Anomalies and Recoveries in Agricultural Trade

• Published in: IDEAS Working Paper Series from RePEc
• Main Authors: Khadka, Savin, Gopinath, Munisamy, Batarseh, Feras A
• Format: Paper
• Language: English
• Published: St. Louis Federal Reserve Bank of St. Louis 01.01.2022
• Edition: 938
• Series: IATRC Commissioned Paper 30
• Subjects: Agricultural and Food Policy; agricultural trade; anomaly detection; International Relations/Trade; machine learning; policy uncertainty; Risk and Uncertainty
• DOI: 10.22004/ag.econ.329520

While uncertainty effects on macroeconomic indicators such as consumption, production, and investment have been well-studied, much remains to be known about the relationship between uncertainty and international trade. Some early explorations into this topic have revealed that high economic uncertainty can have detrimental impacts on trade, but the evidence is not conclusive, particularly that on the heterogeneity of uncertainty effects across sectors. This study provides one of the first investigations into the uncertainty-agricultural trade nexus. Application of a novel data-driven methodology - anomaly detection and classification - to monthly trade data at the HS-4 level finds that imports of agricultural commodities are reduced when economic uncertainty is high. Evidence also suggests that economic policy-related uncertainty has larger and more persistent impacts on agricultural trade than structural uncertainty arising from supply-side fluctuations. Interestingly, anticipatory stock-piling occurred, like in durable goods, when uncertainty is specific to trade policy.