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Issue title: Special Section: Intelligent Algorithms for Complex Information Services - Recent Advances and Future Trends
Guest editors: Andino Maseleno, Xiaohui Yuan and Valentina E. Balas
Article type: Research Article
Authors: Liu, Rana; b | Liu, Pingfenga; * | Zhang, Wanga | Metawee, Ahmed K.c
Affiliations: [a] School of Economics, Wuhan University of Technology, Wuhan, China | [b] Hubei Technology Exchange, Wuhan, China | [c] Accounting Department, Faculty of Commerce, Mansoura University, Dakahliya, Egypt
Correspondence: [*] Corresponding author. Pingfeng Liu, School of Economics, Wuhan University of Technology, Wuhan, China. E-mail: lpf@whut.edu.cn.
Abstract: The objective of this study is to promote the structural optimization of the banking industry and improve the national economic level. The analysis method based on the co-integration test is adopted to study the relationship between market structure optimization and economic growth in the banking industry. Firstly, the current economic growth condition, development trend, and the development of the banking industry are analyzed. Secondly, the model between the bank market institutions and the economy is constructed, and the data source of the model is analyzed. Thirdly, the stationarity test, co-integration test, and regression analysis of the studied data are carried out based on the co-integration test. The results show that there is a significant negative correlation between the concentration of banks and the overall economy, and there is a significant negative correlation between the market structure of banks and the downgrading growth of various industries. Also, the variables of social material input level and human capital input have a significant positive correlation with the economy. It is hoped that the results of this study can provide a good guiding significance for China’s economic development.
Keywords: Banking market, economic growth, stationary analysis, co-integration test, regression analysis
DOI: 10.3233/JIFS-189008
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5233-5242, 2020
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