Research On The Influence Of Primary Educational Resources Agglomeration And Housing Prices In Chengdu

The real estate industry is an important part of the national economy.However,in recent years,China’s housing market has experienced soaring housing prices and severe regional housing price differentiation.Therefore,it is very important to study the causes of high regional housing prices.Under the background of the policy of "Nearby Enrollment ",educational resources have become one of the most important factors affecting housing prices.Although a large number of studies have focused on the impact of education on housing prices,these studies only focus on the impact of separate educational resource accessibility on housing prices,and no scholars have paid attention to the fact that educational resource aggregation may have a significantly higher than average impact on housing.Premium,which this research will focus on.The research of this paper is mainly divided into two stages: the first is the data and model preparation stage,the main purpose is to evaluate the aggregation of key primary schools;the second is the core model solution and analysis stage,the main content is the quantitative calculation of the key primary schools in the research area.premium.In the data preparation stage,this paper mainly uses the Python web crawler method to collect detailed data of school and housing information from the Chengdu Education Bureau,the second-hand housing transaction website and the map developer platform.School data includes its latitude,longitude and grade information;for housing information data,based on the review of previous literature,this paper collects 18 variables affecting housing prices in six categories: internal characteristics,life,transportation,entertainment,business center and education and related data.Next,this paper evaluates the aggregation of key primary schools.The standard deviation ellipse method can determine the aggregation direction and aggregation degree of key primary schools,and the DBSCAN algorithm helps the text to determine the aggregation area of two key primary schools.In the second stage of the research,this paper calculates the housing premium generated by key primary schools by establishing and solving a mixed geographically weighted regression model,and conducts a comprehensive analysis with the results of the first stage of research.The study found that in the two agglomeration areas,key primary schools will generate a premium of about 11.2% and 10.4% respectively for housing prices,which is about 50%-60% higher than the premium generated by separate educational resources.The results of this paper quantitatively analyze the significant impact of educational resource agglomeration on housing prices at the micro level,which is mutually confirmed with some theoretical analysis results of previous studies: that is,when the spatial allocation of educational resources itself is not balanced,such as "Multi-school Enrollment" policies that locally enhance the randomness of college admissions,cannot effectively control housing prices.At the application level,the results of this paper may provide a reference for the formulation of government education and housing policies,as well as the investment expansion of real estate developers.