Research On The Regional Differences Of Residential Real Estate Market Prices In China

The real estate industry has been playing an increasingly important role in the national economy and became an important pillar industry of national economy in China. The healthy development of the real estate industry has an important impact on economic operation in China. And the real estate price is an important indicator of whether the real estate market develops stable. Study on the changes of real estate prices what is of great significance to promote the whole national economic development and to strength the healthy development of real estate industry.The real estate began the comprehensive market-oriented since 1998, and the real estate market continues to develop and mature. The real estate prices are rising rapidly which leads to regional differences, such as Beijing, Shanghai and other biggest cities has rose to 20,000yuan per square meter, and Shenzhen has broken through 20,000 yuan per square meter, but the other smaller cities such as Luoyang, Yulin and so on are still 4,000yuan per square meter. There are significant differences in regional real estate prices. High housing prices have begun to affect people’s normal life, and if regional differences in real estate prices can’t be inhibited reasonably, then it will reflect people’s quality of life, and excessive gap would most likely affect the fair and stable of the whole society. Therefore, further study of the change about the real estate price and its regional difference is to promote the real estate market and guarantee regional imbalances is crucial for the healthy and orderly development of the real estate market in China.Firstly, from the point of theory analysis to study the reasons of regional differences based on the hedonic price model, which is considered that the regional differences in housing prices are mainly derived from the differences in the characteristics of housing. Combined with the development status of the real estate market to research regional differences of housing price with the exploration of spatial statistical analysis and spatial correlation test, and analysis results show that because of the real estate is location of fixed and not mobility, use for a long time, value and characteristics, the real estate prices exists significant regional difference and spatial correlation in China.Secondly, this paper used the panel data model to analyze the factors of affecting the real estate prices with the real estate related data, resulting regional differences according to the reality of the real estate market in China. It carefully judges and recognizes the influencing factors of the regional difference in real estate markets which are per capita disposable income, unemployment rate, GDP, residential real estate sales area, population natural growth and residential real estate investment. There are six indicators selected from five aspects which are income level, economic development, land supply, demographic factors and credit factors.Again, space and time double fixed spatial Durbin model was constructed based on the basic theory of spatial econometric. The estimated results show that changes in house prices have a significant positive spillover effect on the neighboring cities, unemployment and population natural growth rate of room changes have no significant effect. But spatial spillover effect decomposition shows, the natural population growth rate of the direct effect, indirect effect and total effect are positive, but the direct effect is not significant. The direct effect of unemployment is positive and indirect effect is negative, the total effect is negative, but not significant. Spatial dependence analysis shows that there are significant regional differences in price changes and the differences mainly due to the spillover effects of the explanatory variables.Finally, this paper selects the cross section data of 2014 to analyze the spatial heterogeneity of housing price by constructing a Geographically Weighted Regression model in order to facilitate the analysis. The explore regression results show that the unemployment rate, GDP and population natural growth rate can illustrate the spatial heterogeneity better. The estimated results showed that: compared to the OLS model, the GWR Model is better.There are significant regional differences of the real estate price which are caused by different regions of the unemployment rate, GDP and the natural population growth rate in China. This provides a certain basis to local government when they adjust measures to local conditions of the real estate market regulation and control policies.