Nonlinear effects of crude oil dependency on food prices in China: Evidence from quantile-on-quantile approach

Abstract

The repercussions of disruptions in the global crude oil market have a substantial influence on economies worldwide. Oil shocks are considered important estimators of many economic variables. The current research examines the effects of oil price shocks on food prices in China using monthly data from 2000M1 to 2021M12. The estimation is done using the Quantile on Quantile (QQ) estimation technique. The BDS test is used to test nonlinear dependence in variables. The results of this test confirm the presence of nonlinear dependence in variables. The estimated results of the QQ technique suggest a strong association between oil prices and food prices nexus in China with significant disparities across the quantiles. The lower and medium quantiles show a poor negative effect of crude oil prices on food prices. Nevertheless, it has been shown that there exists a strong positive correlation in the higher quantiles of the distribution, which suggests that an increase in global oil prices directly impacts the costs of food. The outcome of the study offers significant policy recommendations aimed at mitigating the detrimental impact of oil prices on food prices in China.

Keywords

• oil price shocks
• food prices
• BDS test
• quantile-on-quantile regression
• China