Using Supply Chain Network Information and High-frequency Mobility Data to Forecast Firm Dynamics

Author Name KATO Rui (Sumitomo Mitsui Finance and Leasing Co., Ltd.) / MIYAKAWA Daisuke (Waseda University) / YANAOKA Masaki (Tokyo Shoko Research, Ltd.) / YUKIMOTO Shinji (Sumitomo Mitsui Finance and Leasing Co., Ltd.)
Creation Date/NO. January 2024 24-J-005
Research Project Firm Dynamics, Industry, and Macroeconomy
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The use of GPS location data is increasingly common in recent years. In this paper, we use individual-level GPS location data to measure the size of factory-level populations and to forecast the leasing demand of the transaction partners of the companies for which the factory-level population is measured. First, we use GPS location data to measure changes in the population at the main factories of companies in the manufacturing industry. Second, using such measured data and their lease contract data, we construct a machine learning-based prediction model of leasing demand within the company’s suppliers. Except for the periods when corporate activities were greatly disturbed by the COVID-19 pandemic, the use of the GPS location data improves the prediction power of the leasing demand.