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Bayesian Probability Revision and Infection Prevention Behavior in Japan : A Quantitative Analysis of the First Wave of COVID-19

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  • Shin KINOSHITA
  • Masayuki SATO
  • Takanori IDA

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.

Suggested Citation

  • Shin KINOSHITA & Masayuki SATO & Takanori IDA, 2022. "Bayesian Probability Revision and Infection Prevention Behavior in Japan : A Quantitative Analysis of the First Wave of COVID-19," Discussion papers e-22-004, Graduate School of Economics , Kyoto University.
    • Handle: RePEc:kue:epaper:e-22-004
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    1. Campos-Mercade, Pol & Meier, Armando N. & Schneider, Florian H. & Wengström, Erik, 2021. "Prosociality predicts health behaviors during the COVID-19 pandemic," Journal of Public Economics, Elsevier, vol. 195(C).
    2. Sarah Dryhurst & Claudia R. Schneider & John Kerr & Alexandra L. J. Freeman & Gabriel Recchia & Anne Marthe van der Bles & David Spiegelhalter & Sander van der Linden, 2020. "Risk perceptions of COVID-19 around the world," Journal of Risk Research, Taylor & Francis Journals, vol. 23(7-8), pages 994-1006, August.
    3. James H. Stock, 2020. "Data Gaps and the Policy Response to the Novel Coronavirus," NBER Working Papers 26902, National Bureau of Economic Research, Inc.
    4. Gerd Gigerenzer, 1996. "The Psychology of Good Judgment," Medical Decision Making, , vol. 16(3), pages 273-280, August.
    5. John M. Barrios & Yael Hochberg, 2020. "Risk Perception Through the Lens of Politics in the Time of the COVID-19 Pandemic," NBER Working Papers 27008, National Bureau of Economic Research, Inc.
    6. David M. Grether, 1980. "Bayes Rule as a Descriptive Model: The Representativeness Heuristic," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(3), pages 537-557.
    7. repec:eee:jobhd is not listed on IDEAS
    8. Stephen M. Utych & Luke Fowler, 2020. "Age-based messaging strategies for communication about COVID-19," Journal of Behavioral Public Administration, Center for Experimental and Behavioral Public Administration, vol. 3(1).
    9. Manski, Charles F. & Molinari, Francesca, 2021. "Estimating the COVID-19 infection rate: Anatomy of an inference problem," Journal of Econometrics, Elsevier, vol. 220(1), pages 181-192.
    10. Cass R. Sunstein & Richard H. Thaler, 2003. "Libertarian paternalism is not an oxymoron," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 48(Jun).
    11. Liliana Cori & Fabrizio Bianchi & Ennio Cadum & Carmen Anthonj, 2020. "Risk Perception and COVID-19," IJERPH, MDPI, vol. 17(9), pages 1-6, April.
    12. Andrey Simonov & Szymon Sacher & Jean-Pierre Dube & Shirsho Biswas, 2020. "The Persuasive Effect of Fox News: Non-Compliance with Social Distancing During the COVID-19 Pandemic," Working Papers 2020-67, Becker Friedman Institute for Research In Economics.
    13. Arcadio A. Cerda & Leidy Y. García, 2021. "Willingness to Pay for a COVID-19 Vaccine," Applied Health Economics and Health Policy, Springer, vol. 19(3), pages 343-351, May.
    14. Daisuke Moriwaki & Soichiro Harada & Jiyan Schneider & Takahiro Hoshino, 2020. "Nudging Preventive Behaviors in COVID-19 Crisis: A Large Scale RCT using Smartphone Advertising," Keio-IES Discussion Paper Series 2020-021, Institute for Economics Studies, Keio University.
    15. Müller, Stephan & Rau, Holger A., 2021. "Economic preferences and compliance in the social stress test of the COVID-19 crisis," Journal of Public Economics, Elsevier, vol. 194(C).
    16. Shoji, Masahiro & Cato, Susumu & Iida, Takashi & Ishida, Kenji & Ito, Asei & McElwain, Kenneth, 2020. "COVID-19 and Social Distancing in the Absence of Legal Enforcement: Survey Evidence from Japan," MPRA Paper 100723, University Library of Munich, Germany.
    17. Ying Fan & A. Yeşim Orhun & Dana Turjeman, 2020. "Heterogeneous Actions, Beliefs, Constraints and Risk Tolerance During the COVID-19 Pandemic," NBER Working Papers 27211, National Bureau of Economic Research, Inc.
    18. Sasaki, Shusaku & Saito, Tomoya & Ohtake, Fumio, 2022. "Nudges for COVID-19 voluntary vaccination: How to explain peer information?," Social Science & Medicine, Elsevier, vol. 292(C).
    19. Jesper Akesson & Sam Ashworth-Hayes & Robert Hahn & Robert Metcalfe & Itzhak Rasooly, 2022. "Fatalism, beliefs, and behaviors during the COVID-19 pandemic," Journal of Risk and Uncertainty, Springer, vol. 64(2), pages 147-190, April.
    20. Latkin, Carl A. & Dayton, Lauren & Yi, Grace & Konstantopoulos, Arianna & Boodram, Basmattee, 2021. "Trust in a COVID-19 vaccine in the U.S.: A social-ecological perspective," Social Science & Medicine, Elsevier, vol. 270(C).
    21. Pedro Bordalo & Katherine B. Coffman & Nicola Gennaioli & Andrei Shleifer, 2020. "Older People are Less Pessimistic about the Health Risks of Covid-19," NBER Working Papers 27494, National Bureau of Economic Research, Inc.
    22. Macchi, Laura, 2000. "Partitive Formulation of Information in Probabilistic Problems: Beyond Heuristics and Frequency Format Explanations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 82(2), pages 217-236, July.
    23. J. S. Butler & Patrali Chatterjee, 1997. "Tests of the Specification of Univariate and Bivariate Ordered Probit," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 343-347, May.
    24. Yoshihiko Kadoya & Somtip Watanapongvanich & Pattaphol Yuktadatta & Pongpat Putthinun & Stella T. Lartey & Mostafa Saidur Rahim Khan, 2021. "Willing or Hesitant? A Socioeconomic Study on the Potential Acceptance of COVID-19 Vaccine in Japan," IJERPH, MDPI, vol. 18(9), pages 1-18, May.
    25. M. Kate Bundorf & Jill DeMatteis & Grant Miller & Maria Polyakova & Jialu L. Streeter & Jonathan Wivagg, 2021. "Risk Perceptions and Protective Behaviors: Evidence from COVID-19 Pandemic," NBER Working Papers 28741, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    COVID-19; Bayesian inference; cognitive biases;
    All these keywords.

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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