Short term analysis of lead time movements in dry bulk shipping A linear approach to explore the relationship between lead time and other order-specific determinants of historical voyage orders.

Abstract

This thesis investigates explanatory factors on a microeconomic level that affect lead time movements in the short term. We utilize historical voyage orders from January 2015 to April 2021 to analyze the relationship between contract-specific determinants and the lead time for dry bulk cargo. The data sample mainly includes smaller vessels carrying cargo across a wide range of routes. To determine the key drivers, we apply a linear regression model with an incorporated lasso penalty term. We divide the model into nine different commodity groups, where each model inludes the variables of cargo size, seasonality, infrastructure score, and voyage routes between loading and discharge regions. To find the most prominent factors and evaluate the accuracy of the corresponding coefficients, the model coefficients are validated through a bootstrap resampling process. By analyzing the relationship between lead time and order-specific explanatory factors, we seek to establish whether lead time patterns are connected to the market behaviour of other attributes in the dry bulk sector. Our thesis is the first contribution to lead time analysis in the literature of maritime economics. With the application of pre-fixture order data, we are able to investigate the potential of early market insight through lead time. Results suggest that lead time is affected by the size of cargo for all commodities, except steel products. Among the route dynamics, we find strong evidence of a higher lead time for transpacific routes. On the other hand, intra-Europe voyages have a consistently lower lead time than average. Finally, no seasonal patterns seem to affect the lead time in any direction.