The Study Of Impact Of Educational Facilities On Housing Price

With the evolution of urbanization,demands for housing is growing,which promotes the rise in housing prices to a certain extent.Therefore,the housing price factors become a hot issue in recent years.There are a number of factors affecting housing price due to the complexity of the estate market,including geographical location,public transport,the surrounding environment.With the improvement of the quality of life residents' life in recent years,consumers increasingly pay attention to the education facilities surrounding the residence.Our country implements the education policy that they divided all the schools into parts and children should go to the school which near their house.Many parents choose to purchase house belong to school-chip of key school in order to allow their children to enjoy a good education,which contributing that education has become an important factor affecting housing price.There are some achievements about impact of housing price,which have some issues.Small sample and incomplete variables were used in the previous study.Also,space effect was not considered.The paper is to expand the number of sample,set more reasonable variables of education and to eliminate spatial effect.Hedonic Price Model is constructed.And the general regression model and spatial econometric model are used to analyze data,supporting education in the residential market capitalization situation.The main contents of this paper are as follows:(1)With carding the literature about housing price,a relatively perfect Hedonic Price Model is established,which includes1 nine educational variables,five regional variables,four neighborhood variables,four architectural variables.(2)The classical regression model is used to get the semi-elasticity coefficient of educational variables.The educational variables have different influence on housing price and the descending order is primary school quality,junior high school quality,close to the university and kindergarten number.(3)A spatial econometric model is established to prove the spatial correlation between the housing prices of the six districts in Tianjin.A more accurate capitalization rate of house price is obtained after the elimination of spatial effects.(4)According to the research findings,it provides appropriate recommendations forthe education sector,consumers and estate developers.