scholarly journals Research on the Impact of Expressway on the County Economy Based on a Spatial DID Model: The Case of Three Provinces of China

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xueming Xu ◽  
Changping Liu
Keyword(s):  
Economic Development ◽  
Negative Impact ◽  
Transportation Cost ◽  
Spillover Effects ◽  
Difference In Differences ◽  
Spatial Spillover ◽  
County Economy ◽  
Spatial Spillover Effects ◽  
The Impact ◽  
Stages Of Economic Development

Infrastructure construction results in transportation cost and regional economy changes. Based on the exogenous infrastructure change of a county highway opening as a natural experiment, this paper uses the spatial difference-in-differences (DID) model to analyze the impact of highway construction in three different provinces of China from 2004 to 2017. It was proved that highway connectivity had no significant or negative impact on the economy of the counties in three provinces that the highway passes through. In addition, highway connectivity was claimed to have obvious spatial spillover effects, which could promote the economic development of the whole region. For counties belonging to provinces in different regions and stages of economic development, we establish a spatial DID model that integrates time and space dimensions to study the impact of expressways on county economic development, to make up for the traditional DID model’s dependence on SUTVA assumptions, and to obtain spatial spillover effects.

Total-factor air environmental efficiency and its influencing factors in the areas along the Belt and Road in China: A spatial spillover perspective

2021 ◽  
pp. 0958305X2110151
Author(s):  
Ni-Ni Yin ◽  
Ke-Liang Wang ◽  
Zhen Yao ◽  
Li-Li Ding ◽  
Zhuang Miao
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Fixed Effects ◽  
Spillover Effects ◽  
Environmental Efficiency ◽  
Spatial Spillover ◽  
Positive Effects ◽  
Belt And Road ◽  
Spatial Spillover Effects ◽  
The Belt And Road

In order to promote sustainable economic development in the areas along the Belt and Road in China, it is of great necessity to reduce the negative impact of air pollutants resulting from industrialization and urbanization on the complex and fragile ecological environments of neighboring areas. First, this study estimated the total-factor air environmental efficiency (TFAEE) of 17 provinces along the Belt and Road in China from 2010 to 2017 using a slacks-based measure (SBM) model. Second, the global and local Moran indices were used to test the spatial correlations between TFAEEs. Finally, the spatial factors and spatial spillover effects influencing the TFAEEs were investigated using the spatial Durbin model with spatiotemporal double fixed effects. The results were shown as follows: (1) The total-factor TFAEEs of the areas along the Belt and Road were low and showed significant regional spatial differences during 2010–2017. (2) There was a positive spatial autocorrelation between the TFAEEs of the areas along the Belt and Road, and the spatial distribution generally clustered into High-High and Low-Low concentrations. (3) Economic development and technological innovation played significantly positive effects on TFAEEs of the areas in the Belt and Road, while energy consumption structure had negative effect on it. In addition, although industrial structure and environmental regulation were negatively correlated with TFAEEs, the coefficients were not significant. (4) The positive spatial spillover effect of the TFAEEs of the areas along the Belt and Road was mainly the result of significant environmental regulations and insignificant economic development factors, while the technological innovations, energy consumption structures and industrial structures showed insignificant negative spatial spillover effects.

scholarly journals The Spatial Interaction Effect of Environmental Regulation on Urban Innovation Capacity: Empirical Evidence from China

2021 ◽  
Vol 18 (9) ◽  
pp. 4470
Author(s):  
Ruomeng Zhou ◽  
Yunsheng Zhang ◽  
Xincai Gao
Keyword(s):  
Environmental Regulation ◽  
Industrial Development ◽  
Positive Impact ◽  
Spatial Interaction ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Spatial Spillover ◽  
Innovation Capacity ◽  
Spatial Spillover Effects ◽  
The Impact

