Trust Predicts Compliance With COVID-19 Containment Policies: Evidence from Ten Countries Using Big Data

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aut.relation.issue101412
aut.relation.journalEconomics and Human Biology
aut.relation.volume54
dc.contributor.authorSarracino, Francesco
dc.contributor.authorGreyling, Talita
dc.contributor.authorO'Connor, Kelsey
dc.contributor.authorPeroni, Chiara
dc.contributor.authorRossouw, Stephanie
dc.date.accessioned2024-08-09T03:13:20Z
dc.date.available2024-08-09T03:13:20Z
dc.date.issued2024-07-20
dc.description.abstractWe 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.
dc.identifier.citationEconomics and Human Biology, ISSN: 1570-677X (Print); 1873-6130 (Online), Elsevier, 54(101412). doi: 10.1016/j.ehb.2024.101412
dc.identifier.doi10.1016/j.ehb.2024.101412
dc.identifier.issn1570-677X
dc.identifier.issn1873-6130
dc.identifier.urihttp://hdl.handle.net/10292/17868
dc.publisherElsevier
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S1570677X24000649
dc.rights© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by nc/4.0/).
dc.rights.accessrightsOpenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subject1402 Applied Economics
dc.subjectGeneral Arts, Humanities & Social Sciences
dc.subject3801 Applied economics
dc.titleTrust Predicts Compliance With COVID-19 Containment Policies: Evidence from Ten Countries Using Big Data
dc.typeJournal Article
pubs.elements-id563038
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