Study On Commodity Residential House Price Volatility Of The Guanzhong Urban Agglomeration Using Spatial Econometric Analysis

In recent years, due to the rapid development of real estate industry in our country, the commodity housing market has experienced a few times considerable volatility process. To be exact, for some typical cities, real estate price changes may have systemic effect on the operation of other urban housing markets in the area and make a profound impact on the national economic development and social stability.Based on the theory of the balance of supply and demand of housing prices, this paper built the spatial econometric theory of equilibrium price model and chose panel data of Xi ’an, XianYang, BaoJi, 他 ongChuan, and WeiNan as representatives of five major cities house prices in Guanzhong urban agglomeration from 1998 to 2013. Empirical analysis further revealed and explored the main influence factors of the urban commodity house prices volatility. The main conclusions are as follows:(1) This research reviewed and summarized some related literatures about commodity house prices at home and abroad and introduced the related theory of the spatial econometric and method model. The main influence factors of commodity residential house prices volatility attribute to the supply and demand level. The influence factors of commodity housing price volatility are preliminary selected.(2) Commodity residential house prices from five major cities are selected as the research sample, and the global spatial autocorrelation index Moran’s I is used to test the space effect of sample city housing price in space level. The result shows that the Moran’s I index is 0.2107 and there is an obvious spatial dependence in five samples as well as space geography is one of the important factors to influence the price of commodity residential house.(3) Based on the analysis, this article established a reasonable spatial lag model of equilibrium price. By using a stepwise regression method on model parameters, the main factors that influence the housing price are determined. Regression result shows that the main factors including urban population, residents’ disposable income, land acquisition costs, and sales area affect the commodity residential house price volatility. Among them, the land price is a supply factor while urban disposable income, the urban population and the sales area are demand factors. Besides, spatial and regional factors are important to affect commodity residential house price volatility in a given area.(4) This paper used Granger causality test on influence factors of commodity housing price between cities. The result describes that Xi ’an and BaoJi exists a two-way Granger causality whereas the Granger causality of TongChuan does not exist any direction. In addition, XianYang and WeiNan exists a one-way Granger causality. Therefore, Xi ’an the commodity residential house price volatility can cause price changes in these cities. It also provides a reasonable explanation that Xi ’an commodity residential house prices take a leadership position in the city circle.