Working Paper: CEPR ID: DP14613
Authors: Facundo Piguillem; Liyan Shi
Abstract: We study quantitatively the optimality of quarantine and testing policies; and whether they are complements or substitutes. We extend the epidemiological SEIR model incorporating an information friction. Our main finding is that testing is a cost-efficient substitute for lockdowns, rendering them almost unnecessary. By identifying carriers, testing contains the spread of the virus without reducing output. Although the implementation requires widespread massive testing. As a byproduct, we show that two distinct optimal lockdown policy types arise: suppression, intended to eliminate the virus, and mitigation, concerned about flattening the curve. The choice between them is determined by a "hope for the cure" effect, arising due to either an expected vaccine or the belief that the virus can be eliminated. Conditional on the policy type, the intensity and duration are invariant to the welfare function's shape: they depend mostly on the virus dynamics.
Keywords: COVID-19; optimal quarantine; optimal testing; welfare; cost of quarantines
JEL Codes: E1; E65; H12; I1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| testing (C90) | spread of the virus (F65) |
| testing (C90) | lockdowns (H76) |
| critical mass of infected individuals (C92) | effectiveness of testing (C52) |
| critical mass of infected individuals (C92) | effectiveness of lockdown measures (F68) |
| virus dynamics (C69) | lockdown policy type (H56) |