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Trust predicts compliance with COVID-19 containment policies: Evidence from ten countries using big data

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  • Sarracino, Francesco
  • Greyling, Talita
  • O'Connor, Kelsey J.
  • Peroni, Chiara
  • Rossouw, Stephanie

Abstract

We use Twitter, Google mobility, and Oxford policy data to study the relationship between trust and compliance over the period March 2020 to January 2021 in ten, mostly European, countries. Trust has been shown to be an important correlate of compliance with COVID-19 containment policies. However, the previous findings depend upon two assumptions: first, that compliance is time invariant, and second, that compliance can be measured using self reports or mobility measures alone. We relax these assumptions by calculating a new time-varying measure of compliance as the association between containment policies and people's mobility behavior. Additionally, we develop measures of trust in others and national institutions by applying emotion analysis to Twitter data. Results from various panel estimation techniques demonstrate that compliance changes over time and that increasing (decreasing) trust in others predicts increasing (decreasing) compliance. This evidence indicates that compliance changes over time, and further confirms the importance of cultivating trust in others.

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  • Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanie, 2024. "Trust predicts compliance with COVID-19 containment policies: Evidence from ten countries using big data," Economics & Human Biology, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:ehbiol:v:54:y:2024:i:c:s1570677x24000649
    DOI: 10.1016/j.ehb.2024.101412
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    Cited by:

    1. Greyling, Talita & Rossouw, Stephanié, 2024. "Vaccination uptake, happiness and emotions: using a supervised machine learning approach," GLO Discussion Paper Series 1482, Global Labor Organization (GLO).
    2. Rossouw, Stephanié & Greyling, Talita, 2022. "Collective emotions and macro-level shocks: COVID-19 vs the Ukrainian war," GLO Discussion Paper Series 1210, Global Labor Organization (GLO).
    3. Costa-Font, Joan & Vilaplana-Prieto, Cristina, 2023. "Trusting the health system and COVID 19 restriction compliance," LSE Research Online Documents on Economics 118267, London School of Economics and Political Science, LSE Library.
    4. Costa-Font, Joan & Vilaplana-Prieto, Cristina, 2023. "Trusting the Health System and COVID 19 Restriction Compliance," Economics & Human Biology, Elsevier, vol. 49(C).
    5. Sarracino, Francesco & Slater, Giulia, 2024. "The trust paradox," MPRA Paper 120053, University Library of Munich, Germany.
    6. Joan Costa-i-Font & Cristina Vilaplana-Prieto, 2023. "Health System Trust and Compliance with Covid-19 Restrictions," CESifo Working Paper Series 10291, CESifo.

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    More about this item

    Keywords

    compliance; COVID-19; trust; Big Data; Twitter;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management

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