The 'Missing' Link: How Does Oil Transportation Trigger Macroeconomic Implications?

This paper studies how the micro behaviours of oil tankers and their interactions with exporters in the global oil transportation industry can trigger macro implications for oil trade, prices, and final good production. Using detailed Automated Identification System (AIS) data and random forest ensemble learning technique, we firstly explore the micro behaviours of ships by constructing a unique shipping dataset which tracks vessel's movements, loading status, and employment history. Next, inspired by the empirical observations, we develop a multi-market random search model in which ships and exporters optimise their behaviours in response to market-specific and idiosyncratic shocks. Lastly, by leveraging the shipping data, we structurally estimate our model using the Simulated Method of Moments (SMM). Our findings unveil the critical role played by the transportation industry in propagating shocks to the wider economy, which is often overlooked in the traditional setup of commodity market clearing conditions. Major results show that the congestion created by shipping market adjustment to trade shocks helps to stabilise the cycles in oil trade and final good production at the cost of more volatile oil prices. Furthermore, the shipping market adjustment does not create cycles; it only serves to dampen or amplify those induced by trade shocks. We also consider three natural experiments to analyse how the ship's searching behaviours within and across markets respond to variations in shipping policy (e.g., shipping fuel regulation to cut sulphur emission), risk (e.g., 2021 Suez Canal obstruction), and rationing scheme (e.g., the possibility of an unsanctioned Iran) and how each can have distinct macroeconomic consequences.