Study On The Influence Factor And Forecasting Of Residential Commodity Price Changes In Wu Han City

In Wuhan, the commercial housing prices has kept increasing in recent years, the range of rise is far beyond the level of overall economic growth and other industry products and services rise. If the housing prices rose too fast, it can not only affect the quality of life of urban residents, but also influence the stability in the development of the economy in entire nation. The issue of housing prices has attracted broad attention as a major economic and social problem.This paper based on the relevant commodity residential housing prices theory, making a study of residential real estate market situation in Wuhan firstly. The analysis believes that the momentum of the supply and demand in the overall housing market in Wuhan (2003-2009) is flourishing. From the comparative view of supply and demand situation, the growth rate of housing demand is higher than the supply, but the housing prices keep rising. If from a static perspective, the domestic purchasing power of Wuhan has decreased gradually in recent years, but from the dynamic perspective, the purchasing power of residents is maintained in a reasonable range. Secondly, the paper take a method of qualitative analysis to study the main factors caused fluctuations of commercial housing price in Wuhan. Based on the analysis, the paper takes a multiple linear regression model to study the quantitative relationship between the housing prices and the influencing factors both from the demand and supply aspect. The regression results showed that in the demand side, per capita disposable income, residential sales area, bank interest rates have a significantly impact on housing prices, which could explain 99% of price changes, while the population has less impact on housing prices; but in the supply side, investment in commercial residential, the amount of fluctuations in the price level has a greater impact on housing prices, which could explain 98% of price changes, while Completed area of residential and GDP had little significant effect on housing prices. Finally, the paper use a gray prediction model to predict housing price value of future stages, and the study shows that: Grey prediction accuracy is better, we can drawn a prediction that the average price of commercial housing in 2010,2011,2012 is separately 5912.4,6408.3,6830.4yuan per square meter.The paper attempts to explore the factors affecting the trend of housing price, and predict the trend of housing price in Wuhan. We hope that research on the Wuhan municipal government can play a certain reference role in effectively regulating the housing market, at the same time we hope the paper can also help consumers to judge the trend of commercial housing price, and provide a theoretical basis for there current or future purchase behaviors.