 Bayesian Probability Revision and Infection Prevention Behavior in Japan: A Quantitative Analysis of the First Wave of COVID-19Shin Kinoshita, Masayuki Sato and Takanori Ida Discussion papers from Graduate School of Economics , Kyoto University 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 regarding the first wave of coronavirus disease 2019 (COVID-19) from February to May 2020 to investigate the impact of Bayesian probability inference, impact of cognitive biases of PCR test results on infection prevention behavior, and the discrepancy between infection prevention intentions and behaviors. The results showed that the higher probability responses, implying pessimism biases, were more likely to indicate that declaring a state of emergency was necessary and effective, and that they were more health oriented to ensure infection prevention behavior even at the expense of the economy. However, regarding actual behavioral change, it was found that even though they really wanted to reduce the frequency of their outings and the number of people they came in contact with, they actually did not reduce it. It was also found that those affected by pessimism biases showed higher WTP for the vaccine. Keywords: COVID-19; Bayesian inference; cognitive biases (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:kue:epaper:e-22-004 Access Statistics for this paper More papers in Discussion papers from Graduate School of Economics , Kyoto University Contact information at EDIRC. |
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