Trends and persistence in global olive oil prices after COVID-19

Manuel Monge ()
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Manuel Monge: Universidad Francisco de Vitoria

Journal of Revenue and Pricing Management, 2024, vol. 23, issue 5, No 9, 488 pages

Abstract: Abstract Once the coronavirus pandemic was declared by government authorities in March 2020 and several measures were adopted around the world to limit the effects of COVID-19, the limit agroeconomic processing affected important operations such as not being able to prepare the olive trees for the next harvest. This lack of processes has caused the consumer to perceive an increase in prices due to the shortage of product and the growing demand for olive oil around the world. This research paper, through the use of advanced statistical and econometric techniques, attempts to perform a specific analysis and understand the persistence of the data and the trend of global olive oil prices. Artificial intelligence techniques such as neural network models are also used to predict long-term price behavior. Using ARFIMA (p, d, q) model, the results suggest a non-mean reversion behavior, suggesting that the shock is expected to be permanent, causing a change in trend. This result is in line with that obtained using machine learning techniques, where the forecast suggests an increase of the prices around + 11.36% in the next 12 months.

Keywords: Global olive oil prices; Fractional integration; ARFIMA (p; d; q) model; Machine learning (search for similar items in EconPapers)
JEL-codes: C22 C53 Q11 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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DOI: 10.1057/s41272-024-00481-x

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