Working Paper: CEPR ID: DP14658
Authors: Francesco Lippi; Fernando Alvarez; David Argente
Abstract: We study the optimal lockdown policy for a planner who controls the fatalities of a pandemic while minimizing the output costs of the lockdown. The policy depends on the fraction of infected and susceptible in the population, prescribing a severe lockdown beginning two weeks after the outbreak, covering 60% of the population after a month, and gradually withdrawing to 20% of the population after 3 months. The intensity of the optimal lockdown depends on the gradient of the fatality rate with respect to the infected, and the availability of antibody testing that yields a welfare gain of 2% of GDP.
Keywords: lockdown; quarantine; epidemic control; dynamic programming
JEL Codes: I10; I18; C61
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| severe lockdown (H77) | minimized fatalities (H84) |
| fraction of infected individuals (I12) | fatalities (J17) |
| availability of antibody testing (C12) | welfare gain (D69) |
| value of statistical life (J17) | optimal lockdown duration and intensity (C41) |
| higher fatality rate (I12) | necessity for stringent lockdown measures (H12) |
| constant fatality rate (J17) | reduction or elimination of lockdowns (F69) |