Based On The Analysis Of The Wealth Distribution And Evolution Of Complex Networks

As a basic economic problem, the gap between poor and rich is an outstanding social problem. It has a complicated and multiple effects. Reasonable and effective income distribution should be impartiality, fairness and rationality. To a certain extent, the system of income distribution is decided by the social structure of which the social economic relationship is the main content. The economic activities of everyone or organization are all dominated by their own economic relationship network which has complexity, wholeness, hierarchy, dynamic and other important characteristics. So, it is very necessary and realistic to realize the unequal distribution of income and wealth by the way of the structure of social economic relationship. Especially the developing of complex network, economists come to realize that the real economic systems always have a large and complex network formation which is neglected by previous studies. But trading models are always proposed to be closed and conservation systems. So, under the banner of complex network, it is particularly important to compare, study and comprehensive summary the impacts of anisotropic wealth distribution through the economic relationship structure. The main contents in this paper can be summarized as follows:1. The influences of different social economic relationship structure on wealth distribution are discussed.The amount of agent’s wealth is closed linked to the structural properties of social economic relationship structure which is especially the property of dynamic growing. Based on this point, we analyze the impact on the wealth distribution by the economic relationship structure with dynamic increasing character. First, under the same trading mechanism, the forms of wealth distribution are given under the different social economic relationship structures which are depicted by the classic complex network models. By methods of simulation and numerical example, it is obtained that the wealth distribution of richer in BA scale network follows Pareto distribution which is different to the others’. So. the wealth distribution in BA scale network is consistent with that of real society. Then, a wealth evolving network model is built based on the phenomenon of links dynamic change, which is considered a series of economic activity in the actual economic activity, such as keeping or removing existing cooperation and developing new cooperation and so on. The degree distribution and the balance of wealth distribution which is influenced by different parameters are analysis obtained by the way of simulation.2. Two types of wealth dynamic evolution network models are constructed.There are many factors that can lead to the unequal wealth distribution. In addition to the structure characters of social economic relationship, there are still many economical pheromones such as information asymmetry and the liquidity of wealth and so on. We adopt appropriated network model to describe the social economic relationship, and improve the preferred probability. So, two kinds of model are given in this part. The first kind of model is known as IALN. The concept of local is used to descript the information asymmetry during the trading process. When the new node is added to the network, it will select cooperated agent from the scale which it is familiar with nodes because of their limited and asymmetric knowledge. As the same reason, the transaction value which is different is preestablished. This also can reflect the character of asymmetric knowledge. By simulation, figures of the relationship between structural parameters with wealth distribution and gini coefficient are given. Through analysis, we obtained that the impact on the wealth distribution by the node degree is very big. basically in a linear relationship. The second kind of model is called RDN. An evolving network model is induced by the mechanism of wealth redistribution which is introduced by the liquidity of wealth. An influenced coefficient which is in order to achieve the purpose of adjusting the network structure is defined. By applying the theoretical deduction, the time-varying equation of the total wealth, the degree and cumulated wealth are obtained. Then, by the method of simulation, the wealth distribution, the gini coefficient and the relationship figures between node degree and cumulated wealth are given based on the different values of parameters. Finally, application background analysis in actual society is discussed.3. An evolving network model induced by the wealth is proposed, which is considered the earning and income distribution.Profit is one of the main targets of individuals and organizations in economic activities. It is also one of most beneficial motivation of human social relationship. It is always a factor that can not be ignored during economic activities. Firstly, an evolving wealth network model is constructed which not only considered the local preferred link and local wealth redistribution but also earning and income distribution. Secondly, Using rate equations, the dynamic equations of degree and wealth distributions are obtained. Finally, we analyze the model from the two aspects of structure and wealth. The results indicate that the node degree follows the power law distribution; however the wealth distribution fits double power law distribution. It is obtained that the wealth model is a negative network, in which the nodes with small degree display relatively greater clustering. By analyzing the wealth distribution and wealth entropy, we investigate the social wealth distribution is unbalanced. The wealth heterogeneity between agents is still different.4. An industrial clusters cooperation network model is build based on the heterogeneity of clusters.The interaction models between agents can be extended to models which interact between agent and organization or between different organizations. Firstly, an industrial clusters cooperation network model based on the heterogeneity is given. Meanwhile, the basic properties of social network are generalized to definition of clusters. Secondly, we quantitatively defined the difference degree between clusters by the parameters of cluster structure. The degree of clusters heterogeneity can be analyzed by Cobb-Douglas production function. The result manifests that the cost between different clusters is inversely proportional to the account of shared resource. Finally, the structure characteristic values of network can be verified by the computer simulation. By analysis, we obtain that the cluster network model is a heterogeneous network which the centrality and the clustering are very low. It is consent with the weak ties theory in the theory of social resources which is proposed by Lin Nan.