IDEAS home Printed from https://ideas.repec.org/p/eti/dpaper/22065.html
   My bibliography  Save this paper

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

Author

Listed:
  • OTA Rui
  • ITO Arata
  • SATO Masahiro
  • YANO Makoto

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.

Suggested Citation

  • OTA Rui & ITO Arata & SATO Masahiro & YANO Makoto, 2022. "Social Learning and Behavioral Change When Faced with the COVID-19 Pandemic: A big data analysis," Discussion papers 22065, Research Institute of Economy, Trade and Industry (RIETI).
  • Handle: RePEc:eti:dpaper:22065
    as

    Download full text from publisher

    File URL: https://www.rieti.go.jp/jp/publications/dp/22e065.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Keane, Michael & Neal, Timothy, 2021. "Consumer panic in the COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 220(1), pages 86-105.
    2. Michiru Kaneda & So Kubota & Satoshi Tanaka, 2021. "Who spent their COVID-19 stimulus payment? Evidence from personal finance software in Japan," The Japanese Economic Review, Springer, vol. 72(3), pages 409-437, July.
    3. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    4. Ryo Takahashi & Kenta Tanaka, 2021. "Social punishment for breaching restrictions during the COVID‐19 pandemic," Economic Inquiry, Western Economic Association International, vol. 59(4), pages 1467-1482, October.
    5. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    6. Yoko Konishi & Takashi Saito & Toshiki Ishikawa & Hajime Kanai & Naoya Igei, 2021. "How Did Japan Cope with COVID-19? Big Data and Purchasing Behavior," Asian Economic Papers, MIT Press, vol. 20(1), pages 146-167, Winter/Sp.
    7. Christopher Hansman & Harrison Hong & Áureo de Paula & Vishal Singh, 2020. "A Sticky-Price View of Hoarding," NBER Working Papers 27051, National Bureau of Economic Research, Inc.
    8. Glenn W. Harrison & Morten I. Lau & Melonie B. Williams, 2002. "Estimating Individual Discount Rates in Denmark: A Field Experiment," American Economic Review, American Economic Association, vol. 92(5), pages 1606-1617, December.
    9. Quang Nguyen & Colin Camerer & Tomomi Tanaka, 2010. "Risk and Time Preferences Linking Experimental and Household Data from Vietnam," Post-Print halshs-00547090, HAL.
    10. Kureishi, Wataru & Paule-Paludkiewicz, Hannah & Tsujiyama, Hitoshi & Wakabayashi, Midori, 2021. "Time preferences over the life cycle and household saving puzzles," Journal of Monetary Economics, Elsevier, vol. 124(C), pages 123-139.
    11. Tomomi Tanaka & Colin F. Camerer & Quang Nguyen, 2010. "Risk and Time Preferences: Linking Experimental and Household Survey Data from Vietnam," American Economic Review, American Economic Association, vol. 100(1), pages 557-571, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zexuan Wang & Ismaël Rafaï & Marc Willinger, 2023. "Does age affect the relation between risk and time preferences? Evidence from a representative sample," Southern Economic Journal, John Wiley & Sons, vol. 90(2), pages 341-368, October.
    2. Yayan Hernuryadin & Koji Kotani & Tatsuyoshi Saijo, 2020. "Time Preferences of Food Producers: Does “Cultivate and Grow” Matter?," Land Economics, University of Wisconsin Press, vol. 96(1), pages 132-148.
    3. Meier, Stephan & Sprenger, Charles D., 2013. "Discounting financial literacy: Time preferences and participation in financial education programs," Journal of Economic Behavior & Organization, Elsevier, vol. 95(C), pages 159-174.
    4. Jonathan Chapman & Erik Snowberg & Stephanie Wang & Colin Camerer, 2018. "Loss Attitudes in the U.S. Population: Evidence from Dynamically Optimized Sequential Experimentation (DOSE)," NBER Working Papers 25072, National Bureau of Economic Research, Inc.
