Exploring the Determinants of Agricultural Commodity Returns

Abstract: This paper investigates the Granger causal relations between agricultural commodity returns and several potential determinants using a multivariate Vector Error Correction Model (VECM) and Impulse Response Functions (IRF). Agricultural commodities are critical for global food supply, and understanding their determinants is crucial for policymakers and investors. Results show that biofuel and fertilizer returns have a short-run predictive power over future agricultural commodity returns. We contribute to the existing body of literature by examining a comprehensive array of determinants. Our findings could help inform decision-makers in the agricultural sector and improve the investment processes for agricultural commodity investors.