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1.
J Risk Uncertain ; 64(2): 147-190, 2022.
Article in English | MEDLINE | ID: covidwho-2248479

ABSTRACT

Little is known about how people's beliefs concerning the Coronavirus Disease 2019 (COVID-19) influence their behavior. To shed light on this, we conduct an online experiment ( n = 3 , 610 ) with US and UK residents. Participants are randomly allocated to a control group or to one of two treatment groups. The treatment groups are shown upper- or lower-bound expert estimates of the infectiousness of the virus. We present three main empirical findings. First, individuals dramatically overestimate the dangerousness and infectiousness of COVID-19 relative to expert opinion. Second, providing people with expert information partially corrects their beliefs about the virus. Third, the more infectious people believe that COVID-19 is, the less willing they are to take protective measures, a finding we dub the "fatalism effect". We develop a formal model that can explain the fatalism effect and discuss its implications for optimal policy during the pandemic.

2.
Journal of risk and uncertainty ; : 1-44, 2022.
Article in English | EuropePMC | ID: covidwho-1876734

ABSTRACT

Little is known about how people’s beliefs concerning the Coronavirus Disease 2019 (COVID-19) influence their behavior. To shed light on this, we conduct an online experiment (

3.
National Bureau of Economic Research Working Paper Series ; No. 27245, 2020.
Article in English | NBER | ID: grc-748332

ABSTRACT

Little is known about how people’s beliefs concerning the Coronavirus Disease 2019 (COVID-19) influence their behavior. To shed light on this, we conduct an online experiment (n = 3,610) with US and UK residents. Participants are randomly allocated to a control group or to one of two treatment groups. The treatment groups are shown upperor lower-bound expert estimates of the infectiousness of the virus. We present three main empirical findings. First, individuals dramatically overestimate the dangerousness and infectiousness of COVID-19 relative to expert opinion. Second, providing people with expert information partially corrects their beliefs about the virus. Third, the more infectious people believe that COVID-19 is, the less willing they are to take protective measures, a finding we dub the “fatalism effect”. We develop a formal model that can explain the fatalism effect and discuss its implications for optimal policy during the pandemic.

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