Analysis Of Influencing Factors Of Housing Prices In Nanning

In recent years,the development potential of the real estate industry as a pillar industry,like fire cooking oil,to solve the housing problem directly affects the national economy sustained and stable development and social stability and unity,and the core of the housing problem is the housing problems.For the research model has many researchers nationwide real estate forecast,each big city model also like bamboo shoots after a spring rain.Nanning city as the capital of the Guangxi Zhuang Autonomous Region,is the Beibu Gulf Economic Zone in the center of the city,is a comprehensive transportation hub in Southwest China with access to the sea,the real estate industry as an important economy,so the research of prices in Nanning is of practical significance.The characteristics of the regional real estate price fluctuations of the master is the normal operation of the real estate market guarantee.After the basic simple statistics,homogeneity and heterogeneity of the regional real estate price in Nanning city in space.This paper uses spatial statistical analysis methods to study,differences of the price distribution of commercial housing in 2016 6 in Nanning city for a sample of 159 small by using R,OpenGeoDa and other free software,considering the spatial factors of innovation,the hedonic model of this problem is established,namely SLM and SEM model.The spatial econometric model showed that the goodness of fit than the traditional OLS spatial econometric model to Good.According to the estimation results of SLM model,influencing factors on housing prices showed significant positive correlation in the rate of greening,property fees,education facilities,showing the influence factors are significant negative correlation and the volume of the construction area,residential building itself into the main characteristics of visible negative influence,and regional characteristics are mainly positive influence model,overall description of housing characteristics is directly influenced by the factors of spatial variation of housing price.