经济政策不确定性指标的可视图分析
Visibility graph analysis of economy policy uncertainty indices
摘要：
不确定性在全球经济中发挥着重要作用。本文选取美国和中国的经济政策不确定性指数作为国家经济政策不确定性的代理变量。采用可视图算法，将美国和中国的4个经济政策不确定性指数映射到复杂网络中，并研究了相应网络的拓扑性质。四个指标的赫斯特指数均在$\left[0.5,1\right]$之内，表明经济政策的不确定性是持续的。EPU网络的度分布具有幂律尾，因此是无标度的。四个EPU网络的平均聚类系数都很高且彼此接近，但这些网络表现出弱的混合性。我们还发现，美国的EPU网络的日常数据的基础上，显示出小世界的功能，因为平均最短路径长度增加的网络规模，使$L\left(N\right)=0.626\ln N+0.405$。我们的研究突出了从复杂网络的角度来研究EPU的可能性。
英文摘要：
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 $\left[0.5,1\right]$, 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 $L\left(N\right)=0.626\ln N+0.405$. Our research highlights the possibility to study the EPU from the view angle of complex networks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
