影子银行、房地产市场与宏观经济波动  

Shadow Banking, Real Estate Market and Macroeconomic Fluctuations

作　　者：马亚明[1] 王虹珊 

机构地区：[1]天津财经大学经济学院,天津300222

出　　处：《当代财经》2018年第1期12-23,共12页Contemporary Finance and Economics

基　　金：国家社会科学基金重点项目"新常态下我国影子银行体系的风险溢出效应及其对货币政策的影响研究"(15AJY021)

摘　　要：在金融加速器、价格摩擦和投资成本的基础上,将影子银行和房地产市场纳入动态随机一般均衡模型,并利用贝叶斯方法估计模型的结构参数,同时分析了金融和实体两类冲击对我国影子银行、房地产市场与宏观经济变量的影响。方差分解结果表明,利率冲击是引致我国房价变动和影子银行规模的重要因素,生产率冲击则能解释房地产规模、通货膨胀、投资增长等变量的波动。脉冲响应结果表明,两类冲击都会使得房价和影子银行规模呈现相反的变动趋势。福利分析结果显示,关注房价波动和宏观审慎的货币政策都可以提高社会福利。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 shad- ow 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.

关 键 词：影子银行 房地产 宏观经济变量 

分 类 号：F830.3[经济管理—金融学]