scholarly journals Spatial spillover effects of capital factor agglomeration on the urban industrial structure upgrading in China: Based on panel data of 284 prefecture-level cities

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258758
Author(s):  
Maosheng Ran ◽  
Cheng Zhao
Keyword(s):  
Panel Data ◽  
Spatial Econometrics ◽  
Urban Governance ◽  
Industrial Structure ◽  
Spatial Relationship ◽  
Spillover Effects ◽  
Spatial Effects ◽  
Spatial Agglomeration ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

The spatial agglomeration of capital factors has become an important force affecting regional economic development and industrial structure. Investigating the spatial relationship of capital factor agglomeration is a key way to accelerate the upgrading of urban industrial structure and realize sustainable development. Based on the panel data of 284 cities in China from 2008 to 2017, we use the theoretical framework of spatial econometrics and estimate the spatial effects of capital factor agglomeration on the upgrading of urban industrial structure. Both the global Moran index and the local Moran scatter chart present that the agglomeration of capital factors and the upgrading index of urban industrial structure shows the characteristics of spatial agglomeration. The results reveal that the agglomeration of capital factors can significantly promote the upgrading of the industrial structure of local and surrounding cities. Still, the spatial spillover effect is not significant. We then explore the possible factors that limit the spatial spillover effects of capital agglomeration. Using the results of the paper, we provide policy suggestions for strengthening urban industrial construction and optimizing the urban governance model.

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 Spatial Spillover Effect and Action Path of Electricity Consumption Driven by China’s Financial Development based on Global Co-integration

2021 ◽  
Author(s):  
Jianjun Xu ◽  
Xuejiao Ma ◽  
Xiaoqing Xu
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Industrial Structure ◽  
Electricity Consumption ◽  
Structure Optimization ◽  
Spillover Effects ◽  
Short Term ◽  
Spatial Spillover ◽  
Spatial Spillover Effects ◽  
Industrial Structure Optimization

Abstract Although studies on the influencing factors of electricity consumption are rich, the focus on the relationship between financial development and electricity consumption is scarce due to the characteristics of financial sector. In fact, the financial development cannot only increase electricity consumption, but also have the spatial spillover effects. Based on the global spatial modelling techniques, the long-term and short-term relationship between financial development and electricity consumption is examined, and the intermediary effect of financial development on electricity consumption through economic growth, urbanization and industrial structure optimization is also verified. Results show that there is a global co-integration relationship between financial development, economic growth, urbanization, industrial structure optimization and China's electricity consumption, rather than a local co-integration relationship. When the short-term change of electricity consumption deviates from the equilibrium state, the global error correction mechanism can promote the unbalanced system to return to equilibrium from time and spatial dimension. This study not only confirms the spatial spillover effects, but also heterogeneous influences of financial development on electricity consumption, which provides new evidence to make relevant policies.

scholarly journals Spatial Spillover Effects of Mega-City Lockdown Due to Covid-19 Outbreak: Evidence from Turkey

2020 ◽  
Vol 13 (26) ◽  
pp. 93-108
Author(s):  
Fatih CELEBIOGLU ◽  
Keyword(s):  
Supply Chain ◽  
Spatial Econometrics ◽  
Spillover Effects ◽  
Regional Level ◽  
Economic Effects ◽  
Economic Conditions ◽  
Large Magnitude ◽  
Spatial Spillover ◽  
Spatial Spillover Effects ◽  
Mega Cities

With the Covid-19 outbreak, academic studies have been started to calculate the economic effects of the outbreak. Since it is not possible to determine when epidemics/pandemics (or large magnitude earthquakes, etc.) occur, their negative economic effects cannot be precisely predicted. Decreasing consumption and supply at the same time, breaking the supply chain, closing businesses and increasing unemployment are rapidly disrupting economic conditions. The measures are mostly related to issues at the macroeconomic level. If a full curfew is imposed throughout the country, economists are working on how it will have an impact on the economy of the whole country. However, the analysis of the effects at the regional level is discussed secondarily. The aim of this study is to simulate the effects of an economic lock-down that might take place in two important mega cities such as Istanbul and Izmir. As a result of this analysis made using spatial econometrics tools; in the event of a lockdown (or earthquake) in mega cities such as İstanbul and/or İzmir, there will be major economic difficulties that will spread wave by wave to the neighbouring cities and then eventually to the whole country.

