Essays on International Trade, Forecasting and the Container Shipping Network

Seaborne vessels transport approximately 70% of global trade by value according to the United Nations Conference on Trade and Development. The grounding of the 400-meter long container ship “Ever Given” and the ensuing blockage of the Suez Canal for six days in March 2021 clearly demonstrated the importance of a wellfunctioning maritime transport sector for the flow of goods. Container ships play a particularly crucial role in this transportation network as they transport 66% of the maritime cargo by value.

At the same time, the Automatic Identification System (AIS), which was developed to avoid collisions at sea using high frequency radio signals, generates extremely recent information on ships’ positions, course and draught. The essays below have in common that they utilize the daily positions of all approximately 6,000 container ships after the year 2015 for economic analysis. The studies rely on the data to develop and test methods for forecasting trade flows, to investigate the impact of oil prices on trade costs and to quantify the disruptive effects of tropical cyclones and piracy on maritime shipping and trade.

The first chapter uses the AIS data to derive 880 time series at the port and sea area level to reflect seaborne cargo flows. Using a combination of the least absolute shrinkage and selection operator and the partial least squares, the paper demonstrates that these time series can reliably forecast unilateral and bilateral trade flows. The second chapter dervies a highly dimensional data for shipping that sllows the study of trade costs from container shipping. Oil prices are caculated to increase the time of transportation and increase freight rates. The following chapter investigates the effects of tropical cyclones on internaitonal trade and the container shipping network. In the last chapter, research finds that maritime piracy reduces global trade flows.

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