Dynamic Relationships Among U.S. Wheat-Related Markets: Applying Directed Acyclic Graphs to a Time Series Model

Using advanced methods of directed acyclic graphs with Bernanke structural vector autoregression models, this article extends recent econometric research on quarterly U.S. markets for wheat and wheat-based value-added products downstream. Analyses of impulse response simulations and forecast error variance decompositions provide updated estimates of market elasticity parameters that drive these markets, and updated policy-relevant information on how these quarterly markets run and dynamically interact. Results suggest that movements in wheat and downstream wheat-based markets strongly influence each other, although most of these effects occur at the longer-run horizons beyond a single crop cycle.

Dynamic Relationships Among U.S. Wheat-Related Markets: Applying Directed Acyclic Graphs to a Time Series Model Academic Article