摘要
常见的房地产市场价格泡沫估计模型普遍存在参数估计有偏的缺陷,为了更有效地估计房价泡沫,可以将动态最优模型与状态空间滤波方法相结合,通过构建一个动态最优局部均衡模型来刻画不存在投机因素的房地产市场基础供求关系,同时在把基本房价视作状态变量的基础上给出决定基本房价的状态空间模型,从而计算出房价泡沫。以北京市为例,使用2005年1季度至2009年4季度的相关数据,利用卡尔曼滤波方法对状态空间模型进行的测算显示,北京商品房市场的价格泡沫出现于2006年4季度,且近三年来的平均泡沫程度达到26.5%。
The popular methods for studying real estate price bubble share similar defects in parameter estimation. To estimate the real estate bubble more effectively and accurately, the dynamic optimization method must be combined with the state-space model. The paper f＇Lrstly establishes a partial dynamic equilib- rium model to describe the relationship between basic supply and basic demand in the real estate market. Then based on results of the dynamic model, the state-space model determines the state variable and basic housing price, is provided. Finally the model is estimated by running Kalman f＇dter with data from Beijing market between 2005Q1 and 2009Q4. Results show the bubble of Beijing real estate market appeared in 2006Q4 and the average level is 26.5% in the past three years.
出处
《财贸研究》
CSSCI
2011年第1期59-65,共7页
Finance and Trade Research
关键词
房地产
泡沫
最优控制
卡尔曼滤波
real estate
bubble
optimal control
Kalman filter
