中国农业科学院农业信息研究所 中国农学会
Agricultural Information Institute of CAAS China Association of Agricultural Science Societies
En
Ch
中国农业科学院农业信息研究所 中国农学会 主办

AI检索

订阅

返回顶部
当前位置: 首页 > 文章 > 农户分化视角下农地经营权抵押贷款信用风险因素识别与评估——基于四川成都的调研数据 四川农业大学学报 2020 (3) 365-372
Position: Home > Articles > Identification and Evaluation of Credit Risk Factors of Agricultural Land Management Right Mortgage Loan from the Perspective of Farmers' Differentiation——Based on the Survey Data of Chengdu，Sichuan Journal of Sichuan Agricultural University 2020 (3) 365-372

农户分化视角下农地经营权抵押贷款信用风险因素识别与评估——基于四川成都的调研数据

作  者：
宋坤;张馨予
单  位：
关键词：
农户分化;政府主导型;农地经营权抵押贷款;信用风险评估;Logistic-SVM模型
摘  要：
【目的】研究政府主导型农地经营权抵押贷款信用风险问题,为金融机构进一步推广该类贷款提供借鉴。【方法】以四川成都实地调研数据为样本,通过Logistic模型探讨影响政府主导型农地经营权抵押贷款信用风险的主要因素,在采用CRITIC法界定信用风险区间后利用支持向量机进行评估。【结果】家庭总资产、家庭年净收入、经营主体类型、流入农地面积、作物估值、作物价格波动、抵押物类型以及有无担保对信用风险具有显著影响;采用Logistic-SVM模型评估的结果表明仅有2.74%的贷款处于高风险状态,且新型农业经营主体的信用风险小于传统小农户。【结论】鉴于异质性农户的信用风险具有显著差异,政府主导型农地经营权抵押贷款应大力服务于种养大户、家庭农场、专业合作社和龙头企业等新型农业经营主体;金融机构应加强与商业性担保机构的合作,健全传统小农户的征信体系;同时应完善相关配套服务措施。
译  名：
Identification and Evaluation of Credit Risk Factors of Agricultural Land Management Right Mortgage Loan from the Perspective of Farmers' Differentiation——Based on the Survey Data of Chengdu，Sichuan
作  者：
SONG Kun;ZHANG Xinyu;College of Economics, Sichuan Agricultural University;
关键词：
farmer differentiation;;government-led;;farmland management rights mortgage;;credit risk assessment;;Logistic-SVM model
摘  要：
【Objective】To study the credit risk of government-led agricultural land management rights mortgage loans,and provide reference for financial institutions to further promote such loans.【Method】Based on the field survey data of Chengdu,Sichuan,the main factors affecting the credit risk of government-led agricultural land management mortgage loans were discussed through Logistic model. The CRITIC method was used to define the credit risk interval and after that the support vector machine was used to evaluate.【Result】Factors including household total assets,household annual net income,type of business entity,inflowing agricultural land area,crop valuation,crop price fluctuation,collateral type and whether there is guarantee have significant impact on credit risk;using Logistic-SVM model for early warning and the results show that only 2.74% of loans are at high risk,and the credit risk of new agricultural operators is smaller than that of traditional small farmers.【Conclusion】In view of the significant difference in credit risk of heterogeneous farmers,government-led agricultural land management rights mortgage loans should mainly serve the new agricultural business entities such as large-scale breeding/planting farmers,family farms,professional cooperatives and leading enterprises;Financial institutions should strengthen cooperation with commercial guarantee institutions and improve the credit system of traditional small farmers. At the same time,relevant supporting service measures should be improved.

相似文章

导出引用
计量
文章访问数: 13
HTML全文浏览量: 0
PDF下载量: 0

所属期刊

推荐期刊

友情链接Friendly link
农业信息研究所Agricultural information institute 农业智能知识服务平台Agricultural intelligent knowledge service platform 农业学术服务平台Agricultural Knowledge Service System 中国知网CNKI 维普网VIP 万方WANFANG DATA
联系我们Contact us

电话Tell：010-82109652-808

邮箱E-mail：agrijournal@caas.cn

服务Service
关于我们About us 意见建议Opinions and suggest
版权说明Copyright
单位：中国农业科学院农业信息研究所 中国农学会 © 2017中国农业科学院农业信息研究所 ICP备案号：京ICP备09089781号-46