Contemporaneous causal orderings of US corn cash prices through directed acyclic graphs

• Published in: Empirical economics Vol. 52; no. 2; pp. 731 - 758
• Main Author: Xu, Xiaojie
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2017; Springer Nature B.V
• Subjects: Algorithms; Causality; Commodities; Corn; Econometrics; Economic Theory/Quantitative Economics/Mathematical Methods; Economics; Economics and Finance; Error correction & detection; Finance; Graphs; Insurance; Investigations; Management; Prices; Statistics for Business; Time series; Q11; C32; Cointegration; Corn; Graph theory; Error correction model; Causality; Price discovery; L11
• DOI: 10.1007/s00181-016-1094-4
• ISSN: 0377-7332

This study investigates dynamic relationships among US corn cash prices for the years 2006–2011. Using daily data from 182 markets in seven Midwestern states, an error correction model is estimated and directed acyclic graphs characterize the contemporaneous causal relationships among prices from different states. Empirical results based on the PC algorithm show that three states, Iowa, Ohio, and Minnesota, dominate corn cash prices. Four potential causal paths among the three states also are identified. Given that physical flows of grain are different at different times of the year, the data are divided into storage periods and harvest periods, and a VAR in differences is adopted to model the price relationships. While Iowa and Ohio continue to dominate corn prices during the storage period, the causal flows are mixed during the harvest period. An application of the LiNGAM algorithm refines the results relative to those derived from the PC algorithm and reveals that Iowa, the leading corn-producing state, is the only state that dominates pricing over the crop year.