房地产泡沫检验的Switching AR模型

为检验理性泡沫，在放宽Norden的switching regression模型假设的基础上，提出了更为有效的switching autoregressive（AR）模型，并给出模型参数的估计方法以及泡沫检验方法. 运用2001年初到2011年末我国直辖市的房价数据构建该模型，实证分析表明：该模型比switching regression更有效；北京和上海的房价泡沫显著，天津和重庆的房价泡沫不明显；泡沫处于生 存状态的概率走势图表明，政府出台的房地产调控政策将北京的房价泡沫 挤出，但上海的泡沫未受影响. 此外，提出的switching AR模型也可用于检验其他资产价格中的regime switching泡沫.

Switching AR model for housing bubbles test

For detecting rational bubbles, via relaxing the coefficient constraints of switching regression model, the paper proposes a more efficient model, autoregressive (AR) switching model, and gives the estimation method. An application to seasonally Chinese housing price data in the first decade of 21 century shows the model is more efficient than switching regression model, and provides evidence of bubbles in Beijing and Shanghai, but no evidence of bubbles in Tianjin and Chongqing. Further more, the probabilities of being in survival state show that the real estate-related policies of Chinese government have ruled out bubbles in Beijing, but not in Shanghai. The proposed model can also be used to detect rational bubbles with regime switching structures in other assets.