Title of article
Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory
Author/Authors
Wang، نويسنده , , Na and Li، نويسنده , , Dong and Wang، نويسنده , , Qiwen، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2012
Pages
13
From page
6543
To page
6555
Abstract
The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government policies in China on the changes of dynamics of GDP and the three industries adjustment. The work in our paper provides a new way to understand the dynamics of economic development.
Keywords
Government Policy , Visibility graph , Macroeconomic series , Degree distribution , Complex network , Topological property , community structure , Dynamics
Journal title
Physica A Statistical Mechanics and its Applications
Serial Year
2012
Journal title
Physica A Statistical Mechanics and its Applications
Record number
1736297
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