The interrelationship between coastal, Great Lakes, Inland, and deep-sea freight rates: A longitudinal approach

Abstract

This study examines freight rates in four key areas of the U.S. water freight transportation industry –coastal, Great Lakes/St. Lawrence River, inland waterways, and deep-sea shipping. The data involved in this study includes longitudinal data from 2008 to 2021 on freight rates in all four of these sectors along with data on macroeconomic variables and commodity prices. The purpose of this study is as follows: (A) examine lead/lag relationships between the four freight rates, (B) examine lead/lag relationships between the freight rates and macroeconomic variables, and (C) examine lead/lag relationships between the freight rates and commodity prices. We do find significant predictive power for freight rates both on each other as well as for macroeconomic indicators. In terms of predicting other freight rates, inland freight rates are the only ones to predict all three other freight rates. Both inland and deep-sea freight rates are shown to be strong at predicting macroeconomic indicators in the short run, but deep sea has greater long-term predictive power. Commodity prices on the other hand are only minimally predicted by freight rates but are also strong predictors of inland freight rates. Coastal and Great Lake freight rates are shown only to have minimal predictive power. Differences in competitive conditions, as well as the type of cargo between these four sectors, are proposed as an explanation for these results.

Keywords

• Water freight rates
• Forecasting
• Inland shipping