论文标题
经济政策不确定性指数的可见性图分析
Visibility graph analysis of economy policy uncertainty indices
论文作者
论文摘要
不确定性在全球经济中起着重要作用。在本文中，美国和中国的经济政策不确定性（EPU）指数被选为与国家经济政策不确定性相对应的代理变量。通过采用可见性图算法，美国和中国的四个经济政策不确定性指数被映射到复杂的网络中，并研究了相应网络的拓扑特性。所有四个指数的Hurst指数都在$ \左[0.5,1 \右] $之内，这意味着经济政策不确定性是持续的。 EPU网络的程度分布具有幂律尾巴，因此不含尺度。四个EPU网络的平均聚类系数彼此高且彼此接近，而这些网络则表现出较弱的分类混合。我们还发现，基于每日数据的美国EPU网络显示了小世界特征，因为平均最短路径长度随网络大小而对数增加，因此$ l \ weft（n \ right）= 0.626 \ ln n+0.405 $。我们的研究强调了从复杂网络的视角研究EPU的可能性。
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.
