China's Bank Credit Home Prices Mechanism Study

Housing is the key to the economy and human live, it not only affects the survival of the people, but also the social stability. If the housing prices are too high, rising too fast, on the one hand, it will affect the sustained and healthy development of the real estate industry, and also promote the formation of the real estate bubble, on the other hand, it will increase the difficulty of residents to buy houses, so that the quality of human living will be influenced. In order to slow down the rise of the housing prices in some cities, our governments have two macroeconomic controls in April and September in 2010, which have the some core as credit regulation of banks, and which shows the importance of bank credit on macro-control of real estate.The theoretical part of this paper is mainly on building models to analyze the inherent mechanism between bank credit and house prices. Firstly, the paper builds a housing consumption period model to analyze the role of bank credit in achieving the maximum utility, the result is: whether the bank credit will maximize the effectiveness of the realization of housing consumption, the key is the consumers preference between credit interest and ahead of schedule to achieve the target; then construct two housing price models:the one is based on future disposable income, the other is based on demand-supply relation, which are used for the next chapter of the empirical analysis. In addition, the theoretical part of this study also found that "over-confident" and "herd mentality" will be through bank credit to promote the rise in housing prices, and also build a theoretical Analysis model for the quantitative analysis between "excessive self-confidence variable" and "housing credit variables"The empirical study of this paper is divided into two parts, the first part is the static analysis based on the two pricing model, after empirical analysis we know:housing prices rise 0.741% corresponding to every 1% of increasing of the future disposable income; housing prices rise 0.5% in corresponding of bank credit for increasing 1%. The second part of the VAR model is based on the dynamic empirical analysis, the methods used include cointegration test, Granger causality test, VAR models and so on. The empirical results show that:bank credit volatility and price fluctuations are in reciprocal causation, and there is a long-term stable relationship between them. China's banking credit affect the house prices significantly, but the house prices is not significantly affect the bank credit; the increase of the housing prices will hinder the prices in the coming period, we can see it as the residents expects of the decline in house prices, while the growth of bank credit will support housing prices continue to rise.