Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time /
Vessel traffic data based on the Automatic Identification System (AIS) is a big data source for nowcasting trade activity in real time. Using Malta as a benchmark, we develop indicators of trade and maritime activity based on AIS-based port calls. We test the quality of these indicators by comparing...
| Main Author: | |
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| Other Authors: | , |
| Format: | Book |
| Language: | English |
| Published: |
Washington, D.C. :
International Monetary Fund,
2019
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| Series: | IMF Working Papers; Working Paper ;
No. 2019/275 IMF eLibrary |
| Subjects: |
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| 100 | 1 | |a Arslanalp, Serkan | |
| 245 | 1 | 0 | |a Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time / |c Serkan Arslanalp, Marco Marini, Patrizia Tumbarello |
| 264 | 1 | |a Washington, D.C. : |b International Monetary Fund, |c 2019 | |
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| 500 | |a Part of the IMF eLibrary collection | ||
| 506 | |a Restricted for use by site license. | ||
| 520 | 3 | |a Vessel traffic data based on the Automatic Identification System (AIS) is a big data source for nowcasting trade activity in real time. Using Malta as a benchmark, we develop indicators of trade and maritime activity based on AIS-based port calls. We test the quality of these indicators by comparing them with official statistics on trade and maritime statistics. If the challenges associated with port call data are overcome through appropriate filtering techniques, we show that these emerging "big data" on vessel traffic could allow statistical agencies to complement existing data sources on trade and introduce new statistics that are more timely (real time), offering an innovative way to measure trade activity. That, in turn, could facilitate faster detection of turning points in economic activity. The approach could be extended to create a real-time worldwide indicator of global trade activity | |
| 588 | |a Description based on print version record | ||
| 650 | 7 | |a Balance of trade |2 imf | |
| 650 | 7 | |a Big data |2 imf | |
| 650 | 7 | |a Data capture & analysis |2 imf | |
| 650 | 7 | |a Empirical Studies of Trade |2 imf | |
| 650 | 7 | |a Exports and Imports |2 imf | |
| 650 | 7 | |a Exports |2 imf | |
| 650 | 7 | |a Imports |2 imf | |
| 650 | 7 | |a Information Management |2 imf | |
| 650 | 7 | |a International economics |2 imf | |
| 650 | 7 | |a International trade |2 imf | |
| 650 | 7 | |a Large Data Sets: Modeling and Analysis |2 imf | |
| 650 | 7 | |a Retail and Wholesale Trade |2 imf | |
| 650 | 7 | |a Technology |2 imf | |
| 650 | 7 | |a Trade balance |2 imf | |
| 650 | 7 | |a Trade in goods |2 imf | |
| 650 | 7 | |a Trade: General |2 imf | |
| 650 | 7 | |a e-Commerce |2 imf | |
| 651 | 7 | |a Malta |2 imf | |
| 700 | 1 | |a Marini, Marco | |
| 700 | 1 | |a Tumbarello, Patrizia | |
| 776 | 0 | 8 | |i Print Version: |a Arslanalp, Serkan |t Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time |d Washington, D.C. : International Monetary Fund, 2019. |z 9781513523224 |
| 830 | 0 | |a IMF Working Papers; Working Paper ; |v No. 2019/275 | |
| 830 | 0 | |a IMF eLibrary | |
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