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Research on the Influencing Factors of Industrial Structure Optimization: A Case Study of Five Counties in Wenzhou Mountainous Area

Zhanhao Zheng

Abstract


This article summarizes and examines existing domestic and international achievements. It analyzes the present industrial structure of five mountainous counties in Wenzhou, based on statistical yearbook data from 2014 to 2021. The study calculates the degree of industrial structure optimization, using the OIS calculation method, and considers the degree of inclusive finance, scientific research expenditure, fiscal expenditure, and transportation level as factors that influence the industrial optimization degree, based on local conditions and literature review. By establishing a panel data regression model, the study concludes that inclusive finance and scientific research expenditure have no significant impact on industrial structure optimization. However, the increase in fiscal expenditure and transportation level can effectively improve the local industrial optimization degree.


Keywords


Inclusive Finance; Industrial Structure; Panel Regression

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References


Jiang BW, Zheng SY. An Empirical Study on the Impact of Fiscal Expenditure on Industrial Structure Transformation. Statistics and Decision Making, 2020, 36(24):133-136.

Ren AH, Liu H. Nonlinear Effects of Fiscal Policy on Industrial Structure Optimization. Financial Science, 2017.6.

Li J, Xu HC. An Empirical Study on the Relationship between Technological Progress and Industrial Structure Adjustment in China. Soft Science, 2011, (4):8-18.

Lin CY, Kong FC. Analysis of Spatial Correlation Effects of China's Industrial Structure High Degree: Based on Social Network Analysis. Economist, 2016(11):45-53.

Zhang QB, Li WD. Empirical Analysis of the Impact of High-Speed Rail on Industrial Structure. Cooperative Economy and Technology, 2019(10):4-7.

Sun Q, Xu ZY. Digital Inclusive Finance, County Endowment, and Industrial Structure Upgrading. Statistics and Decision Making, 2021(18):140-144.




DOI: http://dx.doi.org/10.18686/fm.v8i2.8644

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