Reimagining External Uncertainty: a Dynamic Composite Index and its Asymmetric Inflationary Footprint in China
摘要
This paper constructs a novel External Uncertainty Composite Index (EUCI) for China, integrating geopolitical, economic, and financial sources of external risk. Dynamic weights for the EUCI are endogenously determined using a time-varying parameter vector autoregressive (TVP-VAR) model, reflecting the evolving cumulative impact of distinct uncertainty shocks on China’s economy. Employing a nonlinear autoregressive distributed lag (NARDL) model, we then assess the EUCI’s asymmetric and time-varying effects on domestic inflation and its forecasting performance. The empirical findings reveal that the EUCI exerts a significant, asymmetric, and temporally dynamic influence on inflation. Notably, the EUCI consistently outperforms individual uncertainty measures in forecasting inflation. These results underscore the EUCI’s utility as a comprehensive indicator for inflation analysis and prediction in an environment of heightened global uncertainty, providing critical insights for policymakers.