Democratising Agricultural Commodity Price Forecasting: The AGRICAF Approach

Rotem Zelingher

No 356741, Agricultural Economics Society 99th Annual Conference, April 14-16, 2025, The University of Bordeaux, France from Agricultural Economics Society (AES)

Abstract: Ensuring food security is a global challenge, particularly in low-income countries where food prices affect access to nutritious food. The instability of global agricultural commodity (AC) prices exacerbates food insecurity, with international trade restrictions and market disruptions further complicating the situation. Although online platforms exist for monitoring food prices, there is still a need for accessible, detailed forecasts for non-specialists. This paper proposes the Agricultural Commodity Analysis and Forecasts (AGRICAF) methodology, integrating explainable machine learning (XML) and econometric techniques to analyse and forecast global ACs prices up to one year ahead across different horizons. This innovative integration allows us to model complex interactions while providing clear, interpretable results. We demonstrate the utilization of AGRICAF, applying it to three major commodities and explaining how different factors impact prices across months and forecast horizons. By facilitating access to reliable forecasts of AC prices, AGRICAF can advance a fairer and sustainable food system.

Keywords: Demand and Price Analysis; Food Consumption/Nutrition/Food Safety; International Relations/Trade; Teaching/Communication/Extension/Profession (search for similar items in EconPapers)
Pages: 43
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aes025:356741

DOI: 10.22004/ag.econ.356741

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