Spatial Differentiation Pattern And Impact Factors Of Rental Price In Beijing City

Beijing city is rich in resources and developed in economy,attracting a large number of foreign workers,with a large floating population.Due to rising house prices in recent years,and the government strictly limit the purchase house,a large number of floating population choose renting to solve the accommodation problem.Unlike the real estate market,the government did not develop a clear and defined rent price standards,and neglect of management,resulting in the rent intermediary arbitrary charges,and a serious impact on the healthy development of rental market.According to the first law of geography,the rent is closely related to geographical location.Different regional has different development orientation,Living facilities,transportation,environment and so on are also different,these factors have a different impact on the price of rent,leading to existence of heterogeneity in the rent space.The research on spatial distribution of rent and the influence factors of rent price can help the urban management department to better manage the rent market.Therefore,based on the Beijing rental intermediary platform-chain home online rental data in September 2016,POI data of Amp in this paper,the spatial distribution of rent in Beijing is studied,and factors of rent is quantitatively analyzed.The research work and achievements are as follows:Rental data of the 176 blocks in six districts of Beijing are collected by the crawler technology,the spatial data of districts,and the POI data of Amp,so as to provide the spatial data support for research.First,this paper uses the trend analysis,variation,contour map in statistical theory to analyze the spatial pattern of rent price,The analysis shows that the price of rent in Beijing presents the spatial distribution that the center is high,the east is high and the west is low,the north is high and the south is low.Then,spatial autocorrelation analysis is used to study the relationship between rent and spatial heterogeneity,and hierarchical clustering method is used to research the relationship between rent and local autocorrelation coefficient.The results show that the rent price of 176 blocks in six districts of Beijing has a high correlation,the local autocorrelation shows the characteristics of high correlation between the center and the periphery,and the poor correlation of middle zone.Select fifteen characteristic variables from rental data and POI data,the linear regression coefficient of rent characteristic is obtained by linear form of hedonic price model,then,on the basis of linear model,add the spatial weight to construct the geographically weighted regression model,and get the price model of 176 blocks in six districts of Beijing.Finally,analyze the impact of different factors in different space on rental price.