基于逐步判别分析方法的农户正规融资信用风险度量研究  

Measurement of farmers formal financing credit risk based on stepwise discriminat analysis

作　　者：马永杰[1] 孔荣[1] 

机构地区：[1]西北农林科技大学经济管理学院,陕西杨凌712100

出　　处：《广东农业科学》2011年第20期218-220,共3页Guangdong Agricultural Sciences

基　　金：国家自然科学基金(70873096);教育部人文社科规划项目(07JA790027)

摘　　要：在综合评价信用风险度量模型后,认为多元统计分析方法更适于我国现阶段农户信用风险的测度,同时在山东省满庄和宁阳96位农户数据的基础上,运用逐步判别分析法对农户正规融资信用风险进行了实证分析。结果表明,判别函数总体上区分样本的准确率高达82.3%,正规金融机构可应用该方法对农户融资的信用风险进行度量;负债情况、借款用途、贷款年利率3个因素与农户贷款违约成正向影响关系;家庭规模、户主教育程度、资产价值3个因素与农户贷款违约成负向影响关系。Based on comprehensive evaluation of credit risk metric model, farmer credit risk measurement was most likely to use multivariate statistical analysis at the present stage in China. This paper used the database of Ningyang and Manzhuang 96 farmers sampling survey in Shandong province, and stepwise discriminat analysis method was introduced into the farmer credit risk measurement in this article. The result showed that overall accuracy rate of discriminant function was up to 82.3%.The model could be applied to the farmer formal financing credit risk measurement. At the same time, the default factors of farmers loan, which was borrowed from the formal financial institutions was also analyzed. The liabilities, borrowing purpose and loan interest rate had positive effect on Chinese farmer default. The family size, education level of household and asset value had negative influence on Chinese farmer default.

关 键 词：农户 正规融资 信用风险度量 逐步判别分析 

分 类 号：F323.9[经济管理—产业经济]