| Real estate price’s fluctuation is related closely to people’s life and it affects thehealthy development of national economy and social harmony. The development ofChina’s real estate shows obvious spatial heterogeneity in different cities as a result ofdifferent spatial location, different economic foundation, different market expectationsas well as different regional and city features. Along with the ending of the rise of allthe urban real estate prices and the gradual appearance of market differentiated trendsin different cities, it is discussed again about the spatial difference and influencingfactors of the real estate prices in China’s city. What causes the differences of realestate price among different cities? How do the city’s characteristics affect thefluctuation of the real estate price? Does real estate price bubble exist and what arethe differences of the real estate price bubble in different cities? All these questionsshould be studied further since the China’s real estate market has the emerging andtransforming. The development of information technology and the progress of thetransportation network unite cities and the real estate price’s formation process isbecoming more and more complex. It brings new challenges to identify the real estateprice’s mechanism and reveal the spatial differences of fluctuation of the real estateprice and implement differentiated regulation policy. It is necessary to explore theinfluential factors of the urban real estate prices and fluctuation patterm from thetheoretical and empirical perspective.After summarizing the related theory and existing research results systematically,the paper builds model to research nonlinear characteristics and spatial difference ofthe fundamentals’ impact on the real estate prices based on the theory of supply anddemand. It studies the nonlinear characteristic of the urban public service supply andurban value from two aspects of investment and output effect respectively based onhedonic price theory. At last it builds a dynamic panel data model to reveal the spatialdifference law of urban real estate prices’ fluctuations. The main contributions andconclusions of the paper are as follows: Firstly, it puts forward an analysis framework of the urban real estate price’sformation mechanism including three dimensions—economic fundamentals, cities’input and cities’ value and establishes the model of spatial difference to identify thelaw of real estate price’s fluctuations.This paper follows the system of "from question to theory modeling, and thenfrom the empirical analysis to the conclusion". It builds model from three dimensionsrespectively，the economic fundamentals, the urban public service investment and theurban quality characteristics on the basis of the supply and demand theory and thehedonic price theory. Further, it uses nonlinear and spatial econometric method tostudy the influencing mechanism of real estate prices. After that it builds a model tocalculate the fluctuation rules of35large and medium cities’ real estate price bubblesin China and reveals the nonlinear characteristics and spatial differences.Secondly, it builds a basic theoretical model of real estate price influenced bybasic economic factors. Then it analyzes the urban real estate price formationmechanism with the help of the panel data quantile regression and the mixedgeographically weighted regesstion.Based on the theory of supply and demand, it builds real estate prices’mechanism model to study the impact of income, interest rates and other factors. Andwith the help of the panel data quantile regression and mixed geographically weightedregression, it investigates the main economic fundamentals in the process of priceformation. The results show that the fundamental factors that affect real estate pricessignificantly in a nonlinear and spatial way. From the point of the level of price, thehigher prices of cities, the greater influence of income on prices is. The impact ofpopulation density and construction cost on housing prices are considerablysignificant when real estate prices are lower. While with the rising real estate price,their effects become less significant. From the point of regional spatial distribution,the income has greater influence on the real estate prices in southeast coastaldeveloped cities, while in north cities; especially in northeast cities the cost hasgreater influence on the real estate prices. The economic development has moreinfluence on the real estate prices in western cities. Thirdly, on the basis of founding a model of the urban residents’ utilitymaximization, it studies the nonlinear influence of the urban public service on the realestate prices with the help of the panel threshold regression model.It constucts the model of urban residents’ utility maximization, introduces themethod of the panel data threshold regression, and studies the impact of the urbanpublic service supply on the real estate price, based on the Tiebout theory model. Theresults show that there is an obvious nonlinear relationship between the levels ofpublic service, the impact on real estate price also increases gradually. The imbalanceof urban public resource allocation is a main reason for the polatization of urban realestate and the obvious spatial difference. The real estate tax policy and fiscal transferpolicy related to the level of public service should be explored so as to regulate thereal estate market.Fourthly, the paper puts forward an index system of city value containing fivecharacters of being suitable for living, for business, for employment, for schoolingand for tourism. Then it studies the nonlinear relationship of the city value and thereal estate prices with the help of a panel quantile regression model.Based on the Lancaster consumption theory and the Rosen invisible markettheory, the paper constructs a real estate price theory model. The city quality can bedivided into five aspects including being suitable for living, for business, foremployment, for schooling and for tourism. On this basis, it builds the index systemof the city quality by selecting40indicators. After that it calculates the value index ofcity by using the maximum entropy weight method. Then, with the help of quantileregression for panel data, it examines the nonlinear relation between the quality ofcity and real estate price. The results show that the impact on real estate price of thefive aspects on the real estate price is different. The impact declines in the followingorder: being suitable for employment, for living, for tourism, for business and forschooling. For those cities with low real estate price, the aspect of being suitable forliving and for tourism are obvious, while the aspect of being suitable for employmentis more significant in high real estate price cities. The aspect of being suitable forschooling is significant in all kinds of cities. Fifthly, the paper builds a real estate price model containing expectation. Byapplying this model it calculates the real estate price’s fluctuation in35large andmedium cities through the iterative regression method and examines the spatialconduction effect of the urban real estate price’s fluctuation.It constructs a dynamic panel data model containing real estate price affectingfactor and the expectation factor. Then the iterative regression method is applied tocalculate the real estate equilibrium price. It calculates the degree of the urban realestate price bubble annually by comparing the actual price with the equilibrium pricedecided by economic fundamentals. Finally it tests the real estate prices’ conductingeffect between cities by constructing the corresponding statistic. Through theempirical study of the35large and medium cities in China, the results show that theurban real estate price bubbles are various among different cities. However, thebubble is not related to the level of the real estate price. At the same time, it showsthat the expectation promotes the formation of the real estate price bubble and theconstructing effect of the price fluctuation among different cities can relieve the realestate price bubble.In conclusion, this paper discusses the nonlinear formation mechanism andfluctuation pattern of real estate price by applying spatial and nonlinear calculatingmethod, based on the two theoretical systems of the supply and demand theory andthe hedonic price theory. The achievements of the paper make up for somedeficiencies in the research of influencing factors and fluctuation of real estate prices,and to some extent, enriches the theoretical system of urban real estate prices research.At the same time, it has practical guiding significance for the regulation and control inthe implementation of regional differentiation of government policy.
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