How have global pandemics destabilised the food market?

The paper explores the influence of global pandemic uncertainty (GPU) on food prices (FP) by using the mixed-frequency vector autoregression (MF-VAR) model. Empirical findings indicate that the influence of GPU on FP varies across different scenarios, exhibiting either positive, negative, or insignificant effects. A positive influence implies that GPU fuels panic-buying and stockpiling behaviours, thereby boosting food demand. Concurrently, disruptions in agricultural production and food export restrictions tighten the market supply, potentially pushing FP upwards. Conversely, a negative effect suggests that the global economic downturn and food safety anxieties stemming from pandemic-related uncertainty may dampen food demand, causing FP to decline. In some instances, FP remains unaffected mainly by GPU due to the competing pressures from adverse climate change risks on the food market. Notably, FP's predictive error variance decomposition underscores that the net impact of GPU on FP is stimulatory. This overall effect aligns with the inter-temporal capital asset pricing model (ICAPM), which posits a positive influence of GPU on FP. The findings recommend that consumers and investors diversify their food sources, while policymakers should bolster food supply chain resilience, promote sustainable agriculture, establish emergency reserves and coordinate aid.