文献类型：期刊文献

英文题名：Club convergence of house prices: Evidence from China's ten key cities

作者：Meng, Hao[1];Xie, Wen-Jie[2,3];Zhou, Wei-Xing[4,5]

机构：[1]E China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Dept Finance, Res Ctr Econophys, Shanghai 200237, Peoples R China;[3]E China Univ Sci & Technol, Postdoctoral Res Stn, Shanghai 200237, Peoples R China;[4]E China Univ Sci & Technol, Dept Finance, Dept Math, 130 Meilong Rd, Shanghai 200237, Peoples R China;[5]E China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China

年份：2015

卷号：29

期号：24

外文期刊名：INTERNATIONAL JOURNAL OF MODERN PHYSICS B

收录：;WOS:【SSCI(收录号:WOS:000362455200008)，SCI-EXPANDED(收录号:WOS:000362455200008)】；

基金：This work was partially supported by the National Natural Science Foundation of China (71131007), the Program for Changjiang Scholars and Innovative Research Team in University (IRT1028), the Shanghai (Follow-up) Rising Star Program (Grant No. 11QH1400800), the Shanghai "Chen Guang" Project (2012CG34), and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：Econophysics; random matrix theory; club convergence; house prices; ripple effect

摘要：The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a marked fall during the global financial tsunami and China's economy has also slowed down by about 2%-3% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than 10 years. However, the structure and dynamics of the Chinese housing market are less studied. Here, we perform an extensive study of the Chinese housing market by analyzing 10 representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5% of the house price growth, indicating very high systemic risk in the Chinese housing market. The 10 key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices among different cities.