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Academic Journal of Humanities & Social Sciences, 2020, 3(3); doi: 10.25236/AJHSS.2020.030306.

Research on regional economic vitality based on ordered logistic regression model

Author(s)

Hong Guo, Xinyue Zhang

Corresponding Author:
Hong Guo
Affiliation(s)

Institute of Economics Hebei University, Baoding City Heibei Province 071000

Abstract

On the road to becoming an economic power, we must pay more attention to the regional and regional individualized development. We should actively promote regional coordinated development, stimulate regional economic vitality and optimize the spatial distribution of modern economy. In recent years, a series of major decisions on the coordinated development of western China, the revitalization of northeast China, the rise of central China and the first development of eastern China have continued. With the implementation, China's road of regional coordinated development has become wider and wider. There is a need to develop a model to quantitative analysis the factors and measures of regional economic activity. Firstly, we design a model to measure the regional economic vitality, and sets up a comprehensive index system of the first and the second level, using Topsis comprehensive evaluation method to analyze and evaluate ten provinces (cities) in the eastern region from different dimensions. Then, an ordered logistic regression model is established. We have taken into account the impact of demographic and entrepreneurial dynamism trends on regional economic dynamism. A total of 6 indicators are selected for model testing and analysis at the population and enterprise levels. The conclusion is that the higher the score, the greater the regional economic vitality. Finally, we have conducted a comprehensive test of the models involved in this article to achieve a better measure of regional economic activity.

Keywords

Regional economic vitality, Logistic regression model, Index system, Measure activity

Cite This Paper

Hong Guo, Xinyue Zhang. Research on regional economic vitality based on ordered logistic regression model. Academic Journal of Humanities & Social Sciences (2020) Vol. 3, Issue 3: 41-51. https://doi.org/10.25236/AJHSS.2020.030306.

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