A Random Matrix Model of Regional Economic Disparity Based on Spatial Panel Data Analysis

This paper adopts a random matrix approach to model spatial panel data and applies the model to the analysis of regional economic disparity. A panel data clustering method based on variable influence and response structural relationship clustering is proposed to define the structural relationship distance, cluster the panel data from the structural relationship so that the data within the class have the same structural relationship, and give the specific algorithm for determining the classification number in the clustering process based on the structural relationship. The methods of clustering panel data with the presence of linear, nonlinear, and functional relationships are considered separately to aggregate and classify the panel data in terms of the structural relationships of parameters. Using the classification modeling approach proposed in this paper, the empirical analysis is better than the estimation effect in the case of no classification; the empirical test data also show that there is a strong cross-sectional correlation between the economic and financial development data of different regions, and the estimation effect of the model with the correlation treatment is better than the estimation effect of the model without the correlation treatment. The study finds that there is a significant imbalance between financial and economic development, the phenomenon of financial exclusion is serious, and the dynamic influence relationship between financial and economic development in relatively less developed regions is different from that between financial development and economic development in relatively developed regions. In addition to the influencing factors, we should improve the efficiency of investment utilization, give better play to the geographical advantages, keep the industrial structure rationalized, develop the special economy according to the local conditions, and give full play to the spatial effect as well as improve the economic development.