Author(s)

Huangwei Li ¹, Jie Ye ^2,3, Chen Qiu ¹, Ketao Lin ⁴

Affiliation(s)

¹ Anxi College of Tea Science, Fujian Agriculture and Forestry University, Quanzhou, 362400, China
² Business College, Quanzhou Normal University, Quanzhou, 362000, China
³ The Private Economic Development Research Institute of Characteristic New Think Tank for Universities, Quanzhou, 362000, China
⁴ Laboratory of Regional Analysis and Simulation of Resources and Environmental Sciences, Quanzhou Normal University, Quanzhou, 362000, China

Corresponding Author

Ketao Lin

ABSTRACT

The construction of the intensity of China's inter-provincial economic ties is of great significance to the spatial carrier of China's inter-provincial modern industrialization system. We uses entropy method, modified gravity model and grey correlation model to measure inter-provincial economic linkage intensity in 2019 and its influencing factors. The research shows that: (1) The strength of China's inter-provincial economic connection network is different, and the economic connection is not balanced. It is mainly concentrated in Beijing-Tianjin-Hebei region and Jiangsu-Zhejiang-Shanghai region. There is a certain coincidence between the economic connection network and the total economic connection intensity in space, and the economic development of each province is closely related to the connection between provinces. (2) The relationship between the China's inter-provincial economic linkage intensity and the gray correlation degree of each subsystem is infrastructure > social development > economic development > ecological environment protection > population and labor development. Among them, 6 subsystems have a correlation degree of 0.79 or more for the strength of interprovincial economic linkage, and the strongest correlation is 0.823 for infrastructure.

KEYWORDS

Hainan, modified gravity model, economic linkages intensity, social network analysis

CITE THIS PAPER

Huangwei Li, Jie Ye, Chen Qiu, Ketao Lin, Analysis of the Strength of China's Inter-Provincial Economic Linkage Intensity and Its Influencing Factors. Financial Engineering and Risk Management (2023) Vol. 6: 34-42. DOI: http://dx.doi.org/10.23977/ferm.2023.060804.

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