Dynamic linkages between crude oil, climate policy uncertainty, and agricultural commodities in China: perspective from structural SBTVAR and VIRF analysis

Purpose This study explores the dynamic interactions between crude oil price fluctuations, climate policy uncertainty (CPU), and agricultural futures markets. With CPU increasingly influencing commodity price behaviour, we aim to uncover the transmission mechanisms through which oil markets mediate the impact of CPU on agricultural price levels and volatilities. Design/methodology/approach We employ a multifactor threshold vector autoregressive (TVAR) model with identified structural breakpoints to capture nonlinear and regime-dependent dynamics among crude oil prices, CPU, and agricultural futures markets. Structural identification allows us to compute both impulse response functions (IRF) and variance impulse response functions (VIRF), assessing the magnitude and duration of CPU-induced shocks on return and volatility levels of oil and agricultural commodities. Findings The analysis indicates that soybean futures exhibit the strongest response to CPU shocks, followed by corn and rice. For rice, the transmission mechanism operates more significantly through oil markets, whereas soybean and corn are less reliant on this channel. Notably, soybean markets show intensified financialization characteristics after the 2016 structural break. VIRF results reveal that corn demonstrates the highest volatility in response to oil market transitions, surpassing soybean and rice. Originality/value This research contributes to understanding how CPU and crude oil volatility jointly affect agricultural markets in a nonlinear framework. It provides novel evidence on channel heterogeneity and structural shifts in commodity markets, offering actionable insights for designing integrated climate and energy policies to contain risk spillovers.