Arbeitspapier

Key Links in Network Interactions: Assessing Route-specific Travel Restrictions in China during the Covid-19 Pandemic

We consider a model of network interactions where the outcome of a unit depends on the outcomes of the connected units. We determine the key network link, i.e., the network link whose removal results in the largest reduction in the aggregate outcomes, and provide a measure that quantifies the contribution of a network link to the aggregate outcomes, which complements the intercentrality measure of the key network node proposed by Ballester, Calv'o-Armengol, and Zenou (2006). We provide an example examining the spread of Covid-19 in China. Travel restrictions were imposed to limit the spread of infectious diseases. As uniform restrictions can be inefficient and incur unnecessarily high costs, we examine the design of restrictions that target specific travel routes. Our approach may be generalized to multiple countries to guide policies during epidemics ranging from ex ante route-specific travel restrictions to ex post health measures based on travel histories, and from the initial travel restrictions to the phased reopening.

Sprache
Englisch

Erschienen in
Series: GLO Discussion Paper ; No. 1030

Klassifikation
Wirtschaft
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Health: Government Policy; Regulation; Public Health
Network Formation and Analysis: Theory
State and Local Government: Health; Education; Welfare; Public Pensions
Thema
network interactions
key network links
Covid-19
transmission

Ereignis
Geistige Schöpfung
(wer)
Chen, Xi
Qiu, Yun
Shi, Wei
Yu, Pei
Ereignis
Veröffentlichung
(wer)
Global Labor Organization (GLO)
(wo)
Essen
(wann)
2022

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Chen, Xi
  • Qiu, Yun
  • Shi, Wei
  • Yu, Pei
  • Global Labor Organization (GLO)

Entstanden

  • 2022

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