Bayesian probability revision and infection prevention behavior in Japan: A quantitative analysis of the first wave of COVID-19

Shin Kinoshita, Masayuki Sato and Takanori Ida

Research in Economics, 2024, vol. 78, issue 4

Abstract: The relationship between cognitive biases and infection prevention behavior remains unexplored in the existing literature. This study uses data from a questionnaire survey conducted in Japan on the first wave of Coronavirus Disease 2019 (COVID-19) from February to May 2020 to empirically investigate the impact of Bayesian probability inference, the influence of cognitive biases of PCR test results on infection prevention behavior, and the discrepancy between infection prevention intentions and behaviors. We used a bivariate ordinal probit model when considering the correlation between behaviors. The results showed that the higher probability responses, implying pessimistic biases, were more likely to indicate that declaring a state of emergency was necessary and effective, and were more health-oriented in ensuring infection prevention behavior even at the expense of the economy. However, the study found that although they wanted to reduce the frequency of their outings and the number of people they met, they did not reduce them in terms of actual behavior change. It also found that those with pessimistic biases had a higher WTP for the vaccine.

Keywords: COVID-19; Bayesian inference; Cognitive biases; Bivariate ordinal probit model (search for similar items in EconPapers)
JEL-codes: C30 D91 I12 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1090944324000504
Full text for ScienceDirect subscribers only

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:eee:reecon:v:78:y:2024:i:4:s1090944324000504

DOI: 10.1016/j.rie.2024.100986

Access Statistics for this article

Research in Economics is currently edited by Federico Etro

More articles in Research in Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().