Study On The Evaluation Of Planting Family Farms’ Credit Risk

Industrial prosperity is the focus of rural revitalization.China is in the crucial period of transformation from traditional agriculture to modern agriculture.Under the background,new agricultural management entities with a higher degree of marketization emerged and became the link that promoted the organic connection between small farmers and modern agriculture.Among the new agricultural management subjects,the development of family farm conforms to modern agriculture and society,and becomes the main force of agricultural modernization development.However,poor availability of credit data on family farms makes it difficult to accurately characterize their credit risk.In order to prevent financial risks,financial institutions have raised the lending threshold.The development of the family farms are facing the difficulty of expensive financing.Domestic and foreign scholars have carried out a lot of research on the financing constraints of family farms.However,different types of family farms are very different in their operation mode and risk resistance ability.The subdivision research on the credit risk of family farms can help financial institutions to accurately identify credit risk.Among them,the number of planting family farms in our country is the largest and the distribution range is the broadest.And the financing constraint facing in its development is related to food security,so it has a high research value.In view of this,this paper takes planting family farm as the research object.And by constructing a model to build a set of planting family farm credit risk evaluation system,so as to judge the credit risk of planting family farm scientifically.In this paper,1990 planting family farms in 30 province(autonomous region,municipality directly under the Central Government)in China are taken as research objects to construct a credit risk assessment model.Firstly,by referring to high-frequency indicators cited by large financial institutions and domestic and foreign literatures,a set of original data of 50 indicators was constructed,which including six criterion layers: solvency,operation status,management level,basic information of farmers,external macro conditions of family farms and credit characteristics.Secondly,the index system of credit risk evaluation is constructed by selecting indexes of planting family farms through random forest model.Thirdly,GA-BP neural network model was used to solve the index weights of planting family farms and obtain credit scores.Fourthly,Ward clustering is used to classify the credit rating of plantation farms.Finally,the non-parametric test is used to find out which characteristic attribute under the same index is the key characteristic affecting the default of planting family farms.Empirical conclusions are as follows:(1)By analyzing the credit data of 1,990 planting family farms in 30 provinces and cities in China,the random forest model is constructed to screen out 11 important indicators that can significantly distinguish the default status of planting family farms.It includes historical loan use,profit rate of total cost,farmer’s employment experience,total cost,agricultural capital input,loan-to-deposit ratio,per capita disposable income of rural residents,total operating land area,total income,ratio of labor cost to total cost and engel coefficient of rural residents.(2)The credit rating of planting family farms is normally distributed.24.87% of planting family farms are at grade A or above,55.83% are at grade B to grade BBB,19.30% are at grade CCC or below.(3)Dig out11 key characteristics affecting plant-based family farms.For example,in the aspect of solvency of planting family farms,the credit risk of planting family farms is the highest when the total income is between [0,500,000] yuan,the profit rate of total cost is between [0,0.25],the total cost is between [0,500,000] yuan,and the agricultural capital input is between [0,200,000] yuan.The above characteristics are the key affecting the credit risk of planted family farms.Based on the above conclusions,this paper puts forward countermeasures and suggestions from three perspectives: Regulators need to promote the establishment of a comprehensive credit data integration platform and improve credit support for farmers;Financial institutions should establish a credit evaluation system suitable for planting family farms and identify the key points of credit risk.Planting family farms should improve their operating ability and organizational management level,actively understand the credit rating,so as to improve their credit investigation level.