Abstract: Based on the financial accelerator, price friction and investment costs, this article brings the shadow banking and the real estate market into the dynamic stochastic general equilibrium model, uses the Bayesian method to estimate the structural parameters of the model, and at the same time, analyzes the impact of financial and physical shocks on China’s shadow banking, real estate market and macroeconomic variables. The results of the variance decomposition show that the interest rate shock is an important factor leading to the changes of China’s housing prices and the sizes of shadow banks; while the productivity shocks can explain the fluctuations of such variables as real estate size, inflation, and investment growth. The impulse response results show that both types of the shocks will make housing price and shadow banking scale presenting an opposite trend. The results of the welfare analysis show that the monetary policies which keep a watchful eye on house price volatility and macro-prudence can improve social welfare.

Key words: shadow banking; real estate; macroeconomic variables