scholarly journals Does Economic Policy Uncertainty Matter for Healthcare Expenditure in China? A Spatial Econometric Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Pu Bai ◽  
Yixuan Tang ◽  
Weike Zhang ◽  
Ming Zeng
Keyword(s):  
Economic Policy ◽  
Healthcare Expenditure ◽  
Spatial Clustering ◽  
Spillover Effects ◽  
Policy Uncertainty ◽  
Spatial Effects ◽  
Economic Policy Uncertainty ◽  
Spatial Spillover ◽  
Eastern Area ◽  
Spatial Spillover Effects

A growing body of research has documented the determinants of healthcare expenditure, but no known empirical research has focused on investigating the spatial effects between economic policy uncertainty (EPU) and healthcare expenditure. This study aims to explore the spatial effects of EPU on healthcare expenditure using the panel data of 29 regions in China from 2007 to 2017. Our findings show that healthcare expenditure in China has the characteristics of spatial clustering and spatial spillover effects. Our study also shows that EPU has positive spatial spillover effects on healthcare expenditure in China; that is, EPU affects not only local healthcare expenditure but also that in other geographically close or economically connected regions. Our study further indicates that the spatial spillover effects of EPU on healthcare expenditure only exist in the eastern area. The findings of this research provide some key implications for policymakers in emerging markets.

scholarly journals IMPACTS OF EDUCATIONAL FACTORS ON ECONOMIC GROWTH IN REGIONS OF CHINA: A SPATIAL ECONOMETRIC APPROACH

2015 ◽  
Vol 23 (6) ◽  
pp. 827-847 ◽  
Author(s):  
Kangjuan LV ◽  
Anyu YU ◽  
Siyi GONG ◽  
Maoguo WU ◽  
Xiaohong XU
Keyword(s):  
Economic Growth ◽  
Capital Investment ◽  
Cumulative Effect ◽  
Spillover Effects ◽  
Spatial Effects ◽  
Estimation Model ◽  
Spatial Spillover ◽  
Economic Output ◽  
Spatial Spillover Effects ◽  
Educational Factors

This paper investigates the impacts of educational factors on economic growth across 31 provinces during 1996 and 2010 in China. A spatial panel estimation model is applied to study the impacts of education on economic growth taking into account the spatial spillover effects in Feder model and the cumulative effect. The results reveal that (1) educational factors are significantly spatially autocorrelated. Educational factors have spatial spillover effects. Regional differences of education impacts still exist. (2) Average schooling year has a more positive effect on economic output than capital investment and labor force. Basic education might play a more important role in economic growth. (3) Education sector also benefits non-education sectors on economic growth if “spatial effects of economic shocks” are considered. Some policies that may enhance education development and their impacts on economic growth are proposed.

Spatial spillover effects in determining China's regional CO 2 emissions growth: 2007–2010

2017 ◽  
Vol 63 ◽  
pp. 161-173 ◽  
Author(s):  
Bo Meng ◽  
Jianguo Wang ◽  
Robbie Andrew ◽  
Hao Xiao ◽  
Jinjun Xue ◽  
...  
Keyword(s):  
Spillover Effects ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

Responding to Risky Neighbors: Testing for Spatial Spillover Effects for Defensible Space in a Fire-Prone WUI Community

2018 ◽  
Vol 73 (4) ◽  
pp. 1023-1047 ◽  
Author(s):  
Travis Warziniack ◽  
Patricia Champ ◽  
James Meldrum ◽  
Hannah Brenkert-Smith ◽  
Christopher M. Barth ◽  
...  
Keyword(s):  
Spillover Effects ◽  
Defensible Space ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

Pooling in Tourism Demand Forecasting

2018 ◽  
Vol 58 (7) ◽  
pp. 1161-1174 ◽  
Author(s):  
Wen Long ◽  
Chang Liu ◽  
Haiyan Song
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Demand Forecasting ◽  
Spillover Effects ◽  
Ordinary Least Squares ◽  
Spatial Effects ◽  
Tourism Demand ◽  
Forecasting Accuracy ◽  
Demand Models ◽  
Forecasting Performance

This study investigates whether pooling can improve the forecasting performance of tourism demand models. The short-term domestic tourism demand forecasts for 341 cities in China using panel data (pooled) models are compared with individual ordinary least squares (OLS) and naïve benchmark models. The pooled OLS model demonstrates much worse forecasting performance than the other models. This indicates the huge heterogeneity of tourism across cities in China. A marked improvement with the inclusion of fixed effects suggests that destination features that stay the same or vary very little over time can explain most of the heterogeneity. Adding spatial effects to the panel data models also increases forecasting accuracy, although the improvement is small. The spatial distribution of spillover effects is drawn on a map and a spatial pattern is recognized. Finally, when both spatial and temporal effects are taken into account, pooling improves forecasting performance.

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