Agglomeration effects in Europe

Ciccone, Antonio

doi:10.1016/s0014-2921(00)00099-4

Cited by 752 publications

(536 citation statements)

References 3 publications

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“…The market price of the regional industrial value added represents regional advancement in the industrial share (K) Chow (1993Chow ( , 2010, which is further determined by the regional market size (MSz) measured through the regional gross domestic product, intraregional trade costs (IntraTC) as the cost borne for the transportation of passenger and freight volume, interregional trade costs (InterTC) as the flow of foreign direct investment and comparative advantage (CAd) as the average ratio of productivity per unit of labor in each region, (Ciccone 2002;Zhang and Zhang 2003;McCann and Shefer 2003). Each variable is averaged for the annual outcome of each region, which helps us to check all the regions in a single platform and find the regional comparative advantage over others:…”

Section: Resultsmentioning

confidence: 99%

Impact of market access and comparative advantage on regional distribution of manufacturing sector

Imran

Hu-sen

2017

China Financ. and Econ. Rev.

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Background: This paper discuss the effects of trade costs and comparative technology on industry location for the economy of China. Methods: The model assumes differences in comparative technology and different intraregional and interregional trade costs, and argues how different factors influence the location of industrial value added. Results: By processing the designed model, equations were set up to check whether the conclusions from our mathematical model are credible under panel data at the provincial level of China from 1995 to 2014. We found that the location of industrial value added in a region strongly related to infrastructure and local market size.

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Section: Resultsmentioning

confidence: 99%

Impact of market access and comparative advantage on regional distribution of manufacturing sector

Imran

Hu-sen

2017

China Financ. and Econ. Rev.

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“…The increasingly frequent inter-enterprise exchange and technical cooperation promotes knowledge spillover. Ciccone (2002) points out that the cross-industry knowledge spillover effect is often the main stimulant of major innovations [15]. This explains why the technological innovation efficiency of this stage increases significantly.…”

Section: Results Of the Panel Threshold Regressionmentioning

confidence: 99%

Diversified Agglomeration, Specialized Agglomeration, and Emission Reduction Effect—A Nonlinear Test Based on Chinese City Data

2018

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Industrialization and urbanization has rapidly advanced in China. Therefore, clarifying the relationship between industrial agglomeration and environmental pollution resolves questions if intensive or dispersed development should be adopted for the future Chinese industry or not. By distinguishing between specialized and diversified agglomeration, this paper adopts the threshold regression method to investigate the differentiated influence of industrial agglomeration stages on pollution emission reduction. This was based on panel data from 2003 to 2016 on 285 prefecture-level cities in China. The result indicates that moderate degrees of industrial agglomeration and suitable agglomeration modes are conducive for the reduction of pollution emission. From a perspective of environmental protection, the development of diversified agglomeration is superior to that of specialized agglomeration. Specifically, a "U-shaped" relationship was found between specialized agglomeration and environmental pollution, suggesting that the former first mitigated and then worsened environmental pollution. This staged evolution of diversified agglomeration exerts a more-complex influence on environmental pollution. The following policy implications have been proposed: The currently implemented industrial growth pole strategy in China should fully utilize the "self-purification" effect of agglomeration to achieve energy conservation and emission reduction. Furthermore, differentiated agglomeration policies should be formulated in response to various growth poles according to different stages of industrial agglomeration. In addition, efforts should be made towards creating an interactive early warning mechanism for the spatial distribution of both economic activities and pollution.

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“…The evidence is not conclusive with respect to size (Rosenthal and Strange, 2004) although it does seem to be so in relative terms. Ciccone and Hall (1996), Ciccone (2002) and Fingleton (2003) find a positive effect of the density of employment on productivity.…”

Section: An Application To the Ebro Valleymentioning

confidence: 89%

Detecting Dependence Between Spatial Processes

Herrera¹,

Ruiz²,

Mur³

2013

Spatial Economic Analysis

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Testing the assumption of independence between variables is a crucial aspect of spatial data analysis. However, the literature is limited and somewhat confusing. To our knowledge, we can mention only the bivariate generalization of Moran's statistic.This test suffers from several restrictions: it is applicable only to pairs of variables, a weighting matrix and the assumption of linearity are needed; the null hypothesis of the test is not totally clear. Given these limitations, we develop a new non-parametric test, Υ (m), based on symbolic dynamics with better properties. We show that the Υ (m) test can be extended to a multivariate framework, it is robust to departures from linearity, it does not need a weighting matrix and can be adapted to different specifications of the null. The test is consistent, computationally simple and with good size and power, as shown by a Monte Carlo experiment. An application to the case of the productivity of the manufacturing sector in the Ebro Valley illustrates our approach.

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Agglomeration effects in Europe

Cited by 752 publications

References 3 publications

Impact of market access and comparative advantage on regional distribution of manufacturing sector

Impact of market access and comparative advantage on regional distribution of manufacturing sector

Diversified Agglomeration, Specialized Agglomeration, and Emission Reduction Effect—A Nonlinear Test Based on Chinese City Data

Detecting Dependence Between Spatial Processes

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