The Spatial Statistics Analysis of Housing Market Bubbles

Qian SUN, Yong TANG, Aimee YANG

系统科学与信息学报(英文) ›› 2017, Vol. 5 ›› Issue (3) : 250-266.

PDF(311 KB)
PDF(311 KB)
系统科学与信息学报(英文) ›› 2017, Vol. 5 ›› Issue (3) : 250-266. DOI: 10.21078/JSSI-2017-250-17

The Spatial Statistics Analysis of Housing Market Bubbles

    Qian SUN1,2, Yong TANG1,3, Aimee YANG4
作者信息 +

The Spatial Statistics Analysis of Housing Market Bubbles

    Qian SUN1,2, Yong TANG1,3, Aimee YANG4
Author information +
文章历史 +

摘要

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 andWest 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.

Abstract

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 andWest 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.

关键词

housing market bubbles / spatial statistics / state-space model

Key words

housing market bubbles / spatial statistics / state-space model

引用本文

导出引用
Qian SUN, Yong TANG, Aimee YANG. The Spatial Statistics Analysis of Housing Market Bubbles. 系统科学与信息学报(英文), 2017, 5(3): 250-266 https://doi.org/10.21078/JSSI-2017-250-17
Qian SUN, Yong TANG, Aimee YANG. The Spatial Statistics Analysis of Housing Market Bubbles. Journal of Systems Science and Information, 2017, 5(3): 250-266 https://doi.org/10.21078/JSSI-2017-250-17

参考文献

[1] Stiglitz J E. Symposium on bubbles. The Journal of Economic Perspectives, 1990, 4(2): 13-18.
[2] Renaud B. The 1985-94 global real estate cycle: Its causes and consequences. World Bank Publications, 1995.
[3] Krugman P. Bubble, boom, crash: Theoretical notes on Asia's crisis. MIT mimeo, 1998.
[4] Yuan Z G, Fan X Y. An analysis of rational bubbles in the real asset market. Economic Research Journal, 2003, 3(3): 34-43.
[5] Wong K Y. Housing market bubbles and the currency crisis: The case of Thailand. Japanese Economic Review, 2001, 52(4): 382-404.
[6] Jiang C H. A case study of the speculation bubble on china's real estate market. Management World, 2005(12): 71-84.
[7] Case K E, Shiller R J. Is there a bubble in the housing market?. Brookings Papers on Economic Activity, 2003(2): 299-362.
[8] Lü J L. The measurement of the bubble of urban housing market in China. Economic Research Journal, 2010(6): 28-41.
[9] Taipalus K. A global house price bubble? Evaluation based on a new rent-price approach. Evaluation Based on a New Rent-Price Approach, 2006.
[10] Mikhed V, Zemík P. Testing for bubbles in housing markets: A panel data approach. The Journal of Real Estate Finance and Economics, 2009, 38(4): 366-386.
[11] Shi X J, Zhou Y. Switching AR model for housing bubble test. System Engineering-Theory & Practice, 2014, 34(3): 676-682.
[12] Chan H L, Lee S K, Woo K Y. Detecting rational bubbles in the residential housing markets of Hong Kong. Economic Modelling, 2001, 18(1): 61-73.
[13] Zhou J K. Forming and evolvement of real estate bubble: An explanation of hypothesis financial supportive excess. Financial & Trade Economic, 2006(5): 3-10, 96.
[14] Chen N K. Asset price fluctuations in Taiwan: Evidence from stock and real estate prices 1973 to 1992. Journal of Asian Economics, 2001, 12(2): 215-232.
[15] Lee N J, Ong S E. Upward mobility, house price volatility, and housing equity. Journal of Housing Economics, 2005, 14(2): 127-146.
[16] Chen G J, Liu J E. Heterogeneous beliefs money illusion and the housing bubbles in China. Economic Management, 2011, 33(2): 46-53.
[17] Fan X Y, Zhang S D, Feng J R. The measurement and regional differences of the real estate price bubble: Taking 35 large and medium-sized cities in China as an example. On Economic Problems, 2013(11): 48-53.
[18] Pan A M, Wang H, Chen X Z. The bubble test of city residential price based on regional correlation. Finance and Trade Research, 2014(2): 41-48.
[19] Mei Z X, Huang L. Spatial autocorrelation analysis of housing prices distribution: A case study of Dongguan. China Land Science, 2008, 22(2): 49-54.
[20] Chhetri P, Han J H, Corcoran J. Modelling spatial fragmentation of the Brisbane housing market. Urban Policy and Research, 2009, 27(1): 73-89.
[21] Brady R R. Measuring the diffusion of housing prices across space and over time. Journal of Applied Econometrics, 2001, 26(2): 213-231.
[22] Chen L N, Wang H. Empirical investigation on the regional interactions of real estate prices in China. Statistical Research, 2012(7): 37-43.
[23] Shen T Y, Feng D T, Sun T S. Spatial econometrics. Peking University Press, 2011.
[24] Anselin L. Local indicators of spatial association-LISA. Geographical Analysis, 1995, 27(2): 93-115.
[25] Alessandri P. Bubbles and fads in the stock market: Another look at the experience of the US. International Journal of Finance & Economics, 2006, 11(3): 195-203.

基金

Supported by the China Scholarship Council, the Natural Science Foundation of Hunan (2017JJ3010) and the Science Foundation for the Excellent Youth Scholars of Department of Education of Hunan (13B008)

PDF(311 KB)

84

Accesses

0

Citation

Detail

段落导航
相关文章

/