Measurement Of Farmers Formal Financing Credit Risk

Since2004, the CPC Central Committee has published the document on the issues ofagriculture, rural. It shows the party and the state determination of solving the agriculture,rural and farmer questions. Financing volume of investing in rural financial markets is low.farmers carry out agricultural industrialization, modernization with insufficient funds, whichrestrict rural development, agricultural development and farmers’ income increase. Thisoutstanding issue resolving relies mainly on the financial support of rural finance. However,the rural financial market is facing more problems: the farm credit system has not beenestablished, farmers have more information in the credit business, which leads farmers ofmoral hazard and adverse selection. When financial institutions operate farm credit, it facesgreater credit risk and high rate of bad loans. Financial institutions do not want to enter therural financial markets, which cause low supply on the rural financial market. Therefore, theidentification and management of farmers credit risk is of great significance. But now China’sfinancial institutions on farmers’ credit risk measurement and evaluation is still in the stage ofqualitative analysis of classical credit, which mainly rely on the experience of loan officers.Financial institutions are lack of effective credit risk control measures for farmers credit risk.In response to these problems, the formal financing credit risk of the farmers as the researchobject explore suitable model to measure the credit risk of the Farmers in China to reduce therisk of default of farmers and stimulate the financial institutions into the rural market.This article first by reviewing the development process of the credit risk measurementmodel, you can choose the type of model to measure farmers formal financing credit risk.Secondly, by the cause of the farmers formal financing credit risk measurement analysis,farmers have strong and diversified financing needs. But financial institutions are lack ofeffective means of controlling farmers’ credit risk, causing that supply for farmers creditbusiness is low, which is unable to meet the funding needs of the farmers growing. Thirdly,the credit risk of is different from ordinary loan. The article specifically analyzes the uniquenature of the farmers formal financing, which leads to the high credit risk. The article pointsout that the most feasible measurement of China’s farmers credit risk is the multi-statisticalanalysis methods. Then, on the basis of field research data, this article empirically analyzesfarmers formal financing credit risk: this article designs three types25indicators of affecting farmers credit risk,which are family demographic characteristics, household wealth andborrowing factor. These indicators were entered into the discriminant analysis model andlogistic regression analysis model, the following conclusions: discriminant analysis model ismore likely to choose the stepwise discriminant analysis model. According to the contributionof identifying farmers credit risk,18variables totally enter the model, which are the size of thetotal amount of arrears, land quality, the loan interest rate, the total agricultural expenditureover the past12months, arable land, migrant workers number, the number of agriculturallabor, the value of the assets, family size, whether it is a group guarantee, the number of morethan65years old, whether it is the members of credit unions,deposit ratio, over the past12months total consumption expenditure, the number of children under the age of12, the headof household education level, the evaluation of credit, migrant income over the past12months. The accuracy of judging credit risk of the farmers formal financing is88.5%. Logisticregression analysis model tend to choose to use the backward stepwise logistic regressionanalysis. The rate, the model recognizes farmers formal financing credit risk, is84.3%.Through the empirical analysis, stepwise discriminant analysis model on the the accuracy offarmers credit risk identification and evaluation is higher than the logistic regression analysismodel. Stepwise discriminant analysis model become an effective means of financialinstitutions in controlling household credit risk. Finally, in order to alleviate the contradictionbetween supply and demand in the rural financial market, and promote stepwise discriminantanalysis model as an effective means of controlling the farmers formal financing credit risk,this article will give the appropriate policy recommendations.