Size and Characteristic of Housing Bubbles in China's Major cities:1999-2010

There is some disagreement in the published literature regarding the definition and the measurement of housing bubbles in China. Extending the analytical framework of Black et al. （2006）, the present paper measures the housing bubbles of China＇s 35 major cities from the second quarter of 1999 to the second quarter of 2010. The results indicate that the housing bubbles in China＇s 35 major cities were relatively small in the sample interval, but the bubbles in eastern metropolises, such as Beijing, Shanghai, Shenzhen, Hangzhou and Ningbo, have been relatively big since 2005. The changing tendency of housing bubbles in most cities highly corresponds with the changes in real estate policies. This paper decomposes the housing bubbles of the 35 cities, and finds a great proportion of irrational bubbles rather than rational intrinsic bubbles generated by price speculation. Based on empirical analysis, this paper proposes policy recommendations for preventing the generation and expansion of housing bubbles.

Spatial-Temporal Changes of Housing Bubbles in China＇s Major Cities： 1999 to 2012

Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. （2006） to a spatial panel VAR structure, this paper measures housing bubbles in China＇s 35 major cities from 1999Q2 to 2012Q3 and analyzes the spatial-temporal changes of the housing bubbles in these cities. Results indicate that 1） changes to housing bubbles in most cities highly correspond with changes in the main real estate policies of the country and 2） housing bubbles in eastern developed cities such as Beijing, Shanghai, Shenzhen, Hangzhou, and Ningbo, have been relatively large in recent years although the average housing bubble is not very serious over the 35 major cities. Through the Kernel Density Function and local indicators of spatial autocorrelation analysis, this paper finds that housing bubbles are concentrated in several eastern developed cities. Based on empirical analysis, this paper proposes policy recommendations on inhibiting the expansion and diffusion of housing bubbles.

The Spatial Statistics Analysis of Housing Market Bubbles

With the incorporation of spatial statistic method, this paper constructs a state-space model of housing market bubbles, discussing the spatial pattern of housing market bubbles in China,and identifying the dynamic evolution process. The results show that: The bubbles of housing market walked along a path from low level to high level and then downsized to a low level during the period of 2009 and 2014, and the highest level stayed at 2011. From overall, the level of housing market bubbles had shown significant spatial autocorrelation and spatial agglomeration. In detail, the direction of North-South in China showed the inverted U shape, i.e., Central region was with high bubbles, and two ends contained low bubbles; from East-West direction, the East had high bubbles and the West contained comparatively low bubbles. Local spatial test indicates that there were some approximate spatial features in housing market bubbles among the adjacent regions. Observed from the level of housing market bubbles, China contained 3 plates: The first was the plate with low bubble level,including 3 provinces in North-East China(provinces of Jilin, Heilongjiang and Liaoning were included,but Dalian in Liaoning province was excluded; the second was the Central and West plate(the provinces of Yunnan, Guizhou, Sichuan, Guangdong, Guangxi, Hunan, Hubei, Gansu, Fujian, Jiangxi and Hainan were included in this plate), which was also featured with low bubble; and the third was Central East plate(provinces or provincial regions of Beijing, Tianjin, Hebei, Jiangsu, Zhejiang, Shanghai, Shandong,Anhui, Shanxi, Shaanxi and Inner Mongolia were included), which was characterized as high bubble region.

Asymmetric Fluctuating Behavior of China＇s Housing Prices

The present study explains the reasons for the imbalanced development of the Chinese housing market. Using the quantile autoregression unit-root test, we examine housing prices in China＇s five major cities. The results show that the rising and falling of housing prices in these cities exhibits asymmetric reversion. When housing prices fall, market capital is highly sensitive to housing prices, and housing prices resist the pressure to faU further. However, when housing prices rise, the housing market becomes imbalanced, with housing prices tending to overreact in an upturn. The results of this study indicate that when housing prices rise irrationally, the government should intervene in the housing market promptly to prevent housing bubbles.