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Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time
Author:
Mr. Serkan Arslanalp
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,
Mr. Marco Marini
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, and
Ms. Patrizia Tumbarello
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Series:
IMF Working Papers
Volume/Issue:
Volume 2019: Issue 275
Language:
English
Publication Date:
13 Dec 2019
DOI:
https://doi.org/10.5089/9781513521121.001
ISBN:
9781513521121
ISSN:
1018-5941
Pages:
34
Keywords:
WP; AIS data; trade statistics; cargo load indicator; trade activity; trade data; port call data; Trade balance; Trade in goods; Imports; Big data; Exports; Global; Europe
Legal-disclaimer:
IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
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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.
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Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund