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首頁> 美國政府科技報(bào)告 >Dynamic Economic Relationships Among U.S. Soy Product Markets: Using a Cointegrated Vector Autoregression Approach with Directed Acyclic Graphs
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Dynamic Economic Relationships Among U.S. Soy Product Markets: Using a Cointegrated Vector Autoregression Approach with Directed Acyclic Graphs

機(jī)譯：美國大豆產(chǎn)品市場的動(dòng)態(tài)經(jīng)濟(jì)關(guān)系：使用有向無環(huán)圖的協(xié)整向量自回歸方法

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This paper applies a combined methodology of a recently developed directed acyclic graph(DAG) analysis with Johansen and Juselius methods of the cointegrated vector autoregression (VAR)model to a monthly U.S. system of markets for soybeans, soy meal, and soy oil. Primarily a methodspaper, Johansen and Juselius procedures are applied, with a special focus on statistically addressinginformation inherent in well-known sources of non-normal data behavior to illustrate the effectiveness ofmodeling the system as a cointegrated multi-market system. Perhaps for the first time, methods of thecointegrated VAR model are combined with DAG analysis to account for contemporaneously correlatedresiduals, and are applied to this U.S. soy-based system. Analysis of the error correction or cointegrationspace illuminates the empirical nature of policy-relevant market elasticities, price transmissionparameters, and effects of important policy and institutional changes/events on U.S. soy-related market long-run horizons beyond a single crop cycle. A statistically strong U.S. demand for soybeans emergedas the primary cointegrating relation in the error-correction space. Analysis of the DAG-adjusted cointegrated VAR models forecast error variance decomposition illuminates how the soy-related variables and the three U.S. soy product markets dynamically interact at alternative time horizons extending up to two-years.

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