Research On The Change Of Commodity Residential Buildings Price In Xi'an

The prices of commodity residential houses is the core for operating the housing market, the change of price not only affect the health of the residential market, but also related to the vital interests of the wider housing consumers directly. With the continuous advance of China's socio-economic development, the prices of housing in major cities continuously keep improving, especially in the period which increasing intensity policies for regulate and control commodity residential market, the research projects is more necessary and important than before. The papers on the following three main areas:First, on the basis of in-depth study domestic and abroad residential pricing model and the impact of house prices, we use the existing system of commercial housing prices theory and the characteristics and history about Xi'an, analysis the various domestic factors of commodity residential buildings price from the various participants in the housing market commodity perspective theoretically. In the process local government policy factor is extracted as an important factor of the change in the prices of commodity prices for residential houses.Then on the basis of the residential economic theory we introduce the econometric analysis and principal components to analyze the driving force of domestic commodity price changes in Xi'an. The conclusion: the drivers of changes on commodity residential buildings price in Xi'an can be summed up as the strong demand in the residential houses market, the increasing costs of residential construction, the local government's pursuit of their own interests and the country's financial factors of macro-control policies four factors.Finally, we do the trend research on the price of housing in Xi'an changes. This study investigated the traditional linear regression model and grey linear regression model forecast of housing price changes in Xi'an. Through the empirical analysis of the prices of commodity prices for residential houses in Xi'an, we not only predict the trend of changes, but also gave a detailed analysis on two models in the use of the premise, the prediction accuracy and the representation of two model, which concluded: grey linear regression model is more accuracy than linear regression model in the short term residential price prediction, and in a relatively longer period of time the accuracy of grey linear regression model is lower than linear regression model.In this paper, we hope the suggestions about commodity residential houses in Xi'an or in China will be useful to the management and decision-making.