The Regional Difference In Factors Affecting Real Estate Prices

After the implementation of real estate reform in 1998, China's housing market began to transform into a buyer's market. The real estate industry, as a pillar of the national economy, has never been a lack of attention. People in China are attracted to the real estate prices of some areas, which have been soaring in recent years. The government had implemented various policies and measures for regulating the real estate market in 2010, but with little success. The increasing rate of house prices throughout the year still reached 7.2%. Why are our government and buyers so concerned about the real estate prices, the reasons are obvious.On the one hand, the real estate industry is a major force in the national economy development. According to the National Bureau of Statistics, The real estate transactions are more than 5.3 trillion RMB, accounting for 14% of GDP. The annual real estate investment totaled 4.8256 trillion RMB, accounting for 17.4% of the investment of total assert. Real estate can also pull the development of other industries, such as steel industry, building materials industry, home appliance industry. The other hand, real estate related to the vital interests of the masses. High prices not only greatly increased the burden on ordinary people, but also decreased people's future consumption, which could cause growth inhibition and eventually may become an important factor of social instability.In addition, real estate has also been the focus of academic issues, domestic and foreign scholars have done a lot of theoretical and empirical researches on the real estate market. As the real estate market itself is a complex market, real estate price ups and downs, and the factors affecting the price can be described as complex. There are certain differences, whether in space or time, between each factor. The purpose of this paper is to study the regional difference in factors affecting real estate prices. This paper comprehensively analyzes the factors affecting the house prices, which also innovatively divided the factors into following three categories: economic factors, social factors and other factors. Economic factors mainly include economic indicators that can be quantified, this category include:income level, price level, interest rates, money supply and so on. Social factors include: population, urbanization, social psychological. Other factors include:factors apart from economic factors and social factors, such as physical factors mentioned in this article, location and environment factors.We select VAR model (vector autoregressive model) as a tool to do quantitative research on regional differences in factors affecting real estate prices. In order to facilitate comparison of results, we chose two cities of Shanghai and Chongqing as our sample. After processing the data, we do unit root test, found that all the data become stationary by first differences. In addition, we found the cointegration relationship exists among the five variables:Housing prices index, Land prices index, Disposable income, M2, Real rate. Then we tried to determine the number of model installments by the command of "Lag Lengthcriteria" standards in Eviews 6.0, then we could try to model a VAR model. Then we got the outcome of impulse response function (IRF) and the variance decomposition.This paper concluded that:①To the factor of disposable income, The impact on house prices in Shanghai is much weaker than the impact on Chongqing;②The shock of Shanghai's house prices is much stronger than the shock of Chongqing's house prices caused by Changes in land prices.③To changes in interest rates and money supply, the impact on home prices in Shanghai are stronger than Chongqing, while this part we have also analyzed the reasons for these conclusions, and we made the appropriate economic interpretation. Finally, we tentatively gave the corresponding policy recommendations on the basis of conclusion, that the State's macro control policies should be different from region to region.