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

IF 3.9 Q2 TRANSPORTATION Maritime Transport Research Pub Date : 2023-07-20 DOI:10.1016/j.martra.2023.100097
Joshua Shackman , Margaret Ward
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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.

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沿海、五大湖、内陆和深海运费之间的相互关系:纵向方法
本研究调查了美国水运行业的四个关键地区的运费率-沿海,五大湖/St。劳伦斯河,内陆水道,和深海航运。本研究涉及的数据包括2008年至2021年这四个行业运费的纵向数据,以及宏观经济变量和大宗商品价格的数据。本研究的目的如下:(A)检验四种运价之间的领先/滞后关系,(B)检验运价与宏观经济变量之间的领先/滞后关系,(C)检验运价与商品价格之间的领先/滞后关系。我们确实发现运费对彼此以及宏观经济指标都具有显著的预测能力。在预测其他运价方面,内陆运价是唯一能够预测其他三种运价的运价。在短期内,内陆和深海运价在预测宏观经济指标方面都表现出很强的能力,但深海运价具有更大的长期预测能力。另一方面,商品价格只能最低限度地由运费预测,但也是内陆运费的有力预测因素。沿海和大湖地区的运价仅显示出最小的预测能力。竞争条件的差异,以及这四个部门之间的货物类型,被认为是对这些结果的解释。
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