TY - BOOK ID - 69246837 TI - Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time AU - Arslanalp, Serkan. AU - Marini, Marco. AU - Tumbarello, Patrizia. PY - 2019 SN - 1513521128 1513523236 1513523228 PB - Washington, D.C. : International Monetary Fund, DB - UniCat KW - Exports and Imports KW - Information Management KW - Empirical Studies of Trade KW - Trade: General KW - Retail and Wholesale Trade KW - e-Commerce KW - Large Data Sets: Modeling and Analysis KW - International economics KW - Data capture & analysis KW - Trade balance KW - Trade in goods KW - Imports KW - Big data KW - Exports KW - International trade KW - Technology KW - Balance of trade KW - Malta KW - E-Commerce UR - https://www.unicat.be/uniCat?func=search&query=sysid:69246837 AB - 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. ER -