Evaluating the spatial spillover effects of transportation infrastructure on agricultural output across the United States

Based on provincial panel data observed over the 2005–2014 period, we analyze the impacts of transportation infrastructure investments on inventory levels in China’s manufacturing sector. Our results indicate that transportation infrastructure investments do not reduce inventory levels in the manufacturing sector in China. This conclusion is different from the results in the previous literature, which demonstrate positive effects of transportation investments on reducing inventory levels. The difference can be partly explained by the ongoing inland shift of industry and geographic market expansion in China, which lead to longer transportation distances and longer lead times from suppliers to customers. We also find that road investments have spatial spillover effects overall, and the impacts of different types of road investments differ significantly from each other. Railway investments, however, do not have spatial spillover effects. Finally, we present several policy implications of transportation infrastructure investments, inland shifts of industry, and geographic market expansion.

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Effects of government supports and credits on Turkish agriculture

Journal of Agribusiness in Developing and Emerging Economies ◽

10.1108/jadee-11-2018-0164 ◽

2019 ◽

Vol 9 (4) ◽

pp. 391-401 ◽

Cited By ~ 3

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.

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Government Competition, Transportation Infrastructure Construction and Industrial Agglomeration

Journal of Business Administration Research ◽

10.5430/jbar.v10n1p1 ◽

2021 ◽

Vol 10 (1) ◽

pp. 1

Author(s):

Yanru Deng ◽

Yixin Wang

Keyword(s):

Estimation Method ◽

Spillover Effects ◽

Measurement Model ◽

Transportation Infrastructure ◽

Transport Infrastructure ◽

Industrial Agglomeration ◽

Infrastructure Development ◽

Partial Differential ◽

Spatial Spillover ◽

Spatial Spillover Effects

This paper uses the prefecture-level data from 2003 to 2016 of the Yangtze River Delta region of China and uses the spatial Dubin model(SDM) to study the promotion effect of transportation infrastructure on industrial agglomeration and the spatial spillover effect: First, it is found that there is a significant positive spatial correlation between transportation infrastructure development at the prefecture and city level governments in China, which supports the hypothesis of intergovernmental transport infrastructure competition in this paper; secondly, the regression of the spatial measurement model proves that transportation infrastructure has a certain role in promoting regional industrial agglomeration, and enhances the level of industrial agglomeration in the surrounding areas through spatial spillover effects; in addition, this article uses the Spatial Dubin Model(SDM)) partial differential decomposition method to explore the spatial spillover effects of transportation infrastructure on the flow of elements (this paper explores the spatial spillover effects of transport infrastructure on factor mobility using a partial differential decomposition of the Spatial Durbin Model(SDM)); finally, the robustness of the results of this paper is tested using the replacement space weight matrix and estimation method.

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FOREIGN BIAS OF SOVEREIGN WEALTH FUND AND SPATIAL SPILLOVER EFFECTS

The Singapore Economic Review ◽

10.1142/s021759081747004x ◽

2019 ◽

Vol 64 (02) ◽

pp. 377-397

Author(s):

HONGXIA ZHANG ◽

HEEHO KIM

Keyword(s):

Foreign Investment ◽

Spillover Effects ◽

The United States ◽

Sovereign Wealth Fund ◽

Spatial Spillover ◽

Spatial Panel ◽

The United Kingdom ◽

Bias Model ◽

Spatial Panel Data ◽

Spatial Spillover Effects

This study explores a foreign bias model to examine if the degree of foreign bias of sovereign wealth fund depends on the spatial spillover effects of cultural distances. Using the spatial panel data of foreign investment by sovereign wealth fund in 2008–2014, we empirically test (1) whether the relationships between return, risk and foreign bias of sovereign wealth fund are statistically significant and (2) whether this relationship depends on the spatial spillover effects of cultural distances. The evidence strongly supports our hypotheses across six target countries (Australia, Canada, China, Germany, the United Kingdom and the United States).

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

Land ◽

10.3390/land10040346 ◽

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.

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Empirical Study of the Spatial Spillover Effect of Transportation Infrastructure on Green Total Factor Productivity

Sustainability ◽

10.3390/su13010326 ◽

2020 ◽

Vol 13 (1) ◽

pp. 326

Author(s):

Xi Liang ◽

Pingan Li

Keyword(s):

Total Factor Productivity ◽

Spillover Effect ◽

Spillover Effects ◽

Transportation Infrastructure ◽

Factor Productivity ◽

Spatial Durbin Model ◽

Spatial Spillover ◽

Spatial Spillover Effects ◽

Dynamic Spatial Durbin Model ◽

Spatial Spillover Effect

Transportation infrastructure promotes the regional flow of production. The construction and use of transportation infrastructure have a crucial effect on climate change, the sustainable development of the economy, and Green Total Factor Productivity (GTFP). Based on the panel data of 30 provinces in China from 2005 to 2017, this study empirically analyses the spatial spillover effect of transportation infrastructure on the GTFP using the Malmquist–Luenberger (ML) index and the dynamic spatial Durbin model. We found that transportation infrastructure has direct and spatial spillover effects on the growth of GTFP; highway density and railway density have significant positive spatial spillover effects, and especially-obvious immediate and lagging spatial spillover effects in the short-term. We also note that the passenger density and freight density of transportation infrastructure account for a relatively small contribution to the regional GTFP. Considering environmental pollution, energy consumption, and the enriching of the traffic infrastructure index system, we used the dynamic spatial Durbin model to study the spatial spillover effects of transportation infrastructure on GTFP.

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