| Since the reform and opening-up in 1978,a large number of people have migrated from countrysides into cities,making the original welfare housing system in cities failed to provide enough housing.Therefore,real estate markets gradually formed in multiple regions to satisfy the increasing demand of urban housing.In 1998,the abolition of the policy on unit housing division system forced people to start to rely on the real estate market to solve their housing completely,which is an important milestone.Since then,the overall transaction volume and transaction price of residential housing have increased significantly,accompanied with the increasingly spatial heterogeneity of housing prices between and within regions.Then what are the factors that determine the spatial layout of housing prices in cities?What is the dynamic process of current housing price distribution,and how will the extent of housing price heterogeneity develop in the future?Education quality is one of the most important factors that influence housing price,on the contrary,the value of education quality can be presented by housing price.Therefore,can housing price be ulitilized as a tool to testify if the currently promoted "zero school choice" policies will bring about real education equity.As extremely unique commodities,how to quantitatively measure the overall fluctuation of housing price in a flexible spatial range in the fluctuation cycle?How effective are the housing purchase restriction policies promulgated by central and local government on regulating the housing price?As the basis of the real estate industry on valuation in the economy,the solution of these questions is crucial for people to understand the causes and future trends of housing prices from both micro and macro aspects,proving theoretical and practical foundation for effective macro regulation policy.The housing price of Tianjin has experienced serious fluctuation from 2015-2017,marco-regulation policies were frequently promulgated before and within this period.Under this context,41908 second-hand housing transaction data of six urban districts in Tianjin from October 2014 to May 2018 were obtained through web crawling technology in R language.Determinants of housing price were explored from the static prespective,and from the dynamic perspective,determinants of the formation process of housing price spatial distribution were explored,and education factor was studied as a special case.These studies will provide practical evidence for urban resource planning and education policy making.Morever,general housing price index construction method is provided to quantify the fluctuation trend and magnitude of housing price.By comprehensively applying a variety of models to mine the transaction data of second-hand housing price in Tianjin,main conclusions are obtained as follows.(1)Public goods in Tianjin have been capitalized into the housing price,and purchasers in different locations have different preferences for different types of resources,leading to significant spatial differences of housing structural characteristics,community characteristics and neighborhood characteristics on the housing price.The quality of educational resources has a significant effect on the housing price,and there is a significant interaction between different educational resources.City key primary schools,high-quality public junior high schools and private junior high schools reinforce each other’s impact on housing price.(2)Leading index of housing price is built up to quantify the status of housing in the fluctuation cycle.I concluded that most factors which have a positive influence on housing prices also have essential positive influence on this index.Hence,the unequal distribution of public goods not only resulted in the existence of spatial difference of housing prices,but also will further aggravate the extent of residential price differentiation.(3)As an important factor of housing price,the beneficial boundary of educational resources quality is clearer compared with other public goods because of the long-term implementation of the "nearby enrollment" policy.Meanwhile,the alteration of recruitment policy from elementary to secondary school in Tianjin in 2015 provided a natural experiment for testing the effect of policy change on capitalization.The implementation of "multiple school district" for secondary school policy has capitalized the quality of secondary school district into housing price,besides,the extent of capitalization on primary school education quality is enhanced.Therefore any policies on "strictly school choice" only enhance the cost of "choosing school by buying houses",real education fairness will not be brought about.(4)The traditional construction of Hedonic housing price index based on OLS model doesn’t include the geographical location coordinates in the model,which could cause the spatial correlation between the observed individuals,leading errors in the estimated parameters in the model and the constructed Hedonic housing price index.On the other hand,the problem mentioned above could also be treated as insufficient adjust "the quality of location",which may underestimate housing price index especially on the condition when housing price rises rapidly.Thus,spatial econometric models(SEM and SLM)and generalized additive model(GAM)are applied to analyze the second-hand housing transaction data of six urban districts of Tianjin with geographic coordinates.I concluded that,SEM,SLM and GAM all have advantage in fitting and predicting than ordinary OLS model.SEM nd GAM have better goodness of fit and better ability to remove spatial autocorrelation in the residuals than the SLM.The application of SEM,SLM and GAM on building up the corresponding Hedonic price indexes can improve the precision of traditional Hedonic price index based on OLS.Traditional Hedonic price index based on OLS model is effective in valuing housing price fluctuation when the price is relatively stable,while may underestimate housing price in the period when housing price rises fast for not being able to adjust houses’geographic location quality.(5)The Hedonic index is compared with the mean index,the median index,the index based on the OLS model adjusted for housing size only,and the "70 Second-hand Housing Sales Price Index in 70 Large and Medium-sized Cities(70 index)announced by the National Bureau of Statistics.We found that the method with less quality adjustment ability underestimates more housing price index.And if "70 index" construction method is applied to the same spatial range of this paper(that is,the six urban districts of Tianjin),the "70 index"of six urban districts is only slightly lower than the Hedonic index.So "70 index" has the ability to control the quality of houses sold in different periods,and the reason for the phenomenon that "70 index" is different from people’s institution is mostly caused by sampling.(6)This article obtained the consistent trend of housing price fluctuation from two perspectives:one is relative risk of "selling no higher price" of transaction date,and the other is the construction of housing price.Compared with the date of macro policies promulgated in Tianjin,the cancelling of housing purchase restriction did not promote housing price immediately,while in May 2015,with announcement of reduction of down payment and raise of loan limit by Tianjin Center for Housing Fund Management,housing price starts to rise.However,after the promulgation of the second purchase restriction policies in September 2016 and March 2017,the growth rate of housing price did slow down,while the housing price did not decline. |
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