EconPapers    
Economics at your fingertips  
 

Social Learning and Behavioral Change When Faced with the COVID-19 Pandemic: A big data analysis

Rui Ota, Arata Ito, Masahiro Sato and Makoto Yano

Discussion papers from Research Institute of Economy, Trade and Industry (RIETI)

Abstract: At the beginning of the COVID-19 outbreak, knowledge about the disease and its prevention was scarce. For example, there was no scientific evidence that masks could prevent the disease. However, masks were rapidly purchased in large quantities in Japan, resulting in a severe shortage after late January 2020. The purpose of this paper is to clarify what factors caused this change in people's behavior toward infection prevention. To this end, we employ high-resolution consumer panel data and newspaper articles nationally or locally published in Japan to empirically analyze the impact of consumers' information reception on their mask purchasing behavior. Logistic regression results demonstrate that the cumulative number of articles was significantly related to the frequency of mask purchases with respect to any period of the first wave of infections. We found that early information in a pandemic is important and that learning from public information, or social learning, can significantly induce behavioral change.

Pages: 39 pages
Date: 2022-07
New Economics Papers: this item is included in nep-big and nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.rieti.go.jp/jp/publications/dp/22e065.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eti:dpaper:22065

Access Statistics for this paper

More papers in Discussion papers from Research Institute of Economy, Trade and Industry (RIETI) Contact information at EDIRC.
Bibliographic data for series maintained by TANIMOTO, Toko ().

 
Page updated 2025-03-22
Handle: RePEc:eti:dpaper:22065