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Modeling Nonlinearities in the U.S. Soybean-to-Corn Price Ratio: A Smooth Transition Autoregression Approach



The soybean-to-corn price ratio has long been considered one of the triggers that farmers use in the decision to produce corn or soybeans, but little has been done to analyze its dynamics. Recently, the soybean-to-corn price ratio options were introduced on the Chicago Board of Trade, providing the market participants with an opportunity to trade the relative prices of the crops. In this study, the author investigates potentially nonlinear dynamics of the soybean-to-corn price ratio by applying the smooth transition autoregression (STAR) modeling framework to the soybean-to-corn price ratio, derived from monthly futures prices of corn and soybeans. The estimated model demonstrates nonlinear dynamics, resulting in asymmetries in the adjustment to the long-run equilibrium of the soybean-to-corn price ratio. The findings of this research provide insightful implications to crop producers, input suppliers, and other market participants.