This work analyzes the impact that the fluctuations of the large-scale atmospheric-oceanic phenomenon known as El Niño Southern Oscillation have on wheat production, and the consequent changes in prices at the global scale by using computer simulations. Several intermediate results are obtained on the way to the final goal. The identification of geographic areas relevant to the international wheat market and the integration of heterogeneous datasets are two of them. Building on these two results, the local effects of the El Niño Southern Oscillation phases on the wheat yield are quantified using robust Anova regression, and their potential impacts on the aggregate production of each production area are estimated. Finally, these estimated impacts are provided as inputs to the computational model, which outputs wheat prices of the 12 internationally relevant production areas. Simulation results show how the cross-section distributions of prices conditional on the occurring of El Niño and La Niña spread to the right compared to that observed for the Neutral phase. Therefore, both non-neutral phases imply an increase of average and dispersion of prices, although the effect of La Niña is weaker than that of El Niño.

Simulating the effect of El Niño Southern Oscillation on the worldwide wheat prices

Gianfranco Giulioni
Secondo
;
2022-01-01

Abstract

This work analyzes the impact that the fluctuations of the large-scale atmospheric-oceanic phenomenon known as El Niño Southern Oscillation have on wheat production, and the consequent changes in prices at the global scale by using computer simulations. Several intermediate results are obtained on the way to the final goal. The identification of geographic areas relevant to the international wheat market and the integration of heterogeneous datasets are two of them. Building on these two results, the local effects of the El Niño Southern Oscillation phases on the wheat yield are quantified using robust Anova regression, and their potential impacts on the aggregate production of each production area are estimated. Finally, these estimated impacts are provided as inputs to the computational model, which outputs wheat prices of the 12 internationally relevant production areas. Simulation results show how the cross-section distributions of prices conditional on the occurring of El Niño and La Niña spread to the right compared to that observed for the Neutral phase. Therefore, both non-neutral phases imply an increase of average and dispersion of prices, although the effect of La Niña is weaker than that of El Niño.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/759857
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