Logistics competition between the U.S. and Brazil for soybean shipments to China: An optimized Monte Carlo simulation approach

Gwen Kamrud, William W. Wilson and David Bullock ()

Journal of Commodity Markets, 2023, vol. 31, issue C

Abstract: The United States and Brazil fiercely compete with each other in the Chinese soybean import market. Logistical functions and costs are volatile and risky and influence the export competition between the two countries. This study analyzes commodity trading strategies and the effect of logistical functions and costs in the United States and Brazil for shipments to China using an Optimized Monte Carlo Simulation model accounting for a large number of random and correlated variables. Base case results approximate the actual monthly data between 2013 and 2019. These results indicate that the United States captures a larger share of soybean export shipments between December and March while Brazil is dominant from April to November. Sensitivity analyses were performed on logistical variables in the United States (ocean shipping costs, U.S. secondary rail car market, and rail unload incentives) and Brazil (improving logistical infrastructure and wait times) to illustrate their impacts on optimal trading strategies.

Keywords: Soybeans; Trading; Optimized monte carl simulation; Brazil; China; United States (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jocoma:v:31:y:2023:i:c:s2405851322000472

DOI: 10.1016/j.jcomm.2022.100290

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