Working Paper: NBER ID: w27121
Authors: Robert S. Pindyck
Abstract: I use a simple SIR model, augmented to include deaths, to elucidate how pandemic progression is affected by the control of contagion, and examine the key trade-offs that underlie policy design. I illustrate how the cost of reducing the "reproduction number" R0 depends on how it changes the infection rate, the total and incremental number of deaths, the duration of the pandemic, and the possibility and impact of a second wave. Reducing R0 reduces the number of deaths, but extends the duration (and hence economic cost) of the pandemic, and it increases the fraction of the population still susceptible at the end, raising the possibility of a second wave. The benefit of reducing R0 is largely lives saved, and the incremental number of lives saved rises as R0 is reduced. But using a VSL estimate to value those lives is problematic.
Keywords: COVID-19; Welfare Effects; Contagion; Social Distancing; Epidemiological Model
JEL Codes: C02; H12; I10
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| reproduction number (R0) (C59) | total number of deaths (d) (J11) |
| reproduction number (R0) (C59) | number of susceptible individuals (s) (C20) |
| reproduction number (R0) (C59) | maximum fraction of the population that becomes infected (imax) (J11) |
| reproduction number (R0) (C59) | duration of the pandemic (C41) |
| total number of deaths (d) (J11) | economic cost (D61) |