Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5103228 | Physica A: Statistical Mechanics and its Applications | 2017 | 23 Pages |
Abstract
The consumer price index (CPI) contains rich information of the consumer market, in order to characterize the essential characteristics of the consumer market of China, a novel method by using complex network theory is proposed to visualizing the evolution and transformation characteristics of correlated modes among the regional consumer markets. CPI data of 31 provinces and cities of China are selected as sample data. Underlying dynamics of time-evolving correlation networks are revealed. A formula to measure the systemic risk in the consumer market is designed. And the correlation modes transmission network of the regional consumer markets is obtained. Numerical simulations show that the consumer market network has co-movement, group-occurring and small-word property. Different regions played different roles in the consumer market of China. The risk in the consumer market presented a decreasing trend from April 2013 but remain at the high level. Different from the stochastic system, the consumer market of China both has the short-range correlation and the long-range correlation. The strength of correlation modes transmission network basically satisfies a power-law distribution. The correlation modes are transferred into each other conveniently, although the consumer market system is highly complicated. The transformation of the correlation patterns of the regional consumer markets mainly revolves around three core correlation modes and each transformation needs to undergo 4 non-core modes.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Minggang Wang, Lixin Tian, Hua Xu, Weiyu Li, Ruijin Du, Gaogao Dong, Jie Wang, Jiani Gu,