Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning
Joint Authors
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-07-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Agricultural enterprises play a significant role in China’s economic development.
However, compared with other enterprises, agricultural enterprises are facing serious financial problems.
Financing difficulty is essentially a question of financing efficiency.
Based on the DEA method, this paper evaluates the financing efficiency of 39 agricultural listed companies in China from 2013 to 2017.
The results suggest that the financing efficiency is generally low, and the Total Factor Productivity of agricultural enterprises’ financing has a tendency to decrease first and then increase.
The influencing factors of financing efficiency are analyzed using the Tobit regression model and the random forest regression model.
And we find the following: (1) The random forest regression model significantly outperformed the Tobit regression model, with determination coefficients (R2) greater than 0.9 in full sample sets.
(2) Total liability, financial expenses, return on total assets, and inventory turnover rate are important factors affecting financing efficiency of agricultural listed companies.
(3) Return on total assets and inventory turnover rate promote the financing efficiency, while total liability and financial expenses reduce financing efficiency.
Finally, the paper makes some suggestions for the financing of agricultural enterprises.
American Psychological Association (APA)
Liu, Lixia& Zhan, Xueli. 2019. Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning. Complexity،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1133158
Modern Language Association (MLA)
Liu, Lixia& Zhan, Xueli. Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning. Complexity No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1133158
American Medical Association (AMA)
Liu, Lixia& Zhan, Xueli. Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning. Complexity. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1133158
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133158