing interest among researchers and policy makers. In this paper, a complex network model and land use intensity assessment were integrated into a spatial econometric model to explore the spatial spillover effect of the road network on intensive land use patterns in China’s Beijing–Tianjin–Hebei (BTH) urban agglomeration. First, population density, point of interest (POI) density, and aggregation index were selected to measure land use intensity from social, physical, and ecological aspects. Then, the indicator of average degree (i.e., connections between counties) was used to measure the characteristics of the road network. Under the hypothesis that the road network functions in shaping land use patterns, a spatial econometric model with the road network embedded spatial weight matrix was established. Our results revealed that, while the land use intensity in the BTH urban agglomeration increased from 2010 to 2015, the road network became increasingly complex with greater spatial heterogeneity. The spatial lag coefficients of land use intensity were positively significant in both years and showed a declining trend. The spatially lagged effects of sector structure, fixed asset investment, and consumption were also significant in most of our spatial econometric models, and their contributions to the total spillover effect increased from 2010 to 2015. This study contributes to the literature by providing an innovative quantitative method to analyze the spatial spillover effect of the road network on intensive land use. We suggest that the spatial spillover effect of the road network could be strengthened in the urban–rural interface areas by improving accessibility and promoting population, resource, and technology flows.

scholarly journals Foreign Trade, FDI and the Upgrading of Regional Industrial Structure in China: Based on Spatial Econometric Model

2020 ◽  
Vol 12 (3) ◽  
pp. 815 ◽  
Author(s):  
Shan-Li Wang ◽  
Feng-Wen Chen ◽  
Bing Liao ◽  
Cuiju Zhang
Keyword(s):  
Foreign Trade ◽  
Industrial Structure ◽  
Econometric Model ◽  
Spillover Effect ◽  
Spatial Effects ◽  
Spatial Agglomeration ◽  
Significance Level ◽  
Spatial Spillover ◽  
Spatial Spillover Effect ◽  
Regional Industrial Structure

The upgrading of industrial structure is the core means of coordinating economic development and environment protection. Its spatial agglomeration can also reduce environmental pollution partly. The upgrading of China’s industrial structure has become an important issue concerned by the whole society. To better understand this issue, based on the provincial data of China (1997–2017), this paper strives to explore the spatial effects of foreign trade and foreign direct investment (FDI) on the upgrading of China’s regional industrial structure by constructing the weight matrix of economic distance, and by introducing the spatial autocorrelation analysis method and spatial panel econometric model. The results show that: 1. The Moran’s I index of China’s import, export, FDI, and industrial structure upgrading has passed the 5% significance level test, displaying remarkable spatial agglomeration characteristics. 2. Foreign trade and FDI are important driving factors to upgrade China’s industrial structure. 3. Foreign trade has a significant spatial spillover effect. Imports and exports can not only promote the upgrading of local industrial structure, but also radiate to other regions, promote or inhibit the development of its industry, and further affect the national data. 4. The spatial spillover effect of FDI is not significant. Finally, some policy suggestions are put forward.

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.

scholarly journals Internet Development and Environmental Quality—Evidence from the Development of Chinese Cities

2021 ◽  
Vol 13 (20) ◽  
pp. 11308
Author(s):  
Xiaoying Zhong ◽  
Ruhe Xie ◽  
Peng Chen ◽  
Kaili Ke
Keyword(s):  
Environmental Quality ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Mediating Effect ◽  
The Internet ◽  
Eastern Region ◽  
Spatial Spillover ◽  
Internet Development ◽  
The Impact ◽  
Spatial Spillover Effect

Based on the data of the 283 prefecture-level cities in China from 2003 to 2018, this paper examines the impact of Internet development on environmental quality. The results show that China’s urban PM2.5 has a significant spatial spillover effect. In general, the Internet has a significant negative direct effect on urban environmental pollution, which means that the development of the Internet can improve urban environmental quality. This result remains robust under different methods. As the Internet has evolved over the years, its influence on environmental quality has increased and became more and more significant. In terms of regions, the spatial spillover effect of PM2.5 shows a pattern of eastern region < central region < western region < northeast region, where the eastern region is the only region with a statistically significant negative value for the coefficient, which indicates the direct effects of Internet development on the environmental quality. In addition, the statistic testing on mediating effect shows that the Internet’s effect on urban environment quality is mainly transmitted through the upgrading of industrial structure. With the industrial structure being used as the threshold variable, the influence of Internet development on environmental quality could be divided into two stages.

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.

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