A Study of the Cross-National Spillover of Inflation-at-Risk from a Time-Varying Perspective
Against a backdrop of unprecedented change,extreme events and record levels of inflation are taking place in economies around the world.To adequately consider the time-varying and extreme nature of inflation in this new global paradigm,this paper proposes and estimates a time-varying parameters quantile vector autoregressive(TVP-QVAR)model.The model aims to describe the contemporary and intertemporal relationships of inflation-at-risk from a time-varying perspective.Using a quantile-based approach,the paper also proposes an extended time-varying spillover index and a network construction method to quantify the mutual spillover characteristics of inflation-at-risk among major economies in high,moderate and low inflation scenarios.The results indicate that the contemporaneous and lagged inflation relationships between countries exhibit both heterogeneity at different quantiles and significant time-varying characteristics,with structural changes occurring in major events.The inflation-at-risk spillover analysis reveals a U-shaped pattern for the overall spillover index at different quantiles,being lower in the middle and higher at both ends.Notably,European and American countries are the primary sources of inflation risk spillover in extremely low and moderate inflation states.Conversely,during extremely high inflation,Russia's inflation risk spillover significantly increases,while China primarily acts as a net recipient of inflation in most scenarios.Further analysis of the influencing factors suggests that inflation-at-risk spillover effects and the asymmetry of risk accumulation at the tail end are primarily influenced by global inflation levels,global economic conditions,crude oil price fluctuations,financial market volatility and uncertainty in US policies.This paper offers a new perspective for the study of time-varying complex economic systems in extreme situations and provides useful information for China to prevent imported inflation risks under a new development paradigm.
万方数据
维普
