An Empirical Analysis Of Corrugated Effect And Influencing Factors Of Urban Residents' Residential Price

Along with the advancement of the aim to build a well-off society in an all-round way in our country, gradually speed up the urbanization process, urban residential demand and investment demand rigid synchronous development, makes the city real estate industry is booming. In nearly a decade, part of the urban housing price growth too fast, showing the development of city real estate market is not healthy.How to effectively regulate the real estate market supply and demand balance, to promote the healthy development of the urban real estate market in China, the need to change of the real estate market development and changes in different regions of the effect and influence factors for further research, put forward the corresponding suggestion.Firstly, domestic and foreign research literature on the spatial effect and influence factors of urban residential price fluctuations were reviewed, significance is further elaborated on the basis of the review. Secondly, the price of urban residential four-quadrant model is described, detailing the interaction between economics of real estate between the capital market and the property market, pointing out that in the long term market conditions will always reach a balanced state, which for analysis factors urban residential prices provide a basis. Then, the necessary condition for spatial "ripple effect" of the existence of that heterogeneity and dependence were discussed, as on regional urban residential prices, "ripple effect" to prepare the ground.The first part is the empirical analysis of urban residential price "ripple effect" of the empirical analysis, the second part of the urban residential price factors were analyzed.Empirical Analysis "ripple effect" of China’s urban residents in housing prices, by making trend of China’s urban residential zoning to describe the status of the price fluctuations, fluctuations in the state of mutual regional and price range that may exist from trend analysis. Then interaction possible test of spatial dependence test using Moran’s I index confirmed the existence of spatial correlation between the various regions. 31 provinces and cities of the residential price unit root test, smooth sequence Granger causality test, on the same order single whole sequence selected provinces and cities have representative cointegration test and error correction model. Both methods are explained urban residential price interaction between the various provinces and states. It confirmed the existence of "ripple effect" and Fluctuation most economically developed provinces affected is relatively backward economically more provinces.Factors influencing urban residential price analysis, by the factors influencing the price of urban residential classification elaborate, change each influencing factors affecting urban residential prices brought about by analysis. Then select a representative factors from these factors as explanatory variables for urban residential price modeling, confirmed the presence of space between the urban residential prices. The eventual establishment of spatial error model, confirming the impact of space factors on regional urban housing prices is very significant; taxes, the impact of urban residents per capita disposable income and population natural growth rate of the region’s urban housing prices are also very significant.From the empirical results of view, China’s urban residential price policy control required subregions to accelerate the construction of transportation infrastructure between the cities, narrow city distance, to establish a market-based competition, government guidance, supplemented by local real estate policy.