Data and Code for Optimal Lockdown in a Commuting Network

Principal Investigator(s):  View help for Principal Investigator(s) Pablo Fajgelbaum, Princeton; Amit Khandelwal, Columbia GSB; Wookun Kim, Southern Methodist University; Cristiano Mantovani, Universitat Pompeu Fabra; Edouard Schaal, CREI

Version:  View help for Version V1

Name File Type Size Last Modified
  Covid 02/03/2021 04:26:PM
  KOR_adm2 02/03/2021 04:26:PM
  Seoul_CCD 02/03/2021 04:26:PM
  Seoul_Metro_Transaction 02/03/2021 04:27:PM
KOR_map.cpg text/plain 5 bytes 02/03/2021 11:07:AM
KOR_map.dbf application/octet-stream 21.1 KB 02/03/2021 11:07:AM
KOR_map.prj text/plain 145 bytes 02/03/2021 11:07:AM
KOR_map.shp application/octet-stream 20.5 MB 02/03/2021 11:07:AM
KOR_map.shx application/octet-stream 2.1 KB 02/03/2021 11:07:AM
NTS_1.csv text/csv 7.7 KB 02/03/2021 11:07:AM

Project Description

Summary:  View help for Summary
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
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Scope of Project

Subject Terms:  View help for Subject Terms commuting; covid; lockdown; network; economic geography; Seoul; Daegu; new york metropolitan area
JEL Classification:  View help for JEL Classification
      C60 Mathematical Methods; Programming Models; Mathematical and Simulation Modeling: General
      R38 Production Analysis and Firm Location: Government Policy
      R40 Transportation Economics: General
Geographic Coverage:  View help for Geographic Coverage Daegu, South Korea, Seoul, South Korea, New York Metropolitan Area, USA
Universe:  View help for Universe Districts in Seoul and Daegu, South Korea; Counties in New York Metropolitan Area, USA 
Data Type(s):  View help for Data Type(s) aggregate data; geographic information system (GIS) data; observational data; program source code

Methodology

Data Source:  View help for Data Source All the data sources are cited in the readme.
Unit(s) of Observation:  View help for Unit(s) of Observation Counties, USA, Districts, South Korea

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Published Versions

V1 [2021-11-23]

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