Selection Bias in Voluntary Random Testing: Evidence from a COVID-19 Antibody Study

Abstract

We use data from a serological study that experimentally varied financial incentives for participation to detect and characterize selection bias. Participants are from neighborhoods with substantially lower COVID-19 risks. Existing methods to account for the resulting selection bias produce wide bounds or estimates that are inconsistent with the population. One explanation for these inconsistent estimates is that the underlying methods presume a single dimension of unobserved heterogeneity. The data suggest that there are two types of nonparticipants with opposing selection patterns. Allowing for these different types may lead to better accounting for selection bias.