Working Paper: NBER ID: w27441
Authors: Pablo Fajgelbaum; Amit Khandelwal; Wookun Kim; Cristiano Mantovani; Edouard Schaal
Abstract: We study optimal dynamic lockdowns against Covid-19 within a commuting network. Our framework integrates canonical spatial epidemiology and trade models, and is applied to cities with varying initial viral spread: Seoul, Daegu and NYC-Metro. Spatial lockdowns achieve substantially smaller income losses than uniform lockdowns. In NYM and Daegu—with large initial shocks—the optimal lockdown restricts inflows to central districts before gradual relaxation, while in Seoul it imposes low temporal but large spatial variation. Actual commuting reductions were too weak in central locations in Daegu and NYM, and too strong across Seoul.
Keywords: COVID-19; lockdown; commuting networks; spatial epidemiology; trade models
JEL Codes: C6; R38; R4
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| spatial lockdowns (R32) | lower income losses (J17) |
| high virus diffusion potential (O33) | stricter initial lockdowns (E65) |
| optimal lockdowns by destination of commuting flows (R41) | nearly as efficient as fully flexible benchmarks (H21) |
| actual commuting reductions (R41) | larger-than-necessary economic losses (F69) |