02061cas a2200265 a 4500 AALejournalIMF016065 230101c9999 xx r poo 0 0eng d 5.00 USD 9781513521121 1018-5941 BD-DhAAL BD-DhAAL Arslanalp, Serkan. Big Data on Vessel Traffic : Nowcasting Trade Flows in Real Time / Serkan Arslanalp, Marco Marini, Patrizia Tumbarello. Washington, D.C. : International Monetary Fund, 2019. 1 online resource (34 pages) IMF Working Papers <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required Electronic access restricted to authorized BRAC University faculty, staff and students 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. Mode of access: Internet Marini, Marco. Tumbarello, Patrizia. IMF Working Papers; Working Paper ; No. 2019/275 Full text available on IMF http://elibrary.imf.org/view/journals/001/2019/275/001.2019.issue-275-en.xml IMF e-Library