An analysis of international grain freight rates

Abstract

Transportation costs are often given little importance in international trade analysis because of inadequate knowledge about the important factors influencing transportation costs. Thus, the primary purpose of this study is to develop an empirical model that explains ocean freight rates for grain. The variables were selected for the estimated econometric model based on causal flow relationships between selected explanatory variables and the dependent variable, ocean freight rates for grain. The presence of autoregressive conditional heteroskedasticity (ARCH) in the OLS residuals suggested the superiority of generalized autoregressive conditional heteroskedacticity (GARCH) methodology for modeling. To correct the problem of autocorrelation, the lag of the dependent variable was included in the model as an explanatory variable. The estimated econometric model was designed to explain ocean freight rates for grain. Results indicate rates increase at a decreasing rate with distance and rates decrease at a decreasing rate as shipment quantity increases. Highest rates were associated with the berth term followed by the free discharge and free-in-and-out terms. The ships with U.S. flags were found to charge higher rates when compared to ships with foreign flags. The grain freight rate was found to increase with increases in the voyage-chartered tonnage of coal. However, rates declined as voyage-chartered tonnage of other ore increased. This may have occurred because of increased grain back-haul opportunities between selected grain- and ore-trading countries, thus the unexpected negative relationship between grain freight rates and voyage-chartered shipments of other ore. The results also suggest the presence of seasonality in grain freight rates with highest rates in the second quarter and lowest rates in the third quarter of the year. Finally, the estimated model was proven superior in generating out-of-sample ship rate forecasts as compared to a random walk model. This suggests the model may be used as a tool for forecasting grain freight rates.