IDEAS home Printed from https://ideas.repec.org/p/tcr/wpaper/e162.html
   My bibliography  Save this paper

Epidemics and Macroeconomic Dynamics

Author

Listed:
  • Masashige Hamano
  • Munechika Katayama

Abstract

We propose a novel SIR-macro model in which virus transmission is uncertain. The model is solved with the perturbation method around a deterministic infectious steady state. Assuming a stationary infection process, a positive infection shock increases infection while reducing consumption and hours worked for susceptible individuals. Further, we estimate our model with the recent US data on the COVID-19 outbreak. Historical decomposition obtained with Bayesian techniques finds that the dis-containment rule that encourages people to work more, as well as infection shock and technology shock, play an important role in characterizing US infection and macroeconomic dynamics.

Suggested Citation

  • Masashige Hamano & Munechika Katayama, 2021. "Epidemics and Macroeconomic Dynamics," Working Papers e162, Tokyo Center for Economic Research.
    • Handle: RePEc:tcr:wpaper:e162
    as

    Download full text from publisher

    File URL: https://www.tcer.or.jp/wp/pdf/e162.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dirk Krueger & Harald Uhlig & Taojun Xie, 2022. "Macroeconomic dynamics and reallocation in an epidemic: evaluating the ‘Swedish solution’," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 37(110), pages 341-398.
    2. Daisuke Fujii & Taisuke Nakata, 2021. "COVID-19 and output in Japan," The Japanese Economic Review, Springer, vol. 72(4), pages 609-650, October.
    3. Martin Bodenstein & Giancarlo Corsetti & Luca Guerrieri, 2022. "Social distancing and supply disruptions in a pandemic," Quantitative Economics, Econometric Society, vol. 13(2), pages 681-721, May.
    4. Fernández-Villaverde, Jesús & Arias, Jonas & Rubio-Ramírez, Juan Francisco & Shin, Minchul, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CEPR Discussion Papers 15951, C.E.P.R. Discussion Papers.
    5. Juillard, M., 2003. "Computing in economics and finance," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 1939-1939, September.
    6. Masashige Hamano & Munechika Katayama & So Kubota, 2020. "COVID-19 Misperception and Macroeconomy," Working Papers 2016, Waseda University, Faculty of Political Science and Economics.
    7. Dirk Kruger & Harald Uhlig & Taojun Xie, 2020. "Macroeconomic Dynamics and Reallocation in an Epidemic," Working Papers 2020-43, Becker Friedman Institute for Research In Economics.
    8. Michel Juillard, 2003. "What is the contribution of a k order approximation," Computing in Economics and Finance 2003 286, Society for Computational Economics.
    9. Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.
    10. Andrew T. Levin & Alexei Onatski & John Williams & Noah M. Williams, 2006. "Monetary Policy under Uncertainty in Micro-Founded Macroeconometric Models," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 229-312, National Bureau of Economic Research, Inc.
    11. Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    12. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
    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. Mitsuhiro Fukao & Etsuro Shioji, 2022. "Is There a Trade‐Off between COVID‐19 Control and Economic Activity? Implications from the Phillips Curve Debate," Asian Economic Policy Review, Japan Center for Economic Research, vol. 17(1), pages 66-85, January.

    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. David Baqaee & Emmanuel Farhi, 2020. "Nonlinear Production Networks with an Application to the Covid-19 Crisis," NBER Working Papers 27281, National Bureau of Economic Research, Inc.
    2. Lazebnik, Teddy & Shami, Labib & Bunimovich-Mendrazitsky, Svetlana, 2023. "Intervention policy influence on the effect of epidemiological crisis on industry-level production through input–output networks," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    3. Getachew, Yoseph, 2020. "Optimal social distancing in SIR based macroeconomic models," MERIT Working Papers 2020-034, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    4. Eichenbaum, Martin S. & Rebelo, Sergio & Trabandt, Mathias, 2022. "The macroeconomics of testing and quarantining," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    5. Garriga, Carlos & Manuelli, Rody & Sanghi, Siddhartha, 2022. "Optimal management of an epidemic: Lockdown, vaccine and value of life," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    6. David Baqaee & Emmanuel Farhi, 2022. "Supply and Demand in Disaggregated Keynesian Economies with an Application to the COVID-19 Crisis," American Economic Review, American Economic Association, vol. 112(5), pages 1397-1436, May.
    7. Pierluigi Balduzzi & Emanuele Brancati & Marco Brianti & Fabio Schiantarelli, 2020. "Credit Constraints anf Firms' Decisions: Evidence from the COVID-19 Outbreak Italian Firms’ Expectations and Plans," Boston College Working Papers in Economics 1013, Boston College Department of Economics, revised 07 Oct 2022.
    8. Saito, Yuta & Sakamoto, Jun, 2021. "Asset pricing during pandemic lockdown," Research in International Business and Finance, Elsevier, vol. 58(C).
    9. Balduzzi, Pierluigi & Brancati, Emanuele & Brianti, Marco & Schiantarelli, Fabio, 2020. "The Economic Effects of COVID-19 and Credit Constraints: Evidence from Italian Firms' Expectations and Plans," IZA Discussion Papers 13629, Institute of Labor Economics (IZA).
    10. Di Bartolomeo, Giovanni & D'Imperio, Paolo & Felici, Francesco, 2022. "The fiscal response to the Italian COVID-19 crisis: A counterfactual analysis," Journal of Macroeconomics, Elsevier, vol. 73(C).
    11. Acurio Vásconez, Verónica & Damette, Olivier & Shanafelt, David W., 2023. "Macroepidemics and unconventional monetary policy," Economic Modelling, Elsevier, vol. 126(C).
    12. 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.
    13. Croce, Mariano & Farroni, Paolo & Wolfskeil, Isabella, 2020. "When the Markets Get COVID: COntagion, Viruses, and Information Diffusion," CEPR Discussion Papers 14674, C.E.P.R. Discussion Papers.
    14. Yasushi Iwamoto, 2021. "Welfare economics of managing an epidemic: an exposition," The Japanese Economic Review, Springer, vol. 72(4), pages 537-579, October.
    15. Hosono, Kaoru, 2021. "Epidemic and Economic Consequences of Voluntary and Request-based Lockdowns in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 61(C).
    16. Yinon Bar-On & Tatiana Baron & Ofer Cornfeld & Eran Yashiv, 2023. "When to Lock, Not Whom: Managing Epidemics Using Time-Based Restrictions," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 292-321, December.
    17. Dizioli, Allan & Pinheiro, Roberto, 2021. "Information and inequality in the time of a pandemic," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    18. Shin Fukuda, 2023. "Impacts of the Substitutability of Consumption on Infection Dynamics," International Journal of Economics and Financial Issues, Econjournals, vol. 13(4), pages 8-14, July.
    19. Yinon Bar-On & Tatiana Baron & Ofer Cornfeld & Eran Yashiv, 2023. "When to Lock, Not Whom: Managing Epidemics Using Time-Based Restrictions," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 292-321, December.
    20. INOUE Tomoo & OKIMOTO Tatsuyoshi, 2022. "Exploring the Dynamic Relationship between Mobility and the Spread of COVID-19, and the Role of Vaccines," Discussion papers 22011, Research Institute of Economy, Trade and Industry (RIETI).

    More about this item

    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:tcr:wpaper:e162. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tctokjp.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.