Uncertainty shocks and risk spillovers in Chinese agricultural markets

This study examines extreme risk spillovers between multidimensional uncertainty shocks and Chinese agricultural spot markets. Using weekly data from January 2005 to August 2025, it incorporates economic policy uncertainty, climate policy uncertainty, geopolitical risk, and financial market uncertainty into a quantile vector autoregression framework to construct spillover networks in the time and frequency domains. A factor-augmented vector autoregression model is further used to estimate dynamic impulse responses. The results show that spillovers at extreme quantiles are markedly stronger than at the median quantile and differ between the lower and upper tails. Dynamic spillovers vary over time and increase sharply around major external shocks, including the 2008 global financial crisis and the 2022 Russia-Ukraine conflict. Long-term risk transmission is more pronounced in the frequency domain, and the four uncertainty indicators generally act as net risk transmitters. The impulse responses also differ in direction, intensity, and persistence across market states and time horizons. These findings provide evidence on tail-dependent and time-frequency risk transmission in agricultural spot markets.