{"title":"Bayesian probability revision and infection prevention behavior in Japan: A quantitative analysis of the first wave of COVID-19","authors":"Shin Kinoshita , Masayuki Sato , Takanori Ida","doi":"10.1016/j.rie.2024.100986","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":46094,"journal":{"name":"Research in Economics","volume":"78 4","pages":"Article 100986"},"PeriodicalIF":1.2000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research in Economics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1090944324000504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Established in 1947, Research in Economics is one of the oldest general-interest economics journals in the world and the main one among those based in Italy. The purpose of the journal is to select original theoretical and empirical articles that will have high impact on the debate in the social sciences; since 1947, it has published important research contributions on a wide range of topics. A summary of our editorial policy is this: the editors make a preliminary assessment of whether the results of a paper, if correct, are worth publishing. If so one of the associate editors reviews the paper: from the reviewer we expect to learn if the paper is understandable and coherent and - within reasonable bounds - the results are correct. We believe that long lags in publication and multiple demands for revision simply slow scientific progress. Our goal is to provide you a definitive answer within one month of submission. We give the editors one week to judge the overall contribution and if acceptable send your paper to an associate editor. We expect the associate editor to provide a more detailed evaluation within three weeks so that the editors can make a final decision before the month expires. In the (rare) case of a revision we allow four months and in the case of conditional acceptance we allow two months to submit the final version. In both cases we expect a cover letter explaining how you met the requirements. For conditional acceptance the editors will verify that the requirements were met. In the case of revision the original associate editor will do so. If the revision cannot be at least conditionally accepted it is rejected: there is no second revision.