| Comprehensive and in-depth understanding of the rural credit system is the basis ofscience rural financial reform. The academic world has done a lot of research in sociology,economics, etc. but more effective methods and ideas on how intuitive and Systematicunderstanding of the complexity of the rural credit system is still lacking. As an effectivecomplex systems research method, the complex network theory has been widely used inscience and technology, economic, social science and other aspects. It provides a new solutionto this problem.This article uses the complex network theory to study rural credit system. First of all,from the fundamental factors affecting the rural credit system, the article analyzes thecharacteristics of the network nodes and edges and gets the basic configuration of the network;Secondly, Use “R†software on the rural credit system modeling analysis and get the basicphysics statistical indicators of the net; At last, by supposing the farmers status changed andtheirs risks arose in the system, the paper gets different result of different change and finds thecharacters of the network stability.The main conclusions of the article:（1）Through econometric analysis, this article finds the two core factors which canaffect the occurrence of the credit relationship is economic capital (income) and social capital.Moreover, the social capital plays a more important role in this progress.（2）By introducing two concepts about the loss of social capital and the efforts utility,the paper uses game theory to analyze the link generation mechanism of the credit networkand find it is easier to establish links in the civilian credit system.（3）Under the two basic assumptions which is the economic capital and social capital,The article starting from the private lending network and informal lending channel to analysethe credit network model. And by using the R software, the article successfully establish thebasic model of the farmer credit network based on farmers linkage mechanism analysis.（4）By statistical physics analysis on farmer credit network model, this paper finds thenetwork has a small-world and scale-free characteristics and some other structural characteristics. Furthermore, by analyzing the coverage of low-income groups in the network,article maintains that private lending network can effectively promote the financing oflow-income farmers.（5）By assuming the node change such as economic growth of farmers and theOrganization of farmers, this paper finds this two factors change will all improve farmerslending network. And if we distinguish between different types of network organization, wecan find the random network organization is more effective. In addition, targeted to developsocial networks has a positive effect on the lending network improvement.（6）The article assumes that the network of farmer credit has “point risk†and “planeriskâ€. If the network suffered plane risks, farmers have differentiated threshold is conducive tosystematic risk identification and preparation. If the network suffered point risks, theconsequences may be very different，The network is robust against random attacks and ifsuffers degree nodes selective attack it will be vulnerable.The innovations of this paper are reflected in the following three points:（1）This paper using complex network theory to research the rural credit system andthrough the analysis of influence element of the system to complete system network topologymodeling, This article found that the formation mechanism of rural credit network and a seriesof network characteristics and its economic and social implications.（2）In the progress of econometrics and game theory analysis on the basic elements ofthe networks, the article introduces some new variables in consideration and perfects thepredecessors in the aspects of these analyses.（3）Based on credit network model, from the policy improve effectiveness and systemrisk spread two aspects have carried on the analysis, found the system characteristics of therural credit system under different assumptions. |
