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A Nowcasting Model of Exports Using Maritime Big Data

December 23, 2022
Kakuho Furukawa*1
Ryohei Hisano*2


We nowcast Japan's exports using maritime big data (the Automatic Identification System data), which contains information on vessels such as their locations. The data has been only relatively rarely used for capturing economic trends. In doing so, we improve the accuracy of nowcasts by utilizing official statistics such as geographical data on ports and machine learning techniques. The analysis shows that the nowcasting model augmented with AIS data improves the performance of nowcasting relative to existing statistics (provisional reports on the Trade Statistics of Japan) that is available in close to real-time. In particular, the nowcasting model developed in this paper follows the movements of exports reasonably well even when they increase or decrease significantly (e.g., when the pandemic began in the spring of 2020 and when the supply chain was disrupted around mid-2021).

JEL Classification
C49, C55, E27

Nowcasting, Alternative data, AIS data, Exports

The authors thank Kosuke Aoki, Ichiro Fukunaga, Yoshihiko Hogen, Yosuke Kido, Yoshiyasu Koide, Teppei Nagano, Jouchi Nakajima, Tomoyuki Yagi, and staff members of the Bank of Japan for their valuable comments. All remaining errors are our own. The views expressed in this paper are those of the authors and do not necessarily reflect the official views of the Bank of Japan.

  1. *1Research and Statistics Department, Bank of Japan
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  2. *2The University of Tokyo
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