  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.