This paper applies a spatial econometric model to measure the impact of environmental regulation on urban innovation capacity from a spatial interaction perspective by using panel data from 41 cities in the Yangtze River Delta urban agglomeration from 2009 to 2018. The study findings are as follows: first, environmental regulation has a significant positive impact on urban innovation capacity and a significant positive spatial spillover effect; second, innovation capacity has significant positive spatial dependence; third, city informatization level, government expenditures on science and technology, city economic scale, and industrial development level all positively affect the innovation capacity of neighboring cities and all have positive spatial spillover effects on the innovation capacity of neighboring cities; and finally, city expansion reduces the innovation capacity of a city and has negative spatial spillover effects on the innovation capacity of neighboring cities.

scholarly journals Spatial spillover effects of export-oriented economic development in the Yangtze River Economic Belt

资源科学 ◽  
2019 ◽  
Vol 41 (10) ◽  
pp. 1871-1885
Author(s):  
Bingbing CAI ◽  
Wei ZHAO ◽  
Zhengyang LI ◽  
Hui YANG ◽  
Keyword(s):  
Economic Development ◽  
Yangtze River ◽  
Spillover Effects ◽  
The Yangtze River ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

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.

scholarly journals The Spatial Characteristics of Sustainable Development for Agricultural Products E-Commerce at County-Level: Based on the Empirical Analysis of China

2021 ◽  
Vol 13 (12) ◽  
pp. 6557
Author(s):  
Zhiheng Chen ◽  
Wen Shu ◽  
Hongpeng Guo ◽  
Chulin Pan
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Industrial Development ◽  
Agricultural Development ◽  
Spillover Effects ◽  
Agricultural Products ◽  
Development Economic ◽  
County Level ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

This paper used the sectional data of Chinese counties to analyze the spatial distribution characteristics of sustainable development of e-commerce for agricultural products in China at the county-level. The standard deviation ellipses and Moran’s index were used to research this subject. Then, by constructing spatial measurement models, the spatial spillover effects and influencing factors of the development of county-level agricultural products e-commerce were analyzed from economic development, economic structure, economic vitality, and agricultural development. The results show that: (1) the top 100 counties of agricultural products e-commerce mainly concentrate in southeastern China, spreading along the northeast and southwest; (2) the county-level agricultural products e-commerce shows significant negative spatial spillover effects; (3) the level of economic development and public services have a positive impact on the development of county-level agricultural products e-commerce, while the level of industrial development shows a negative correlation; (4) the level of agricultural development and industrial development have a significant negative external effect on the development of agricultural products e-commerce. This study is of great significance to promote the sustainable development of agricultural products e-commerce, the process of rural urbanization and the optimization of county industrial patterns.

scholarly journals The Spatial Changes of Transportation Infrastructure and Its Threshold Effects on Urban Land Use Efficiency: Evidence from China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 346
Author(s):  
Xinhai Lu ◽  
Mengcheng Wang ◽  
Yifeng Tang
Keyword(s):  
Land Use ◽  
Spillover Effects ◽  
Urban Land ◽  
Urban Land Use ◽  
Transportation Infrastructure ◽  
Spatial Spillover ◽  
Land Use Efficiency ◽  
Use Efficiency ◽  
Spatial Spillover Effects ◽  
The Impact

The development of social production and the agglomeration of the urban population have brought tremendous pressure to transportation infrastructure. However, the impacts of transportation development on urban land use systems have not been well investigated. Under the pressure of limited land resources, the impact of transportation infrastructure on urban land use efficiency (ULUE) is receiving increasing attention from scholars and needs to be explored. By collecting panel data from 30 regions in China from 2003 to 2018, in this study we constructed a spatial Durbin model and a panel threshold regression model to explore the spatial spillover effects and threshold effects of transportation infrastructure on ULUE. The most obvious findings emerging from this study are that (1) ULUE is not randomly distributed over different regions in China, but has an obvious positive spatial correlation; (2) transportation infrastructure has significant positive direct and spatial spillover effects on ULUE and the direct effects of transportation infrastructure (0.823) are significantly stronger than the spatial spillover effects (0.263); (3) the impact of transportation infrastructure on ULUE has a significant double threshold effect, and the threshold values are 4.520 and 6.429 respectively, and with the improvement of transportation infrastructure, its marginal effects on ULUE show a downward trend. This paper provides theoretical support for policymakers to achieve cross-regional cooperation on land use and transportation infrastructure construction and inspirations for sustainable development.

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
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