IDEAS home Printed from https://ideas.repec.org/p/bir/birmec/20-17.html
   My bibliography  Save this paper

Learning or habit formation? Optimal timing of lockdown for disease containment

Author

Listed:
  • Siddhartha Bandyopadhyay

    (University of Birmingham)

  • Kalyan Chatterjee

    (Penn State University)

  • Kaustav Das

    (University of Leicester)

  • Jaideep Roy

    (University of Bath)

Abstract

We analyse a model where the government has to decide whether to impose a lockdown in a country to prevent the spread of a possibly virulent disease. If the government decides to impose a lockdown, it has to determine its intensity, timing and duration. We find that there are two competing effects that push the decision in either direction. An early lockdown is beneficial not only to slow down the spread of the disease, but to create beneficial habit formation (such as social distancing, developing hygienic habits) that persists even after the lockdown is lifted. Against that, an early lockdown in addition to damaging the economy, leads to a loss of information and impedes learning about the nature and the dynamics of the disease. Based on the prior probability of the disease being virulent, we characterise the timing, intensity and duration of a lockdown with the above mentioned tradeoffs. Specifically, we show that as the precision of learning goes up, a government tends to delay the imposition of lockdown. Conversely, if the habit formation parameter is very strong, a government is likely to impose an early lockdown.

Suggested Citation

  • Siddhartha Bandyopadhyay & Kalyan Chatterjee & Kaustav Das & Jaideep Roy, 2020. "Learning or habit formation? Optimal timing of lockdown for disease containment," Discussion Papers 20-17, Department of Economics, University of Birmingham.
  • Handle: RePEc:bir:birmec:20-17
    as

