基于关联网络的经济政策不确定性全球溢出效应研究

基于关联网络视角,本文采用溢出指数方法构建2003-2018年全球经济政策不确定性的溢出网络,分别从静态和动态两个方面考察各国经济政策不确定性的溢入、溢出水平,以及全球经济政策不确定性溢出网络的结构特征。研究发现,第一,经济政策不确定性具有显著的跨国传染效应,其溢出网络呈现明显的时变特征。第二,发达国家经济政策不确定性的溢入、溢出水平高于发展中国家。第三,经济政策不确定性总溢出指数在极端事件的冲击下明显攀升,而与极端事件高度相关的国家具有更强的溢出效应。同时,各个国家经济政策不确定性的溢入水平和溢出水平的波动幅度截然不同,溢出水平的波动幅度较大而溢入水平相对平稳。第四,中国与日本、澳大利亚保持着较强的双向溢出关系,而且中国对新兴经济体,尤其是金砖国家的溢出水平较高,并主要接受韩国和欧洲发达国家的溢出影响。

A Study on Global Spillover Effect of Economic Policy Uncertainty from the Perspective of Network

In recent years, the frequent occurrence of global uncertainties such as Brexit and China-US trade frictions have made economic policy uncertainty(EPU) a hot topic of discussion in academia again. In order to investigate the global spillover effect of EPU, this paper uses the monthly EPU index constructed by Baker et al.(2016) and Huang & Luk(2020),and builds the EPU cross-country transmission network of top 15 countries in the world by GDP during 2003-2018,by using the information spillover index approach of Diebold & Yilmaz(2014). The findings are as followed. Firstly, EPU has significant cross-country contagious effect, and the spillover network is characterized by regionalization with obvious time-varying features. Secondly, the input and output level of EPU spillover in developed countries is higher than that of developing countries. Thirdly, the total EPU spillover index has risen sharply under the extreme shock, and countries highly correlated with the extreme events have stronger spillover effect. In addition, for all countries, the fluctuating range of the input level of EPU has notably different spillover effect compared with that of the output, with the output level fluctuating greatly whereas the input level remaining stable. Fourthly, China’s EPU has a strong bidirectional spillover effect in relation to Japan and Australia. China’s spillover effect on emerging economies, especially the BRICS countries, is also high. In the mean time, most spillover effect on China comes from South Korea and European developed countries. The marginal contributions of this paper are as follows: First, from the network perspective, this paper builds the global EPU spillover network, investigates the EPU spillover levels and structural characteristics in 15 countries from both static and dynamic aspects, and fully captures the dynamic features in the time dimension and the path structure in the space dimension of the spillover effect. Second,this paper focuses on China’s EPU, comprehensively analyzes the dynamic characteristics of China’s EPU spillover structure, and examines the co-movement effect between China’s and other countries’ EPU, which complements the existing research.