IDEAS home Printed from https://ideas.repec.org/a/wly/iecrev/v65y2024i1p3-42.html
   My bibliography  Save this article

Four Stylized Facts About Covid‐19

Author

Listed:
  • Andrew G. Atkeson
  • Karen A. Kopecky
  • Tao Zha

Abstract

We develop a Bayesian method for estimating the dynamics of COVID‐19 deaths and discover four key findings that expose the limitations of current structural epidemiological models . (i) Death growth rates declined rapidly from high levels during the initial 30 days of the epidemic worldwide. (ii) After this initial period, these rates fluctuated substantially around 0%. (iii) The cross‐location standard deviation of death growth rates decreased rapidly in the first 10 days but remained high afterward. (iv) These insights apply to both effective reproduction numbers and their cross‐location variability through epidemiological models. Our method is applicable to studying other epidemics.

Suggested Citation

  • Andrew G. Atkeson & Karen A. Kopecky & Tao Zha, 2024. "Four Stylized Facts About Covid‐19," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(1), pages 3-42, February.
    • Handle: RePEc:wly:iecrev:v:65:y:2024:i:1:p:3-42
    DOI: 10.1111/iere.12660
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/iere.12660
    Download Restriction: no
    File URL: https://libkey.io/10.1111/iere.12660?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Askitas, Nikos & Tatsiramos, Konstantinos & Verheyden, Bertrand, 2020. "Lockdown Strategies, Mobility Patterns and COVID-19," IZA Discussion Papers 13293, Institute of Labor Economics (IZA).
    2. Björn Bornkamp & Katja Ickstadt, 2009. "Bayesian Nonparametric Estimation of Continuous Monotone Functions with Applications to Dose–Response Analysis," Biometrics, The International Biometric Society, vol. 65(1), pages 198-205, March.
    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. Karl M. Aspelund & Michael C. Droste & James H. Stock & Christopher D. Walker, 2020. "Identification and Estimation of Undetected COVID-19 Cases Using Testing Data from Iceland," NBER Working Papers 27528, National Bureau of Economic Research, Inc.
    5. T Déirdre Hollingsworth & Don Klinkenberg & Hans Heesterbeek & Roy M Anderson, 2011. "Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-11, February.
    6. Edward L. Glaeser & Caitlin S. Gorback & Stephen J. Redding, 2020. "How Much Does COVID-19 Increase with Mobility? Evidence from New York and Four Other U.S. Cities," Working Papers 2020-22, Princeton University. Economics Department..
    7. Mr. Pragyan Deb & Davide Furceri & Mr. Jonathan David Ostry & Nour Tawk, 2020. "The Effect of Containment Measures on the COVID-19 Pandemic," IMF Working Papers 2020/159, International Monetary Fund.
    8. 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.
    9. 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).
    10. Pablo D. Fajgelbaum & Amit Khandelwal & Wookun Kim & Cristiano Mantovani & Edouard Schaal, 2021. "Optimal Lockdown in a Commuting Network," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 503-522, December.
    11. Thomas S. Shively & Thomas W. Sager & Stephen G. Walker, 2009. "A Bayesian approach to non‐parametric monotone function estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 159-175, January.
    12. Fang, Hanming & Wang, Long & Yang, Yang, 2020. "Human mobility restrictions and the spread of the Novel Coronavirus (2019-nCoV) in China," Journal of Public Economics, Elsevier, vol. 191(C).
    13. Veronica Guerrieri & Guido Lorenzoni & Ludwig Straub & Iván Werning, 2022. "Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?," American Economic Review, American Economic Association, vol. 112(5), pages 1437-1474, May.
    14. Sumedha Gupta & Thuy D. Nguyen & Felipe Lozano Rojas & Shyam Raman & Byungkyu Lee & Ana Bento & Kosali I. Simon & Coady Wing, 2020. "Tracking Public and Private Responses to the COVID-19 Epidemic: Evidence from State and Local Government Actions," NBER Working Papers 27027, National Bureau of Economic Research, Inc.
    15. Andrew Atkeson & Karen Kopecky & Tao Zha, 2020. "Estimating and Forecasting Disease Scenarios for COVID-19 with an SIR Model," NBER Working Papers 27335, National Bureau of Economic Research, Inc.
    16. Ewout Frankema, 2020. "Christopher B. Barrett, Michael R. Carter, and Jean‐Paul Chavas, eds., The economics of poverty traps, National Bureau of Economic Research Conference Report (Chicago and London: University of Chicago," Economic History Review, Economic History Society, vol. 73(2), pages 619-620, May.