    Download full text from publisher

    File URL: https://repec.cal.bham.ac.uk/pdf/20-17.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Miclo, Laurent & Weibull, Jörgen W. & Spiro, Daniel, 2020. "Optimal epidemic suppression under an ICU constraint," TSE Working Papers 20-1111, Toulouse School of Economics (TSE).
    2. Ichino, Andrea & Favero, Carlo A. & Rustichini, Aldo, 2020. "Restarting the economy while saving lives under Covid-19," CEPR Discussion Papers 14664, C.E.P.R. Discussion Papers.
    3. Aditya Goenka & Lin Liu, 2020. "Infectious diseases, human capital and economic growth," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 70(1), pages 1-47, July.
    4. Fernando Alvarez & David Argente, 2020. "A Simple Planning Problem for COVID-19 Lockdown," Working Papers 2020-34, Becker Friedman Institute for Research In Economics.
    5. Jean‐Paul Chavas & Céline Nauges, 2020. "Uncertainty, Learning, and Technology Adoption in Agriculture," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 42-53, March.
    6. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    7. Raouf Boucekkine & Rodolphe Desbordes & Hélène Latzer, 2009. "How do epidemics induce behavioral changes?," Journal of Economic Growth, Springer, vol. 14(3), pages 233-264, September.
    8. Chakraborty, Shankha & Papageorgiou, Chris & Pérez Sebastián, Fidel, 2010. "Diseases, infection dynamics, and development," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 859-872, October.
    9. Luiz Brotherhood & Philipp Kircher & Cezar Santos & Michèle Tertilt, 2020. "An Economic Model of the Covid-19 Epidemic: The Importance of Testing and Age-Specific Policies," CESifo Working Paper Series 8316, CESifo.
    10. Alwyn Young, 2005. "The Gift of the Dying: The Tragedy of AIDS and the Welfare of Future African Generations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(2), pages 423-466.
    11. Flavio Toxvaerd, 2019. "Rational Disinhibition And Externalities In Prevention," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(4), pages 1737-1755, November.
    12. Goenka, Aditya & Liu, Lin & Nguyen, Manh-Hung, 2014. "Infectious diseases and economic growth," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 34-53.
    13. Aditya Goenka & Lin Liu, 2012. "Infectious diseases and endogenous fluctuations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 50(1), pages 125-149, May.
    14. Christian Gollier, 2020. "Pandemic economics: optimal dynamic confinement under uncertainty and learning," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 45(2), pages 80-93, September.
    15. Alexander E. Saak & David A. Hennessy, 2018. "A model of reporting and controlling outbreaks by public health agencies," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 66(1), pages 21-64, July.
    16. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michèle, 2020. "An economic model of the Covid-19 epidemic: The importance of testing and age-specific policies," CEPR Discussion Papers 14695, C.E.P.R. Discussion Papers.
    17. Bhattacharya, Sudipto & Chatterjee, Kalyan & Samuelson, Larry, 1986. "Sequential Research and the Adoption of Innovations," Oxford Economic Papers, Oxford University Press, vol. 38(0), pages 219-243, Suppl. No.
    18. Robert S. Pindyck, 2020. "COVID-19 and the Welfare Effects of Reducing Contagion," NBER Working Papers 27121, National Bureau of Economic Research, Inc.
    19. Laurent Miclo & Daniel Spiro & Jörgen Weibull, 2020. "Optimal epidemic suppression under an ICU constraint ," Working Papers hal-02563023, HAL.
    20. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michèle, 2020. "An economic model of the Covid-19 epidemic: The importance of testing and age-specific policies," CEPR Discussion Papers 14695, C.E.P.R. Discussion Papers.
    21. Geoffard, Pierre-Yves & Philipson, Tomas, 1996. "Rational Epidemics and Their Public Control," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 37(3), pages 603-624, August.
    22. Jensen, Richard, 1982. "Adoption and diffusion of an innovation of uncertain profitability," Journal of Economic Theory, Elsevier, vol. 27(1), pages 182-193, June.
    23. Daron Acemoglu & Victor Chernozhukov & Ivàn Werning & Michael D. Whinston, 2020. "A Multi-Risk SIR Model with Optimally Targeted Lockdown," CeMMAP working papers CWP14/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Elena Gubar & Laura Policardo & Edgar J. Sanchez Carrera & Vladislav Taynitskiy, 2021. "Optimal Lockdown Policies driven by Socioeconomic Costs," Papers 2105.08349, arXiv.org.
    2. 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.
    3. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bandyopadhyay, Siddhartha & Chatterjee, Kalyan & Das, Kaustav & Roy, Jaideep, 2021. "Learning versus habit formation: Optimal timing of lockdown for disease containment," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    2. David E. Bloom & Michael Kuhn & Klaus Prettner, 2022. "Modern Infectious Diseases: Macroeconomic Impacts and Policy Responses," Journal of Economic Literature, American Economic Association, vol. 60(1), pages 85-131, March.
    3. Christian Gollier, 2020. "Cost–benefit analysis of age‐specific deconfinement strategies," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 22(6), pages 1746-1771, December.
    4. Christian Gollier, 2020. "Pandemic economics: optimal dynamic confinement under uncertainty and learning," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 45(2), pages 80-93, September.
    5. Christian Gollier, 2020. "If the Objective is Herd Immunity, on Whom Should it be Built?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 671-683, August.
    6. Goenka, Aditya & Liu, Lin & Nguyen, Manh-Hung, 2021. "SIR economic epidemiological models with disease induced mortality," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    7. Guimarães, Luís, 2021. "Antibody tests: They are more important than we thought," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    8. La Torre, Davide & Liuzzi, Danilo & Marsiglio, Simone, 2021. "Epidemics and macroeconomic outcomes: Social distancing intensity and duration," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    9. Aditya Goenka & Lin Liu & Manh-Hung Nguyen, 2020. "Modeling optimal quarantines under infectious disease related mortality," Working Papers 202025, University of Liverpool, Department of Economics.
    10. So Kubota, 2021. "The macroeconomics of COVID-19 exit strategy: the case of Japan," The Japanese Economic Review, Springer, vol. 72(4), pages 651-682, October.
    11. d’Albis, Hippolyte & Augeraud-Véron, Emmanuelle, 2021. "Optimal prevention and elimination of infectious diseases," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    12. Alberto Bisin & Andrea Moro, 2020. "Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses," NBER Working Papers 27590, National Bureau of Economic Research, Inc.
    13. Timo Boppart & Karl Harmenberg & John Hassler & Per Krusell & Jonna Olsson, 2020. "Integrated Epi-Econ Assessment," NBER Working Papers 28282, National Bureau of Economic Research, Inc.
    14. Brotherhood, Luiz & Jerbashian, Vahagn, 2023. "Firm behavior during an epidemic," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    15. Aditya Goenka & Lin Liu & Manh-Hung Nguyen, 2021. "Modeling optimal quarantines with waning immunity," Discussion Papers 21-10, Department of Economics, University of Birmingham.
    16. 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).
    17. Baril-Tremblay, Dominique & Marlats, Chantal & Ménager, Lucie, 2021. "Self-isolation," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    18. Daron Acemoglu & Victor Chernozhukov & Ivàn Werning & Michael D. Whinston, 2020. "A Multi-Risk SIR Model with Optimally Targeted Lockdown," CeMMAP working papers CWP14/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Raouf Boucekkine & Shankha Chakraborty & Aditya Goenka & Lin Liu, 2024. "A Brief Tour of Economic Epidemiology Modelling," LIDAM Discussion Papers IRES 2024002, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    20. Luca Gori & Cristiana Mammana & Piero Manfredi & Elisabetta Michetti, 2022. "Economic development with deadly communicable diseases and public prevention," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 912-943, October.

    More about this item

    Keywords

    COVID-19; Lockdown; Learning; Habit formation.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I10 - Health, Education, and Welfare - - Health - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bir:birmec:20-17. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oleksandr Talavera (email available below). General contact details of provider: https://edirc.repec.org/data/debhauk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.