Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approach
We employ a Bayesian Vector Autoregressive methodology, to counter the issue of data availability, and explore the relationship between seaborne commodity trade and freight rates. Our results show three important insights: first and foremost, the quantity of seaborne commodity trade has a strong imp...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-01-01
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| Series: | Maritime Transport Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666822X20300010 |
| _version_ | 1831752675804315648 |
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| author | Nektarios A. Michail Konstantinos D. Melas |
| author_facet | Nektarios A. Michail Konstantinos D. Melas |
| author_sort | Nektarios A. Michail |
| collection | DOAJ |
| description | We employ a Bayesian Vector Autoregressive methodology, to counter the issue of data availability, and explore the relationship between seaborne commodity trade and freight rates. Our results show three important insights: first and foremost, the quantity of seaborne commodity trade has a strong impact on the Baltic Dry Index and the Baltic Dirty Tanker Index, but not on the Baltic Clean Tanker Index, most likely due to the fact that clean tankers can simultaneously operate both in the clean and the dirty sectors. Second, a shock in the price of brent oil has the expected positive response from the Baltic Dry Index, while its relationship with the Baltic Clean Tanker Index and the Baltic Dirty Tanker Index is negative as, in this case, tanker vessels can operate as floating storage units. Third, a relationship between the freight indices appears to hold as a change in one could spill over to the other. |
| first_indexed | 2024-12-21T23:07:29Z |
| format | Article |
| id | doaj.art-d420f9c2af604cd5af8534d2356d0c80 |
| institution | Directory Open Access Journal |
| issn | 2666-822X |
| language | English |
| last_indexed | 2024-12-21T23:07:29Z |
| publishDate | 2020-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Maritime Transport Research |
| spelling | doaj.art-d420f9c2af604cd5af8534d2356d0c802022-12-21T18:47:07ZengElsevierMaritime Transport Research2666-822X2020-01-011100001Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approachNektarios A. Michail0Konstantinos D. Melas1Economic Analysis and Research Department, Central Bank of Cyprus, School of Economics and Business, Cyprus University of Technology, and Cyprus Centre for Business Research, Nicosia, CyprusFaculty of Business and Economics, Metropolitan College, 14, El. Venizelou, 546 24, Thessaloniki, Greece; Corresponding author.We employ a Bayesian Vector Autoregressive methodology, to counter the issue of data availability, and explore the relationship between seaborne commodity trade and freight rates. Our results show three important insights: first and foremost, the quantity of seaborne commodity trade has a strong impact on the Baltic Dry Index and the Baltic Dirty Tanker Index, but not on the Baltic Clean Tanker Index, most likely due to the fact that clean tankers can simultaneously operate both in the clean and the dirty sectors. Second, a shock in the price of brent oil has the expected positive response from the Baltic Dry Index, while its relationship with the Baltic Clean Tanker Index and the Baltic Dirty Tanker Index is negative as, in this case, tanker vessels can operate as floating storage units. Third, a relationship between the freight indices appears to hold as a change in one could spill over to the other.http://www.sciencedirect.com/science/article/pii/S2666822X20300010G11G12G17R41 |
| spellingShingle | Nektarios A. Michail Konstantinos D. Melas Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approach Maritime Transport Research G11 G12 G17 R41 |
| title | Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approach |
| title_full | Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approach |
| title_fullStr | Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approach |
| title_full_unstemmed | Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approach |
| title_short | Quantifying the relationship between seaborne trade and shipping freight rates: A Bayesian vector autoregressive approach |
| title_sort | quantifying the relationship between seaborne trade and shipping freight rates a bayesian vector autoregressive approach |
| topic | G11 G12 G17 R41 |
| url | http://www.sciencedirect.com/science/article/pii/S2666822X20300010 |
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