Open Access

A Time Trend and Persistence Analysis of Sunflower Oil and Olive Oil Prices in the Context of the Russia-Ukraine War

Manuel Monge

Universidad Francisco de Vitoria

DOI: https://doi.org/10.36956/rwae.v5i3.1096

Received: 30 April 2024; Published: 26 August 2024

Copyright © 2024 Manuel Monge. Published by Nan Yang Academy of Sciences Pte. Ltd..

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


Abstract

The imbalances between sunflower oil production (Ukraine) and olive oil production (Europe) due to the substitution effects caused by the Russian invasion of Ukraine on 24 February 2022 affected the prices. Given that Ukraine is the largest producer of global sunflower oil and Europe is the largest territory that produces olive oil, this scientific article tries to analyze the global prices of both vegetable oils and understand how the war between Russia and Ukraine has affected them. Advanced statistical and econometric methods to carry out this analysis have been used. It is found that the prices of both variables separately have similar behavior and that the shock caused by the war will be transitory, with the original price trend recovering in the long term using fractional integration methods. In a multivariate analysis, using a causality test in the frequency domain we observe that both variables are related to each other, and the effects of war will have an impact in the long term, with olive oil being the cause. A negative relationship between both variables measured with a wavelet analysis is also observed. Furthermore, if this trend continues, the price of olive oil would prevail over the price of sunflower in the war between Russia and Ukraine. Finally, a 12-month prediction is presented using artificial neural networks, where the price of olive oil will be high for at least 11 more months. The price of sunflower oil is predicted to last for only 5 more months.

Keywords: Global olive oil prices; Global sunflower oil prices; Fractional integration; ARFIMA (p,d,q) model; FCVAR model; Causality test; Wavelet analysis


References

Online ISSN: 2737-4777, Print ISSN: 2737-4785, Published by Nan Yang Academy of Sciences Pte. Ltd.