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Spatial-SIR with Network Structure and Behavior: Lockdown Rules and the Lucas Critique

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  • Alberto Bisin
  • Andrea Moro

Abstract

We introduce a model of the diffusion of an epidemic with demographically heterogeneous agents interacting socially on a spatially structured network. Contagion-risk averse agents respond behaviorally to the diffusion of the infections by limiting their social interactions. Schools and workplaces also respond by allowing students and employees to attend and work remotely. The spatial structure induces local herd immunities along socio-demographic dimensions, which significantly affect the dynamics of infections. We study several non-pharmaceutical interventions; e.g., i) lockdown rules, which set thresholds on the spread of the infection for the closing and reopening of economic activities; ii) neighborhood lockdowns, leveraging granular (neighborhood-level) information to improve the effectiveness public health policies; iii) selective lockdowns, which restrict social interactions by location (in the network) and by the demographic characteristics of the agents. Substantiating a "Lucas critique" argument, we assess the cost of naive discretionary policies ignoring agents and firms' behavioral responses.

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  • Alberto Bisin & Andrea Moro, 2021. "Spatial-SIR with Network Structure and Behavior: Lockdown Rules and the Lucas Critique," Papers 2103.13789, arXiv.org, revised Apr 2022.
  • Handle: RePEc:arx:papers:2103.13789
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    Cited by:

    1. Giorgio Fabbri & Salvatore Federico & Davide Fiaschi & Fausto Gozzi, 2024. "Mobility decisions, economic dynamics and epidemic," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(1), pages 495-531, February.
    2. Pongou, Roland & Tchuente, Guy & Tondji, Jean-Baptiste, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," GLO Discussion Paper Series 957, Global Labor Organization (GLO).
    3. Eva F. Janssens & Robin L. Lumsdaine & Sebastiaan H.L.C.G. Vermeulen, 2022. "An Epidemiological Model of Economic Crisis Spread across Sectors in the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 885-919, June.
    4. Davide Bosco & Luca Portoghese, 2022. "On the Decentralized Implementation of Lockdown Policies," Working Papers 500, University of Milano-Bicocca, Department of Economics.
    5. Ascari, Guido & Colciago, Andrea & Silvestrini, Riccardo, 2023. "Business dynamism, sectoral reallocation and productivity in a pandemic," European Economic Review, Elsevier, vol. 156(C).
    6. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2023. "Optimal interventions in networks during a pandemic," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 847-883, April.
    7. Lorenzo Amir Nemati Fard & Michele Starnini & Michele Tizzoni, 2023. "Modeling adaptive forward-looking behavior in epidemics on networks," Papers 2301.04947, arXiv.org.
    8. Bisin, Alberto & Moro, Andrea, 2022. "JUE insight: Learning epidemiology by doing: The empirical implications of a Spatial-SIR model with behavioral responses," Journal of Urban Economics, Elsevier, vol. 127(C).
    9. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," Papers 2110.10230, arXiv.org.

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    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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