    17. Toxvaerd, F.M.O, 2020. "Equilibrium Social Distancing," Cambridge Working Papers in Economics 2021, Faculty of Economics, University of Cambridge.
    18. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    19. Bisin, Alberto & Moro, Andrea, 2020. "Learning Epidemiology by Doing: The Empirical Implications of a Spatial SIR Model with Behavioral Responses," MPRA Paper 101059, University Library of Munich, Germany.
    20. Christopher J. Cronin & William N. Evans, 2020. "Private Precaution and Public Restrictions: What Drives Social Distancing and Industry Foot Traffic in the COVID-19 Era?," NBER Working Papers 27531, National Bureau of Economic Research, Inc.
    21. Goolsbee, Austan & Syverson, Chad, 2021. "Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020," Journal of Public Economics, Elsevier, vol. 193(C).
    22. Solomon Hsiang & Daniel Allen & Sébastien Annan-Phan & Kendon Bell & Ian Bolliger & Trinetta Chong & Hannah Druckenmiller & Luna Yue Huang & Andrew Hultgren & Emma Krasovich & Peiley Lau & Jaecheol Le, 2020. "The effect of large-scale anti-contagion policies on the COVID-19 pandemic," Nature, Nature, vol. 584(7820), pages 262-267, August.
    23. 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).
    24. 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.
    25. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. Andrew G. Atkeson & Karen Kopecky & Tao Zha, 2021. "Behavior and the Transmission of COVID-19," AEA Papers and Proceedings, American Economic Association, vol. 111, pages 356-360, May.
    3. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    4. Anand Chopra & Michael B. Devereux & Amartya Lahiri, 2022. "Pandemics through the lens of occupations," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 540-580, February.
    5. Xiao Chen & Hanwei Huang & Jiandong Ju & Ruoyan Sun & Jialiang Zhang, 2022. "Endogenous cross-region human mobility and pandemics," CEP Discussion Papers dp1860, Centre for Economic Performance, LSE.
    6. 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.
    7. Yasushi Iwamoto, 2021. "Welfare economics of managing an epidemic: an exposition," The Japanese Economic Review, Springer, vol. 72(4), pages 537-579, October.
    8. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    9. Nicola Borri & Francesco Drago & Chiara Santantonio & Francesco Sobbrio, 2021. "The “Great Lockdown”: Inactive workers and mortality by Covid‐19," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2367-2382, September.
    10. 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).
    11. Mitman, Kurt & Hanley, Douglas & Bognanni, Mark & Kolliner, Daniel, 2020. "Economics and Epidemics: Evidence from an Estimated Spatial Econ-SIR Model," CEPR Discussion Papers 15310, C.E.P.R. Discussion Papers.
    12. Glover, Andrew & Heathcote, Jonathan & Krueger, Dirk & Ríos-Rull, José-Víctor, 2023. "Health versus wealth: On the distributional effects of controlling a pandemic," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 34-59.
    13. Brinkman, Jeffrey & Mangum, Kyle, 2022. "JUE Insight: The Geography of Travel Behavior in the Early Phase of the COVID-19 Pandemic," Journal of Urban Economics, Elsevier, vol. 127(C).
    14. Giannone, Elisa & Paixão, Nuno & Pang, Xinle, 2022. "JUE Insight: The geography of pandemic containment," Journal of Urban Economics, Elsevier, vol. 127(C).
    15. Bisin, Alberto & Moro, Andrea, 2022. "Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 370-388.
    16. Dirk Niepelt & Mart n Gonzalez-Eiras, 2020. "Optimally Controlling an Epidemic," Diskussionsschriften dp2019, Universitaet Bern, Departement Volkswirtschaft.
    17. Elisa Giannone & Nuno Paixao & Xinle Pang, 2021. "The Geography of Pandemic Containment," Staff Working Papers 21-26, Bank of Canada.
    18. Dirk Krueger & Harald Uhlig & Taojun Xie, 2020. "Macroeconomic Dynamics and Reallocation in an Epidemic," PIER Working Paper Archive 20-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    19. Pol Antràs & Stephen J. Redding & Esteban Rossi-Hansberg, 2023. "Globalization and Pandemics," American Economic Review, American Economic Association, vol. 113(4), pages 939-981, April.
    20. Mauro Caselli & Andrea Fracasso & Sergio Scicchitano, 2022. "From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(4), pages 1517-1550, October.

    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • I1 - Health, Education, and Welfare - - Health

    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:wly:iecrev:v:65:y:2024:i:1:p:3-42. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.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.