Spatial Price Integration in Commodity Markets with Capacitated Transportation Networks

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 a well-defined transportation network, such as the network of pipelines in oil and gas markets. In this paper, we analyze the relationship between spatial price integration, i.e., 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 transportation network, especially when there are capacity constraints on links in the network. Our results are summarized using a price decomposition which 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 U.S., where the methodology effectively characterizes the effects of a series of well-documented network disruptions on market prices, providing important implications for operations and supply chain management.

Keywords: Commodity and Energy Operations, Price Integration, Spatial Price Equilibrium, Supply Chain Management, Network Disruptions, Congestion, Time Series Analysis, Mixed Integer Programming