Working Paper: CEPR ID: DP14923
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 combines 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, and are not easily approximated by simple centrality-based rules. 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 responses were too weak in central locations in Daegu and NYM, and too strong across Seoul.
Keywords: COVID-19; lockdown; commuting; optimal policy; general equilibrium
JEL Codes: R38; R4; C6
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| spatial lockdowns (R32) | smaller income losses (J17) |
| optimal lockdown strategy (C61) | varies based on initial viral spread (C59) |
| commuting responses (R41) | misalignment with optimal strategies (L21) |
| optimal lockdowns (C61) | eliminate prepandemic inflows (F69) |
| spatial targeting (R32) | lower income losses (J17) |
| optimal spatial targeting (R32) | smaller real income losses (F61) |