This study leveraged systemic risk data from 760 financial institutions across 18 e-conomies to examine the time-varying contagion network of global systemic risk through a time-varying parameter vector autoregression model and generalized variance decomposition.It further assessed the impact of various economies on China's upper quantile systemic risk by employing the quantile Granger causality test.The findings reveal that integrating systemic risk data with the time-varying contagion network effectively validates the occurrence of major risk events.Both developed and emerging economies act as net risk spreaders,potentially spreading risk to main-land China either directly or via the Hong Kong Special Administrative Region.Throughout the sample period-including significant risk events such as the 2008 financial crisis,the European debt crisis,the United States-China trade war,and the COVID-19 pandemic-China was a net risk recipient,with the risk inflow effect intensifying to historic highs during the COVID-19 pan-demic.Notably,the United States and United Kingdom exerted substantial impacts on China's up-per quantile systemic risk during these events,with external shocks to China's upper quantile sys-temic risk reaching unprecedented severity during the COVID-19 pandemic.
关键词
系统性风险/时变传染网络/分位数Granger因果检验
Key words
systemic risk/time-varying contagion network/quantile Granger causality test
维普
万方数据