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Social distancing and contagion in a discrete choice model of COVID-19

Author

Listed:
  • Baskozos, Giorgos

    (University of Oxford)

  • Galanis, Giorgos

    (Goldsmiths, University of London, Centre for Applied Macroeconomic Analysis, Australian National University and CRETA, University of Warwick)

  • Di Guilmi, Corrado

    (University of Technology Sydney, Australia; and Centre for Applied Macroeconomic Analysis, Australian National University)

Abstract

We present an epidemic model in which heterogenous agents choose whether to enact social distancing practices. The policy maker decides on the timing and the extent of policies that incentivise social distancing. We evaluate the consequences of interventions and find that: (i) the timing of intervention is paramount in slowing the contagion, and (ii) a delay cannot be compensated by stronger measures.

Suggested Citation

  • Baskozos, Giorgos & Galanis, Giorgos & Di Guilmi, Corrado, 2020. "Social distancing and contagion in a discrete choice model of COVID-19," CRETA Online Discussion Paper Series 57, Centre for Research in Economic Theory and its Applications CRETA.
    • Handle: RePEc:wrk:wcreta:57
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    References listed on IDEAS

    as
    1. Martin S Eichenbaum & Sergio Rebelo & Mathias Trabandt, 2021. "The Macroeconomics of Epidemics [Economic activity and the spread of viral diseases: Evidence from high frequency data]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    2. Andrew Atkeson, 2020. "What Will be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios," Staff Report 595, Federal Reserve Bank of Minneapolis.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, January.
    4. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    5. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
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    Cited by:

    1. Andrew Atkeson, 2020. "On Using SIR Models to Model Disease Scenarios for COVID-19," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 41(01), pages 1-35, June.
    2. Patrick Mellacher & Simon Plakolb, 2025. "Global Inequality in Vaccine Access, Mortality and Economy: An Agent-based Exploration," Graz Economics Papers 2025-12, University of Graz, Department of Economics.
    3. Cassandra Castle & Corrado Di Guilmi & Olena Stavrunova, 2021. "Individualism and Collectivism as predictors of compliance with COVID-19 public health safety expectations," Working Paper Series 2021/03, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    4. Domenico Delli Gatti & Severin Reissl & Enrico Turco, 2023. "V for vaccines and variants," Journal of Evolutionary Economics, Springer, vol. 33(4), pages 991-1046, September.
    5. Domenico Delli Gatti & Severin Reissl, 2020. "ABC: An Agent Based Exploration of the Macroeconomic Effects of Covid-19," CESifo Working Paper Series 8763, CESifo.
    6. Di Guilmi, Corrado & Galanis, Giorgos, 2021. "Convergence and divergence in dynamic voting with inequality," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 137-158.

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