Anomalies in agricultural trade: A Bayesian classifier approach

Abstract This study examines the uncertainty‐agricultural trade nexus. Uncertainty effects on macroeconomic indicators such as consumption and investment have been well studied. However, less is known about the relationship between uncertainty and international trade, particularly the heterogeneity...

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Bibliographic Details
Published inJournal of the Agricultural and Applied Economics Association Vol. 2; no. 3; pp. 402 - 427
Main Authors Khadka, Savin, Gopinath, Munisamy, Batarseh, Feras A.
Format Journal Article
LanguageEnglish
Published Davis John Wiley & Sons, Inc 01.09.2023
Subjects
Agricultural commodities
Agricultural exports & imports
Agricultural production
Anomalies
Bayesian analysis
Beef
Economic activity
Economic growth
Economic policy
GDP
Great Recession
Gross Domestic Product
Heterogeneity
Imports
International trade
Investigations
Investments
Soybeans
Tariffs
Trade policy
Uncertainty
Volatility
United States > US
China
Africa
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Summary:Abstract This study examines the uncertainty‐agricultural trade nexus. Uncertainty effects on macroeconomic indicators such as consumption and investment have been well studied. However, less is known about the relationship between uncertainty and international trade, particularly the heterogeneity of that linkage across sectors. Application of a novel data‐driven methodology—anomaly detection and classification via a Naïve Bayesian Classifier—to monthly data at the HS‐4 level finds that agricultural imports are reduced when economic policy uncertainty is high. The effects of policy‐related uncertainty are more persistent than that of supply‐side fluctuations. Anticipatory stock‐piling occurred when uncertainty is specific to trade policy.
ISSN:2769-2485
2769-2485
DOI:10.1002/jaa2.69