    5. Tristan Le Cotty & Elodie Maître d’Hôtel & Raphael Soubeyran & Julie Subervie, 2018. "Linking Risk Aversion, Time Preference and Fertiliser Use in Burkina Faso," Journal of Development Studies, Taylor & Francis Journals, vol. 54(11), pages 1991-2006, November.
    6. Jetter, Michael & Magnusson, Leandro M. & Roth, Sebastian, 2020. "Becoming sensitive: Males’ risk and time preferences after the 2008 financial crisis," European Economic Review, Elsevier, vol. 128(C).
    7. Arthur E. Attema & Han Bleichrodt & Olivier L’Haridon & Patrick Peretti-Watel & Valérie Seror, 2018. "Discounting health and money: New evidence using a more robust method," Journal of Risk and Uncertainty, Springer, vol. 56(2), pages 117-140, April.
    8. Michal Bauer & Julie Chytilová, 2010. "The Impact of Education on Subjective Discount Rate in Ugandan Villages," Economic Development and Cultural Change, University of Chicago Press, vol. 58(4), pages 643-669, July.
    9. Pablo Brañas-Garza & Diego Jorrat & Antonio M. Espín & Angel Sánchez, 2023. "Paid and hypothetical time preferences are the same: lab, field and online evidence," Experimental Economics, Springer;Economic Science Association, vol. 26(2), pages 412-434, April.
    10. Sawosri, Arieska Wening & Mußhoff, Oliver, 2020. "Risk and time preferences of farmers in India and Indonesia," EFForTS Discussion Paper Series 32, University of Goettingen, Collaborative Research Centre 990 "EFForTS, Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems (Sumatra, Indonesia)".
    11. Glenn W. Harrison & Morten I. Lau & Hong Il Yoo, 2020. "Risk Attitudes, Sample Selection, and Attrition in a Longitudinal Field Experiment," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 552-568, July.
    12. Tamás Csermely & Alexander Rabas, 2016. "How to reveal people’s preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 107-136, December.
    13. Olivier Toubia & Eric Johnson & Theodoros Evgeniou & Philippe Delquié, 2013. "Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters," Management Science, INFORMS, vol. 59(3), pages 613-640, June.
    14. Vásquez-Lavín, Felipe & Carrasco, Moisés & Barrientos, Manuel & Gelcich, Stefan & Ponce Oliva, Roberto D., 2021. "Estimating discount rates for environmental goods: Are People’s responses inadequate to frequency of payments?," Journal of Environmental Economics and Management, Elsevier, vol. 107(C).
    15. Jindrich Matousek & Tomas Havranek & Zuzana Irsova, 2022. "Individual discount rates: a meta-analysis of experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 318-358, February.
    16. Takeuchi, Kan, 2011. "Non-parametric test of time consistency: Present bias and future bias," Games and Economic Behavior, Elsevier, vol. 71(2), pages 456-478, March.
    17. Chi Wai Yu & Y. Jane Zhang & Sharon Xuejing Zuo, 2021. "Multiple Switching and Data Quality in the Multiple Price List," The Review of Economics and Statistics, MIT Press, vol. 103(1), pages 136-150, March.
    18. Thiago Scarelli & David N Margolis, 2022. "When You Can't Afford to Wait for a Job: The Role of Time Discounting for Own-Account Workers in Developing Countries," PSE Working Papers halshs-03288728, HAL.
    19. Pennesi, Daniele, 2021. "Intertemporal discrete choice," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 690-706.
    20. Jacopo Bonan & Philippe LeMay-Boucher & Douglas Scott, 2016. "Can Hypothetical Time Discounting Rates Predict Actual Behaviour: Evidence from a Randomized Experiment," Working Papers 2016.74, Fondazione Eni Enrico Mattei.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eti:dpaper:22065. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: TANIMOTO, Toko (email available below). General contact details of provider: https://edirc.repec.org/data/rietijp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.