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Nowcasting Economic Activity with Mobility Data

March 12, 2021
Kohei Matsumura*1
Yusuke Oh*2
Tomohiro Sugo*3
Koji Takahashi*4

Abstract

In this paper, we develop high frequency indexes to measure sales in service industries and production activity in the manufacturing industry by using GPS mobility data from mobile applications. First, focusing on the possibility that the number of customers in service industries can be estimated using mobility data, we develop indicators to capture economic activity in amusement parks, shopping centers, and food services. We show that using GPS mobility data, it is possible to nowcast economic activity in the service industries, in real time, with a high level of precision-something which conventional statistics are largely unable to assist. In addition, by using statistical methods such as clustering, we can construct an indicator with even better nowcasting performance. Second, in the manufacturing sector we identify the locations of relatively large factories using panel data from the Economic Census for Business Activity and by utilizing hourly and daily mobility patterns such as a daytime ratio. We then construct indicators for nowcasting production based on the population in the specified areas. We find that we can nowcast production with a high level of precision for some labor-intensive industries including the transportation equipment and production machinery industries. These results suggest that mobility data are a useful tool for nowcasting macroeconomic activity.

JEL classification
C49, E23, E27

Keywords
mobility data, nowcasting, clustering

The authors are grateful to Seisaku Kameda, Kenji Sakuta, Takuji Kawamoto, Kenichi Sakura, Kazushige Kamiyama, Jouchi Nakajima, Tomoyuki Iida and participants of the Big Data forum co-hosted by the University of Tokyo Center for Advanced Research in Finance and the Bank of Japan Research and Statistics Department, for helpful comments and discussions. Any remaining errors are ours. 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
    E-mail : kouhei.matsumura@boj.or.jp
  2. *2Research and Statistics Department, Bank of Japan
    E-mail : yuusuke.ou@boj.or.jp
  3. *3Research and Statistics Department, Bank of Japan
    E-mail : tomohiro.sugou@boj.or.jp
  4. *4Research and Statistics Department, Bank of Japan
    E-mail : kouji.takahashi-2@boj.or.jp

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