Investigation And Analysis Of Liaoning Province Farmers Credit Constraints

Agriculture is the country’s basic industries, the development of modern agriculture requires the support of a lot of money, and rural finance is the core of the rural economy, rural finance question therefore become a key issue in the development of modern agriculture. On the one hand, modern intensive agriculture, industry, market and other characteristics, as compared with conventional farmers dispersed, large-scale grain production and operation of more suitable for the development of modern agriculture, they are more willing to accept and adopt new varieties and new technology to make all kinds of advanced production factors play a more effective role. On the other hand, although China in recent years, the rural financial issues constant attention, but also put forward a new concept of agriculture business entities, but funding is still very scarce, particularly large grain, the lack of funding affected its agricultural production and management of the healthy development of rural financial markets also have an impact. Therefore, the credit constraints of large grain-depth analysis is necessary.Taking large grain Liaoning Province as the research object, on the basis of domestic and foreign credit constraints related research, firstly, through questionnaires to collect data through descriptive statistical analysis of the basic characteristics of the sample households will be summarized, followed by, through a gradual questioning of credit constraints to identify the sample households and households by credit constraints are classified into credit supply-side constraints and demand-side credit constraints categories, and finally, through cross-analysis of the sample households and credit constraints The factors were compared.The results showed that 60％ of the sample households by credit constraints. By cross-analysis, we draw the following conclusions:the probability of credit constraints by men is less than women; with age, the probability of credit constraints by the U-shaped distribution; sample households with a higher level of education by the probability of credit constraints decreases; probability participated in training in agricultural technology by farmers is less than the credit constraints did not participate in training in agricultural technology households; family support than the high probability of households being higher than the low credit constraints farmers family support; the number of household assets being inversely proportional to the probability of credit constraints; annual income of farmers, the more by the small probability of credit constraints; the probability of unexpected expenses of families were credit constrained than would otherwise unforeseen expenditure of households; participate in cooperatives farmers receive credit constraints did not participate in the probability is less than cooperative farmers; the probability of social relations farmers receive no less than the credit constraints of social relations farmers.Finally, for the supply-side and demand-side credit constraints both credit constraints, combined with large grain put forward relevant policy recommendations.