文献类型：期刊文献

英文题名：Visibility graph analysis of economy policy uncertainty indices

作者：Dai, Peng-Fei[1]; Xiong, Xiong[1,2]; Zhou, Wei-Xing[3,4,5]

机构：[1] College of Management and Economics, Tianjin University, Tianjin, 300072, China; [2] China Center for Social Computing and Analytics, Tianjin University, Tianjin, 300072, China; [3] Department of Finance, East China University of Science and Technology, Shanghai, 200237, China; [4] Research Center for Econophysics, East China University of Science and Technology, Shanghai, 200237, China; [5] Department of Mathematics, East China University of Science and Technology, Shanghai, 200237, China

年份：2020

外文期刊名：arXiv

收录：EI(收录号：20200573918)

语种：英文

外文关键词：Planning - Uncertainty analysis - Visibility

摘要：Uncertainty plays an important role in the global economy. In this paper, the economic policy uncertainty (EPU) indices of the United States and China are selected as the proxy variable corresponding to the uncertainty of national economic policy. By adopting the visibility graph algorithm, the four economic policy uncertainty indices of the United States and China are mapped into complex networks, and the topological properties of the corresponding networks are studied. The Hurst exponents of all the four indices are within [0.5, 1], which implies that the economic policy uncertainty is persistent. The degree distributions of the EPU networks have power-law tails and are thus scale-free. The average clustering coefficients of the four EPU networks are high and close to each other, while these networks exhibit weak assortative mixing. We also find that the EPU network in United States based on daily data shows the small-world feature since the average shortest path length increases logarithmically with the network size such that L (N) = 0.626 ln N + 0.405. Our research highlights the possibility to study the EPU from the view angle of complex networks. Copyright ? 2020, The Authors. All rights reserved.