Empirical analysis of the impact of financial development on the income gap between urban and rural residents in the context of large data using fuzzy Kmeans clustering algorithm

Abstract

With the rise of the tertiary industry, the financial industry has achieved unprecedented development, which is mainly reflected in the rapid growth of economic aggregate, the increasingly balanced financial structure system and the increasingly diversified financial products. However, with the rapid development of financial industry, the income of urban and rural residents is increasingly unbalanced. The increasing income gap between urban and rural areas has caused a large number of adverse phenomena in the process of economic development, seriously affecting the income distribution of the people and even causing social instability. Therefore, in today’s big data era, it is necessary to systematically study and analyze the impact of financial industry development on the national income gap between urban and rural areas. At the same time, it is of great significance to improve the problem of excessive income gap between urban and rural areas. This paper mainly analyses the relationship between the three effects of the development of financial industry and the income gap between urban and rural residents. In the empirical aspect, the paper creatively uses the fuzzy Kmeans clustering algorithm to regression analysis the panel data of a certain area from 2010 to 2018. At the same time, in the empirical data analysis, this paper creatively replaces the European norm measure of the Kmeans clustering algorithm with the AE measure, and puts forward a proposal. The index of financial development level is based on the proportion of loans from financial institutions. Through theoretical and empirical analysis, this paper draws the following conclusions: the financial scale in the financial industry will have a huge impact on the income gap between urban and rural areas. Finally, based on the above problems and current situation, this paper puts forward relevant improvement suggestions.