Hidden Bibliographic Details
| Other authors / contributors: | International Monetary Fund, issuing body.
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| ISBN: | 1513523236
9781513523231
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| Notes: | Includes bibliographical references.
Online resource; title from PDF title page (EBSCO, viewed February 13, 2020).
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| Summary: | 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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| Other form: | Print version: Arslanalp, Serkan. Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time. Washington, D.C. : International Monetary Fund, ©2019 9781513521121
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