Population economic function model based on data mining algorithm

Abstract

Population structure changes interact with economic development, moderate population and reasonable population structure are important guarantees for sustainable social and economic development. The research ignores the specific impact of the change of population age structure on economic growth, and proposes and establishes a population economic function model based on data mining algorithm. Based on the changes of population structure in Liaoning Province in the past 20 years, Grey correlation analysis method is selected. The analysis shows that there is a close relationship between population structure and economic growth. Based on this research, the econometric method is used to construct a multiple linear regression model to further analyze the specific impact of population structure changes on economic growth. The analysis results show that the total population of urban areas, the total number of employed people in the primary industry, the number of middle school students per 10,000 people, and the total number of employed people in the tertiary industry are the four most significant demographic indicators for the per capita GDP of the study area. There is a significant positive correlation between the total number of employed people in the tertiary industry and per capita GDP and there is a significant negative correlation between the total number of employed people in the primary industry and the number of middle school students per capita and per capita GDP. The impact of other indicators on per capita GDP is not significant. According to the conclusion, countermeasures and suggestions to ease population structure change and promote the coordinated development of population and economy in the study area are put forward.