Working Paper: NBER ID: w28651
Authors: James Allen IV; Arlete Mahumane; James Riddell IV; Tanya Rosenblat; Dean Yang; Hang Yu
Abstract: Can informing people of high community support for social distancing encourage them to do more of it? In theory, the impact of such an intervention on social distancing is ambiguous, and depends on the relative magnitudes of free-riding and perceived-infectiousness effects. We randomly assigned a treatment providing information on true high rates of community social distancing support. 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. 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).
Keywords: COVID-19; social distancing; public health messaging; behavioral economics
JEL Codes: D91; I12; O12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Informing individuals about high community support for social distancing (Z13) | Increase in social distancing (F69) |
| Informing individuals about high community support for social distancing (Z13) | Decrease in social distancing (R12) |
| Local COVID-19 case rates (R23) | Heterogeneous impact of informing individuals about high community support for social distancing (C92) |
| Low current COVID-19 cases (I19) | Decrease in social distancing (R12) |
| High current COVID-19 cases (I19) | Increase in social distancing (F69) |