| Author Name | KONISHI Yoko (Senior Fellow, RIETI) / SAITO Takashi (Consulting Fellow, RIETI) / IGEI Naoya (INTAGE Research, Inc.) / MIYASHITA Yutaka (INTAGE, Inc.) / YAMAMOTO Naoto (INTAGE, Inc.) |
|---|---|
| Creation Date/NO. | August 2023 23-J-028 |
| Research Project | New Indicator Development and Economic Analysis using Big Data: Service industrie |
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Abstract
This paper documents the daily lives of Japanese residents during the three-year period (2020-2022) of the COVID-19 pandemic using Consumption Big Data. We use retail store sales (POS) covering 344 items, including food, beverage, infection prevention, and household goods data from about 6,000 stores nationwide, including supermarkets, convenience stores, home centers/discount stores, drug stores, and specialty stores. By looking at changes in the ranking of sales value, we were able to identify increases and decreases in sales by item, as well as items that are related to the pandemic. We also confirmed that the sales by item follow Zipf's law. Furthermore, we clustered the weekly series of sales from before the pandemic by their characteristics and observed changes in purchasing patterns and seasonality based on their classification.
