| According to statistics of some countries, when the output value of real estate industries is increased by 1%, the output value of related industries can increase 1.5-2%. In China, the raising up of 1 million Yuan in residential investments will increase 147,900,000 Yuan's investment in other 23 related industries increase correspondingly. The real estate, being the foundation and leading part of national economy, and to which it is highly correlated, it plays an important role in Macroeconomics.However, many studies show that fluctuation of housing price in the contemporary is an important factor that causes macroeconomic fluctuations. According to Kindleberger (2000), when housing price is fluctuated, the global economic and financial crisis breaks out easily. For example, because of Japanese real estate bubble in the 90s, Japan suffered the most prolonged economic downturn which lasts 15 years. In addition, Asian financial crisis in 1997 and subprime mortgage crisis in 2007 not only affects the national macro-economic, but also impact on the local and world economy too. It is because the real estate not only has the consumption function, but also has the investment function. Excessive speculation in the real estate will result in bubble, and impact on the overall macroeconomic. Hence, the real estate market should be healthy and stable.Chinese housing price has grown up rapidly since the real estate reformed in 1998. What factors affect housing price? How do they affect? Both questions are widely concerned by the society.The paper analyzed the housing supply market and the demand market, and then obtained the main factors which affected housing price. Qualitative and quantitative analysis was used. Firstly, the paper analyzed how the real estate policies have impacted on commercial housing supply and demand since 1998 by qualitatively analysis. Secondly, the paper analyzed the factors affecting commercial housing price by quantitative analysis. The paper used Engle-Granger method to obtain the cointegration in the factors which affected the commercial housing price. Then the paper used the impulse response function and variance decomposition analysis of VAR model to acquire the dynamic relationship among those factors. Finally, the paper gives the conclusion of the research and some policy suggestions to stabilize commercial housing prices. The conclusion is that the expectation which the public think commercial housing price will still rise is strongly correlated with commercial housing price and the price of land is also correlated with the commercial housing price. |
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