Analysis And Forecast Of Main Influencing Factors Of Housing Price In Xi'an

As the national economy develops rapidly, the real estate, as a rising-sun industry, expandsand grows stronger unceasingly, and it becomes the important force of national economicdevelopment. In recent years the housing price in our country has risen quite quickly andprices in some cities have soared constantly, which have affected people's environment andquality of life enormously, so the society pays more attention to the price and the country andthe local authorities have released all kinds of regulative policies to prevent the housing pricefrom going up excessively. Therefore, in order to help formulate some reasonable effectiveregulative policies for the government and make the real estate market maintain a sustainedand sound development, the author should analyze main factors that affect housing pricethoroughly and grasp the tendency of real estate price and then forecast it reasonably.Based on the literature consult and analysis, the author firstly introduces the concept of thereal estate and its price, constitution, classification and characteristics, and analyzes thesupply and demand of real estate and its price in theory, then makes an analysis of majorfactors that influences the price from six aspects, including own factor, environmental factor,population factor and so on. After that, this paper analyzes the characteristics of real estatemarket in Xi'an thoroughly, studies the major factors of housing demand in Xi'an based onfour aspects, that is residents'income level, the urban population and so on, researches themajor factors of housing supply in Xi'an according to the land cost and building cost, andanalyzes the major factors of housing supply and demand in Xi'an from the monetary policyand national economy. Finally, according to the steps of gray forecast model, builds the GM(1, 1) forecasting model with residual error amendment based on the twelve quarters' sellingaverage price during the time of 2007~2009 in Xi'an, and then uses four methods to check themodel data to confirm its precision and feasibility, and forecasts the housing price of the coming six quarters in Xi'an.