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A detailed method to estimate inter-regional capital flows using inter-firm transaction and person flow big data

Author

Listed:
  • Yuki Akiyama

    (The University of Tokyo)

  • Yohei Yamamoto

    (The University of Tokyo)

  • Ryosuke Shibasaki

    (The University of Tokyo)

  • Hodaka Kaneda

    (ZENRIN-Datacom CO., LTD)

Abstract

This study develops a method to estimate inter-regional capital flows in the real economy across Japan, which is important for understating the regional economy with as much detail as possible, and that existing censuses do not monitor adequately. The method can monitor spatial distributions of three kinds of capital flow: inter-firm transactions (F2F), firm-to-consumer flows as salaries (F2C), and consumer-to-firm flows as consumption behavior (C2F) using inter-firm transaction big data (IF data) and person flow big data (PF data). First, we estimated F2F using IF data that reports all capital flows between a company’s headquarters. Second, we estimate the home, work place, and consumption locations of all consumers using PF data collected by the auto-GPS function on mobile phones. Third, we estimate the F2C of each consumer by estimating their salaries based on the locations of firms in the IF data. Finally, we estimate the C2F of each consumption area by estimating the consumption of F2C in each consumption location. We develop a dataset that can monitor micro-scale capital flows across Japan. This study is one of the first attempts in any country to develop a dataset that can monitor the spatial distribution and time-series changes of nationwide capital flows at a very high-resolution scale. We expected that our data will contribute to policy-making to address the socioeconomic problems in the private sector and among local governments in Japan.

Suggested Citation

  • Yuki Akiyama & Yohei Yamamoto & Ryosuke Shibasaki & Hodaka Kaneda, 2020. "A detailed method to estimate inter-regional capital flows using inter-firm transaction and person flow big data," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 219-239, February.
  • Handle: RePEc:spr:apjors:v:4:y:2020:i:1:d:10.1007_s41685-019-00130-x
    DOI: 10.1007/s41685-019-00130-x
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    References listed on IDEAS

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    1. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    2. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
    3. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
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    More about this item

    Keywords

    Big data; Regional economy; Inter-regional capital flow; Inter-firm transaction; Mobile phone; Mass person flow;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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