天津农学院学报 ›› 2022, Vol. 29 ›› Issue (1): 81-86.doi: 10.19640/j.cnki.jtau.2022.01.017

• 经济管理 • 上一篇    下一篇

农业上市公司的信用风险实证研究——基于因子分析与Logistic模型

任君, 李广通信作者   

  1. 天津农学院 经济管理学院,天津 300392
  • 收稿日期:2020-09-27 出版日期:2022-03-31 发布日期:2022-04-14
  • 通讯作者: 李广(1963—),男,教授,博士,主要从事农产品市场与贸易、农业投资政策、期货与证券市场方面的研究。E-mail:tnliguang@sina.com。
  • 作者简介:任君(1997—),女,硕士在读,主要从事农业经济管理和农业金融研究。E-mail:2440560423@qq.com。
  • 基金资助:
    农业部软科学研究项目(201603-2)

An empirical study on the credit risk of agricultural listed companies——Based on factor analysis and Logistic model

Ren Jun, Li GuangCorresponding Author   

  1. College of Economics and Management, Tianjin Agricultural University, Tianjin 300392, China
  • Received:2020-09-27 Online:2022-03-31 Published:2022-04-14

摘要: 由于农业企业涉农的特性,其风险会受到自然灾害和市场价格波动等多种因素的影响,以间接融资为主,往往也会引起信用风险。本文结合企业信用风险研究情况,确定农业企业的信用风险测度指标,选取45家农业上市公司为研究对象,通过因子分析法消除指标的多重共线性,并用向后去除、逐步向后选择方法建立Logistic模型,度量企业的违约概率,进而分析农业类企业的信用风险情况,为从事农业生产的企业、商业银行等提供参考。

关键词: 农业上市公司, 信用风险, 因子分析, Logistic模型

Abstract: Due to the special characteristics of agricultural enterprises, their risks will be affected by various factors such as natural disasters and market price fluctuations. At the same time, they always use indirect financing, which will cause credit risks. Based on the research of credit risk of enterprises, this paper is designed to determine the credit risk measurement indicators of agricultural enterprises. In order to achieve this, we select 45 listed agricultural enterprises as the research objects and then eliminate the multicollinearity of indicators through factor analysis, and establishes Logistic model by using backward removal and stepwise backward selection methods. The model is used to measure the default probability of enterprises, and then analyze the credit risk of agricultural enterprises, and provide references for enterprises and commercial banks engaged in agricultural production.

Key words: agricultural listed companies, credit risk, factor analysis, Logistic model

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