scholarly journals Spatio-Temporal Variation of Health Production Efficiency Considering Environmental Pollution in China Based on Modified EBM and Spatial Econometric Model

2021 ◽  
Vol 9 ◽  
Author(s):  
Fan Liu ◽  
Gen Li ◽  
Ying Zhou ◽  
Yinghui Ma ◽  
Tao Wang
Keyword(s):  
Temporal Variation ◽  
Production Efficiency ◽  
Econometric Model ◽  
Spillover Effects ◽  
Eastern Region ◽  
Health Production ◽  
Spatial Econometric ◽  
Average Efficiency ◽  
Spatial Econometric Model ◽  
Spatio Temporal

In order to strengthen the construction of China's health industry and improve the health of the people, based on the data of 31 provinces and cities in China from 2009 to 2019, the improved EBM model is used to measure the health production efficiency of each region, and Moran index is used to study the Spatio-temporal variation of health production efficiency of each province. Finally, the spatial econometric model is applied to study the influencing factors of the Spatio-temporal variation of health production efficiency. The results show that generally speaking, the average efficiency of 31 provinces and cities is above 0.7, and the average efficiency of some regions is above 1. From the perspective of time variation, the average efficiency value in the eastern region and the middle region increases from 0.816 to 0.882 and from 0.851 to 0.861, respectively. However, the average efficiency value in the western region and northeast region decreases from 0.861 to 0.83 and from 0.864 to 0.805, respectively. From the perspective of spatial distribution, HH agglomeration and LL agglomeration exist in most regions. By comparing Moran scatter plots in 2009 and 2019, it is found that the quadrants of most regions remain unchanged, and LL agglomeration is the main agglomeration type in local space. There is a significant spatial dependence among different regions. From the perspective of spatial empirical results, Pgdp, Med, and Pd have a positive effect on health production efficiency. The direct effect and indirect effect of Pgdp, Med, and Gov all pass the significance test of 1%, indicating that there are spatial spillover effects of the three indicators. Each region should reasonably deal with the spillover effect of surrounding regions, vigorously develop economic activities, carry out cooperation with surrounding regions and apply demonstration effect to accelerate the development of overall health production.

scholarly journals The Contribution of Technology Finance to the Quality of Economic Growth - Empirical Analysis Based on Spatial Econometric Model

2019 ◽  
Author(s):  
Yuming Xu ◽  
Xu Zhou ◽  
Zhiqiang Li
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Econometric Model ◽  
Entropy Method ◽  
Eastern Region ◽  
Promoting Effect ◽  
Spatial Econometric ◽  
Spatial Econometric Model ◽  
The Relationship

(1) Background: Most of the existing studies focus on the evaluation of technology finance; the relationship between technology finance and technology innovation. But there are few studies on the development of technology finance and the quality of economic development in our country; (2) Methods: Based on the panel data of 30 provinces in China, this paper constructs an index system to measure the development of technology finance through the improved entropy method, and tests the spatial correlation of the development of technology finance in China by Moran'I index. According to the test results, this paper constructs a spatial econometric model to empirically analyze the promoting effect of scientific, technological and financial development on high-quality economic development, and analyzes its promoting effect in different regions and different time periods; (3) Results: The results show that the quality of China's economic growth is spatially dependent, and the development of science, technology and finance can significantly promote the quality economic development in China. And the promotion coefficient of the central region is the largest, as well as the coefficient of the eastern region is the smallest. The promotion coefficient was small and not significant before 2015, and was significantly positive after 2015; (4) Conclusions: this paper puts forward the corresponding policy recommendations according to the research results.

scholarly journals The Impact of Environmental Protection Tax on the Upgrading of Industrial Structure-Based on Spatial Econometric Analysis

2019 ◽  
Vol 131 ◽  
pp. 01070
Author(s):  
Aiping Guan ◽  
Jing Xie ◽  
Yu Meng
Keyword(s):  
Environmental Protection ◽  
Industrial Structure ◽  
Econometric Model ◽  
Positive Impact ◽  
Spillover Effects ◽  
Spatial Correlations ◽  
Spatial Econometric ◽  
Spatial Weight ◽  
Spatial Econometric Model ◽  
The Impact

Based on the provincial panel data of 30 provinces in China from 2000 to 2017, this paper uses the spatial econometric model to analyze the impact of environmental protection tax on the upgrading of industrial structure under three spatial weight matrices. The results show that there are significant positive spatial correlations in the upgrading of provincial industrial structure in China, and environmental protection tax has a significant positive spatial spillover effects on the upgrading of industrial structure. The implementation of environmental protection tax in provinces and regions will promote the upgrading of local industrial structure, which will have a positive impact on the upgrading of industrial structure in neighboring provinces and regions.

Factors Influencing China’s Exports with a Spatial Econometric Model

2015 ◽  
Vol 29 (3) ◽  
pp. 191-211 ◽  
Author(s):  
Kuang-Hann Chou ◽  
Chien-Hsun Chen ◽  
Chao-Cheng Mai
Keyword(s):  
Econometric Model ◽  
Spatial Econometric ◽  
Factors Influencing ◽  
Spatial Econometric Model
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