Correcting Misperceptions about Support for Social Distancing to Combat COVID-19.

IF 2 3区 经济学 Q1 AREA STUDIES Economic Development and Cultural Change Pub Date : 2024-10-01 Epub Date: 2024-09-09 DOI:10.1086/727192
James Allen, Arlete Mahumane, James Riddell, Tanya Rosenblat, Dean Yang, Hang Yu
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Abstract

Can informing people of high community support for social distancing encourage them to do more of it? We randomly assigned a treatment correcting individuals' underestimates of community support for social distancing. In theory, informing people that more neighbors support social distancing than expected encourages free-riding and lowers the perceived benefits from social distancing. At the same time, the treatment induces people to revise their beliefs about the infectiousness of COVID-19 upwards; this perceived infectiousness effect as well as the norm adherence effect increase the perceived benefits from social distancing. We estimate impacts on social distancing, measured using a combination of self-reports and reports of others. While experts surveyed in advance expected the treatment to increase social distancing, we find that its average effect is close to zero and significantly lower than expert predictions. However, the treatment's effect is heterogeneous, as predicted by theory: it decreases social distancing where current COVID-19 cases are low (where free-riding dominates), but increases it where cases are high (where the perceived-infectiousness effect dominates). These findings highlight that correcting misperceptions may have heterogeneous effects depending on disease prevalence.

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纠正对支持保持社交距离以抗击COVID-19的误解
我们设计并测试了一种干预措施,以纠正个人在COVID-19大流行期间对社区支持保持社交距离的低估。
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来源期刊
CiteScore
3.70
自引率
5.00%
发文量
75
期刊介绍: Economic Development and Cultural Change (EDCC) is an economic journal publishing studies that use modern theoretical and empirical approaches to examine both the determinants and the effects of various dimensions of economic development and cultural change. EDCC’s focus is on empirical papers with analytic underpinnings, concentrating on micro-level evidence, that use appropriate data to test theoretical models and explore policy impacts related to a broad range of topics relevant to economic development.
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