Using global freight rates to predict local macroeconomic indicators

Prior research on the lead/lag relationship between freight rates and macroeconomic indicators has focused heavily on the Baltic Dry Index (BDI) and global or U.S. macroeconomic indicators. This study aims to extend this research by examining the lead/lag relationship between freight rates and local macroeconomic indicators in 12 countries encompassing the G7 and original BRICS countries. In addition to examining dry bulk freight rates measured by the BDI, this study includes tanker, container charter, and container route rates. Short-term lead/lag relationships are examined through vector autoregressive models, with long-term relationships examined through autoregressive distributed lag models. Effect size relationships are analyzed using impulse response functions. The results show that freight rates have strong predictive ability over industrial production and import/export volume, but are not as effective at predicting inflation and stock prices. In turn, macroeconomic indicators show strong predictive ability over dry bulk and tanker freight rates but little predictive ability for container freight rates.