Transportation, economic growth and spillover effects: The conclusion based on the spatial econometric model

2010 ◽  
Vol 5 (2) ◽  
pp. 169-186 ◽  
Author(s):  
Angang Hu ◽  
Shenglong Liu
2021 ◽  
Vol 9 ◽  
Author(s):  
Fan Liu ◽  
Gen Li ◽  
Ying Zhou ◽  
Yinghui Ma ◽  
Tao Wang

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.


2022 ◽  
Vol 88 ◽  
pp. 104432
Author(s):  
Yoo Ri Kim ◽  
Anyu Liu ◽  
Jason Stienmetz ◽  
Yining Chen

Author(s):  
Yuming Xu ◽  
Xu Zhou ◽  
Zhiqiang Li

(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.


Jurnal Varian ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 153-158
Author(s):  
Siti Soraya ◽  
Baiq Candra Herawati ◽  
Muttahid Shah ◽  
Syaharuddin Syaharuddin

Gross Regional Domestic Product (GRDP) is a reflection of a region's economic growth. West Nusa Tenggara (NTB) is one of the provinces that contributes to good GRDP for Indonesia. The purpose of this research is to modeling GRDP in NTB using spatial econmetrics. The data used is the GRDP data of each district / city in NTB Province as a response variable and factors that affect the number of workers, capital value and electrification ratio as predictor variables. The results showed that there is a spatial dependence on the district / city GRDP in NTB Province on the error model so that the model formed is the Spatial Error Model (SEM) with a rho of 71.1% and an AIC value of 173.34.


2019 ◽  
Vol 131 ◽  
pp. 01070
Author(s):  
Aiping Guan ◽  
Jing Xie ◽  
Yu Meng

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.


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