Forecasting Global Maize Prices From Regional Productions

Prévision des prix mondiaux du maïs à partir des productions régionales

Rotem Zelingher and David Makowski
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Rotem Zelingher: ECO-PUB - Economie Publique - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
David Makowski: MIA Paris-Saclay - Mathématiques et Informatique Appliquées - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: This study analyses the quality of six regression algorithms in forecasting the monthly price of maize in its primary international trading market, using publicly available data of agricultural production at a regional scale. The forecasting process is done between one and twelve months ahead, using six different forecasting techniques. Three (CART, RF, and GBM) are tree-based machine learning techniques that capture the relative influence of maize-producing regions on global maize price variations. Additionally, we consider two types of linear models—standard multiple linear regression and vector autoregressive (VAR) model. Finally, TBATS serves as an advanced time-series model that holds the advantages of several commonly used time-series algorithms. The predictive capabilities of these six methods are compared by cross-validation. We find RF and GBM have superior forecasting abilities relative to the linear models. At the same time, TBATS is more accurate for short time forecasts when the time horizon is shorter than three months. On top of that, all models are trained to assess the marginal contribution of each producing region to the most extreme price shocks that occurred through the past 60 years of data in both positive and negative directions, using Shapley decompositions. Our results reveal a strong influence of North-American yield variation on the global price, except for the last months preceding the new-crop season.

Keywords: Price forecasting; Regional production (search for similar items in EconPapers)
Date: 2022-04-28
New Economics Papers: this item is included in nep-agr, nep-big and nep-cmp
Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-03764942v1
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Published in Frontiers in Sustainable Food Systems, 2022, 6, 10 p. ⟨10.3389/fsufs.2022.836437⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03764942

DOI: 10.3389/fsufs.2022.836437

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