Spatial Differentiation And Influencing Factors Of Housing Prices In Chengdu

With the rapid development of China's economy,the regional differences in urban resources and public infrastructure have increased during the process of urbanization,and the phenomenon of increasing gaps in the price of residential houses within cities has become increasingly apparent.Housing prices affect the trend of the housing industry and the housing market,and also reflect the complex social and economic relationships.Therefore,housing prices have become the focus of national attention.The factors affecting housing prices are complex.It is the product of the combination of macroscopic factors(social,economic,policy,etc.)and microscopic factors(building,location,neighborhood,etc.).In order to reveal the spatial differentiation of residential prices in Chengdu and its influencing factors,this paper takes 11 districts in the center of Chengdu as the research area.With the technical support of ArcGIS,BIGEMAP,SPSS,and GWR software,select the average transaction price of 5,854 residential communities in Chengdu in 2018 and related 18907 POI data,from the perspective of micro-factors,make a comprehensive analysis and diagnosis of residential prices,analyze their spatial distribution characteristics,build HPM and GWR models,combining model results,and compare the regression coefficient with The administrative areas are superimposed,and the degree of influence of various influencing factors on housing prices is visualized.The following conclusions are obtained:(1)There is a significant concentration of housing price space in Chengdu,with the housing price center moving southward and differentiation in all directions.The analysis of housing price trends shows that housing prices in all directions have an inverted U-shaped distribution,and housing prices have the characteristics of "high in the middle and low in the surroundings".The surface analysis of housing prices shows that the overall housing prices in Chengdu present an irregular ring structure and a fan-shaped structure of "low north and high south".The housing price has a gradient increase characteristic from north to south.In the center of the peak,the residential prices in the "Financial City" and "Huayang-Wan'an-Xinglong" areas in the peak area are higher than 40,000 yuan/?.Analysis of the housing price profile shows that Chengdu`s housing prices are significantly different in all directions.The east,northwest,and north directions have smaller changes in the profile;the south,southwest,and southeast have the largest changes,the peak of the southward profile line is above 40,000 yuan/?;the starting point and ending point of the westward and northeastward section lines are farther and more undulating,and the peaks are sharper than the section lines in other directions.(2)The significance of each influencing factor of housing prices in Chengdu varies,and there are also significant differences in positive and negative correlations.HPM research shows that the volume rate has no significant effect on residential prices;the age of housing,the distance to subway station,and the CBD distance have a negative correlation with housing prices,and the negative impact of CBD distance reaches the most significant-0.314;property management fees,the greening rate,the number of bus stops,distance to malls and shopping centers,distance to banking and finance,distance to school education,distance to general hospitals,distance to government institutions,distance to scenic spots have a positive correlation with housing prices.The positive impact of the greening rate is the most significant,reaching 0.781.(3)The influence of various influencing factors on residential housing prices in Chengdu is not simple and linear,but there are complex spatial differences.The combined effects of various factors affect the housing prices in residential communities.The standard deviation of the GWR model is as follows: CBD distance> Number of bus stations>Greening rate>Metro station distance>Scenic distances> Property management fees>Shopping mall distance>Government institutions distance>General hospital distance>School education distance>Bank financial distance>Volume rate> Housing age,and the standard deviation of the CBD distance is 0.607460,which is the largest of the 13 influencing factors,which indicates that the distance difference between the residential area and the CBD is the largest.(4)Based on the analysis of the spatial differentiation of housing prices in Chengdu and its influencing factors,a scientific and objective recognition of the law of housing price differentiation in Chengdu,and exploring the impact of various influencing factors on housing prices,can enable relevant government departments Understand and master the law of housing price differentiation,implement scientific management and control," Different strategies in different cities " in different directions,promote the transformation of old cities and urban planning and construction,and promote the steady development of the real estate market.