Spatial Price Integration in Commodity Markets with Capacitated Transportation Networks

John Birge, Timothy C. Y. Chan (), J. Michael Pavlin () and Ian Yihang Zhu ()
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Timothy C. Y. Chan: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada
J. Michael Pavlin: Lazaridis School of Business and Economics, Wilfrid Laurier University, Waterloo, Ontario N2L 3C5, Canada
Ian Yihang Zhu: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada

Operations Research, 2022, vol. 70, issue 3, 1739-1761

Abstract: Spatial price integration is extensively studied in commodity markets as a means of examining the degree of integration between regions of a geographically diverse market. Many commodity markets that are commonly studied are supported by stable and well-defined transportation networks. In this paper, we analyze the relationship between spatial price integration, that is, the distribution of prices across geographically distinct locations in the market and the features of the underlying transportation network. We characterize this relationship and show that price integration is strongly influenced by the characteristics of the network, especially when there are capacity constraints on links in the network. Our results are summarized using a price decomposition that explicitly isolates the influences of market forces (supply and demand), transportation costs, and capacity constraints among a set of equilibrium prices. We use these theoretical insights to develop a unique discrete optimization methodology to capture spatiotemporal price variations indicative of underlying network bottlenecks. We apply the methodology to gasoline prices in the southeastern United States, where the methodology effectively characterizes the price effects of a series of well-documented network and supply chain disruptions, providing important implications for operations and supply chain management.

Keywords: Environment; Energy; and Sustainability; commodity and energy operations; price integration; spatial price equilibrium; supply chain management; network disruptions; congestion; time series analysis; mixed integer optimization (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:70:y:2022:i:3:p:1739-1761

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