The purpose of this study is to estimate different data models on house prices using statistical models and the variables which are controlled by real estate policy.
This study used several statistical techniques, such as Vector auto-regression (VAR), Johansen co-integration and variance decomposition, which aim to assess the significant effect of macroeconomic factors on Chinese house prices.
The results show that land supply and other variables have negative effects on house prices. The results also indicate that financial mortgages for real estate have positive effects on house prices and the area of vacant houses as well as the area of housing sold.
This study only covers three cities in China because of limitations of data for other cities.
This study proposes policy suggestions according to the empirical results obtained.
