Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/317645 
Year of Publication: 
2023
Citation: 
[Journal:] Journal of Business Economics and Management (JBEM) [ISSN:] 2029-4433 [Volume:] 24 [Issue:] 4 [Year:] 2023 [Pages:] 696-711
Publisher: 
Vilnius Gediminas Technical University, Vilnius
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.
Subjects: 
BDS test
China
food prices
oil price shocks
quantile-on-quantile regression
JEL: 
C22
Q11
Q43
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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