Confounding, Spillovers and Interactions Influence Estimates of Social Distancing Policy Effects

Abstract

Social distancing policies have been widely used to curb the spread of infectious diseases such as COVID-19, but assessing their effectiveness is challenging. This study shows that widely-used methods to estimate the effects of such policies are highly sensitive to accounting, or failing to account, for the simultaneous adoption of policies and the presence of spillovers across geographies stemming from human movement. By estimating a series of nonparametric models on fine-grained mobility, epidemiological, and policy data from Mexico, this research shows that failing to consider confounders, interactions,and spillovers can change the magnitude and the sign of estimated policy effects, hampering the design of optimal public policies.

Keywords: Social distancing, policy design, spillovers, confounding, interactions

JEL Classification: I10, I18, C18, C23