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

Abstract

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.

Exchange Rates, Foreign Income, and U. S. Agricultural Exports

“…An accepted procedure in this case has been to treat the variables as stationary without differencing them (Harris 1995, pp. 27-29, Kwiatkowski et al 1992, and Babula, Bessler, and Payne 2004. When evidence from the ADF test suggested that evidence was sufficient to reject the null hypothesis of nonstationarity, we concluded that the variable was likely stationary.…”

“…'The application of DAG involves the theoretical work of Pearl (1995) and the algorithm (PC algorithm) in Spirtes, Glymour, and Scheines (2000). DAG analysis allows the construction of the data-determined orthoganization on contemporaneous innovation covariance (Swanson and Granger 1997) to assess the degree of interconnectivity and direction of causation (Awokuse and Bessler 2003, Bessler and Yang 2003, Babula, Bessler, and Payne 2004. Our study focuses on illuminating the contemporaneous relationships among innovations (residuals).…”

The Causal Structure of Land Price Determinants

“…In recent studies, several researchers have advocated the use of DAG, a recently developed statistical method for analyzing contemporaneous causal relationships as an alternative data‐determined approach to identifying the restrictions for structural VAR models (Swanson and Granger 1997; Babula et al 2004; Yang and Bessler 2004). Specifically, identification is achieved by modeling the contemporaneous innovations from a VAR model with DAGs.…”

Deconstructing Wheat Price Spikes: A Model of Supply and Demand, Financial Speculation, and Commodity Price Comovement

“…Agricultural economists have mainly applied SVAR methods to questions of market integration. In the case of wheat, SVAR studies examine linkages between prices for one commodity in different locations (e.g., Goodwin and Schroeder, 1991;Mohanty et al 1999;McKenzie, 2005), prices for different degrees of product processing (Babula et al, 2004) for wheat and wheat products, and prices across commodities (Power and Vedenov, 2009) for a set of agricultural and energy commodities during the 2008 price boom and bust. In general, these applications sought to examine relationships between prices across markets.…”