IDEAS home Printed from https://ideas.repec.org/a/beh/jbepv1/v4y2020is3p77-86.html
   My bibliography  Save this article

What do we know, what we don't and what we cannot know so far about COVID-19: The case of Russia

Author

Listed:
  • Alexis Belianin

    (Higher School of Economics and IMEMO, Russian Academy of Sciences)

  • Alexander Shivarov

    (International College of Economics and Finance, Higher School of Economics)

Abstract

The paper surveys the Russian experience of COVID-19 pandemia over the two waves: April-May and October-December 2020. We discuss the implementation of the various policy measures, including hospital capacity buidling, quarantine restrictions and behavioral nudging, and compare their efficiency against social costs. The analysis of COVID-19 dynamics is much restricted by the quality of the available data, which remains poor for a number of medical, statistical and political reasons. We argue that exogenous sources, such as the number of internet search queries related to COVID and excess mortality over the previous year, provide a more impartial picture of the pandemia. Using panel data regression analysis, we find that both official COVID-19 casualties and excess mortality are correlated with internet queries and population density, but lower excess mortality only is also explained by the exogenous characteristics of healthcare system, such as the number of ambulance staff and mean duration of hospital treatment. We conclude that better information and more diversified health policies are needed to fight the pandemia and its consequences.

Suggested Citation

  • Alexis Belianin & Alexander Shivarov, 2020. "What do we know, what we don't and what we cannot know so far about COVID-19: The case of Russia," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 4(S3), pages 77-86, December.
    • Handle: RePEc:beh:jbepv1:v:4:y:2020:i:s3:p:77-86
    as

    Download full text from publisher

    File URL: http://sabeconomics.org/journal/RePEc/beh/JBEPv1/articles/JBEP-4-S3-6.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Farboodi, Maryam & Jarosch, Gregor & Shimer, Robert, 2021. "Internal and external effects of social distancing in a pandemic," Journal of Economic Theory, Elsevier, vol. 196(C).
    2. Christopher Avery & William Bossert & Adam Clark & Glenn Ellison & Sara Fisher Ellison, 2020. "Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists," NBER Working Papers 27007, National Bureau of Economic Research, Inc.
    3. 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).
    4. Christopher Avery & William Bossert & Adam Thomas Clark & Glenn Ellison & Sara Ellison, 2020. "Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists," CESifo Working Paper Series 8293, CESifo.
    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. Michelle Baddeley, 2020. "COVID-19 2020: A year of living dangerously," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 4(S3), pages 5-9, December.

    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. Daron Acemoglu & Victor Chernozhukov & Iván Werning & Michael D. Whinston, 2021. "Optimal Targeted Lockdowns in a Multigroup SIR Model," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 487-502, December.
    2. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    3. 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).
    4. Vandenbroucke Guillaume, 2022. "The Mechanics of Individually- and Socially-Optimal Decisions during an Epidemic," The B.E. Journal of Macroeconomics, De Gruyter, vol. 22(1), pages 131-158, January.
    5. Julliard, Christian & Shi, Ran & Yuan, Kathy, 2023. "The spread of COVID-19 in London: Network effects and optimal lockdowns," Journal of Econometrics, Elsevier, vol. 235(2), pages 2125-2154.
    6. 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.
    7. Álvaro H. Chaves Castro, 2021. "Análisis sobre la evolución del COVID-19 en Colombia: ¿se alcanzará el pico de contagio?," Tiempo y Economía, Universidad de Bogotá Jorge Tadeo Lozano, vol. 8(1), pages 123-160, January.
    8. Yashiv, Eran & Bar-On, Yinon & Baron, Tatiana & Milo, Ron, 2020. "Caveats for Economists: Epidemiology-Based Modelling of COVID19 and Model Misspecifications," CEPR Discussion Papers 15107, C.E.P.R. Discussion Papers.
    9. Jesper Akesson & Sam Ashworth-Hayes & Robert Hahn & Robert Metcalfe & Itzhak Rasooly, 2022. "Fatalism, beliefs, and behaviors during the COVID-19 pandemic," Journal of Risk and Uncertainty, Springer, vol. 64(2), pages 147-190, April.
    10. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
    11. Nicolò Gatti & Beatrice Retali, 2021. "Fighting the spread of Covid-19 : was the Swiss lockdown worth it?," IdEP Economic Papers 2101, USI Università della Svizzera italiana.
    12. Miguel Casares & Paul Gomme & Hashmat Khan, 2022. "COVID‐19 pandemic and economic scenarios for Ontario," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 503-539, February.
    13. David Baqaee & Emmanuel Farhi & Michael J. Mina & James H. Stock, 2020. "Reopening Scenarios," NBER Working Papers 27244, National Bureau of Economic Research, Inc.
    14. Chernozhukov, Victor & Kasahara, Hiroyuki & Schrimpf, Paul, 2021. "Causal impact of masks, policies, behavior on early covid-19 pandemic in the U.S," Journal of Econometrics, Elsevier, vol. 220(1), pages 23-62.
    15. Lee, Sokbae & Liao, Yuan & Seo, Myung Hwan & Shin, Youngki, 2021. "Sparse HP filter: Finding kinks in the COVID-19 contact rate," Journal of Econometrics, Elsevier, vol. 220(1), pages 158-180.
    16. Huberts, Nick F.D. & Thijssen, Jacco J.J., 2023. "Optimal timing of non-pharmaceutical interventions during an epidemic," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1366-1389.
    17. 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).
    18. Martin Forster & Emanuela Randon, 2020. "Epidemic policy under uncertainty and information," Discussion Papers 20/05, Department of Economics, University of York.
    19. Martin F. Quaas & Jasper N. Meya & Hanna Schenk & Björn Bos & Moritz A. Drupp & Till Requate, 2020. "The Social Cost of Contacts: Theory and Evidence for the Covid-19 Pandemic in Germany," CESifo Working Paper Series 8347, CESifo.
    20. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.

    More about this item

    Keywords

    COVID-19; excess mortality; medical statistics; internet queries; panel data;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

    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:beh:jbepv1:v:4:y:2020:i:s3:p:77-86. 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: SABE (email available below). General contact details of provider: https://edirc.repec.org/data/sabeeea.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.