Abstract
The shipping market has gone through a rough time since the start of the crisis. Today the general sentiment is that rates are improving and that the worst is behind us. However for the shipbuilding sector this does not seem to hold, with rising market sentiment, more orders would be expected, however, the uncertainty around the required Green House Gas reductions agreed upon by the IMO, seems to withhold ship owners from increasing their number of orders for ships. Therefore, this research focuses on the shipbuilding sector and the impact these new regulations have on it. This paper will focus on the first part of this investigation; the creation of a newbuilding price and lead time models. After consideration of relevant literature, the general additive model (GAM) has been chosen and is applied both to the newbuilding price and the lead time as these two elements are seen to mutually influence each other. For the creation of these models, backward elimination was used resulting in a large number of variables tested and compared for relevance. The final results are promising, though the lead time will require further research to increase explanatory power.
Original language | English |
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Title of host publication | International Association of Maritime Economists Conference (IAME 2020) |
Subtitle of host publication | Sustainable Development of Shipping and Trade (online event) |
Publisher | Hong Kong Polytechnic University |
Number of pages | 19 |
Publication status | Published - 2020 |
Event | IAME 2020: Annual Conference of the International Association of Maritime Economists 2020 - Hong Kong, China Duration: 10 Jun 2020 → 12 Jun 2020 Conference number: 2020 https://www.polyu.edu.hk/fb/IAME2020/ |
Conference
Conference | IAME 2020: Annual Conference of the International Association of Maritime Economists 2020 |
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Abbreviated title | IAME |
Country/Territory | China |
City | Hong Kong |
Period | 10/06/20 → 12/06/20 |
Internet address |
Keywords
- general additive model
- Shipbuilding
- Dry bulk
- Maritime economics
- Price estimation
- Lead time estimation