Forecasting World Food Price Volatility: Performance of the GARCH Model with Different Distributions Assumptions

Lagesh Aravalath and Subhendu Dutta
Additional contact information
Subhendu Dutta: ICFAI School of Social Science, India

Economic Alternatives, 2024, issue 1, 120-141

Abstract: This study examines the performance of the GARCH model with two different error distribution assumptions in forecasting the volatility of the global food price indices. For this purpose, it uses the monthly series of the world food price index (FPI), Meat Price Index (MPI), Dairy Price Index (DPI), Cereals Price Index (CPI), and vegetable Oil Price Index (OPI) sourced from the FAO database over a period from 1990M1 to 2022M3. We found that the model selected by the Akaike information criteria (AIC), the Schwarz criteria (SC), and the Hannan-Quinn (HQ) criteria performs well in the prediction of the volatility of all five food price indices. Further, the in-sample and out-of-sample performance analysis revealed that the GARCH models selected by the information criteria, both the normal and student-t distributions perform equally well in forecasting volatility. Finally, the analysis of the volatility series extracted from the best-fit GRACH models shows that the world food price has witnessed unusually large and sustained volatility during the periods 1994-95, 2007-08, and 2011-12. However, the magnitude of the fluctuations in the world food price observed during the recent Covid19 pandemic period was relatively mild, with the exception of vegetable oil prices.

Keywords: forecasting; GARCH; volatility; World Food Price; Error distributions (search for similar items in EconPapers)
JEL-codes: C53 E31 Q10 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.unwe.bg/doi/eajournal/2024.1/EA.2024.1.08.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nwe:eajour:y:2024:i:1:p:120-141

Access Statistics for this article

More articles in Economic Alternatives from University of National and World Economy, Sofia, Bulgaria Contact information at EDIRC.
Bibliographic data for series maintained by Vanya Lazarova ().