[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/p/cam/camdae/20102.html
   My bibliography  Save this paper

Matching Theory and Evidence on Covid-19 using a Stochastic Network SIR Model

Author

Listed:
  • Pesaran, M. H.
  • Yang, C. F.
Abstract
This paper develops an individual-based stochastic network SIR model for the empirical analysis of the Covid-19 pandemic. It derives moment conditions for the number of infected and active cases for single as well as multigroup epidemic models. These moment conditions are used to investigate identification and estimation of recovery and transmission rates. The paper then proposes simple moment-based rolling estimates and shows them to be fairly robust to the well-known under-reporting of infected cases. Empirical evidence on six European countries match the simulated outcomes, once the under-reporting of infected cases is addressed. It is estimated that the number of reported cases could be between 3 to 9 times lower than the actual numbers. Counterfactual analysis using calibrated models for Germany and UK show that early intervention in managing the infection is critical in bringing down the reproduction numbers below unity in a timely manner.

Suggested Citation

  • Pesaran, M. H. & Yang, C. F., 2020. "Matching Theory and Evidence on Covid-19 using a Stochastic Network SIR Model," Cambridge Working Papers in Economics 20102, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:20102
    Note: mhp1
    as

    Download full text from publisher

    File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe20102.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2021. "COVID-19 Time-Varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing," Globalization Institute Working Papers 407, Federal Reserve Bank of Dallas.
    2. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2020. "Voluntary and Mandatory Social Distancing: Evidence on COVID-19 Exposure Rates from Chinese Provinces and Selected Countries," NBER Working Papers 27039, National Bureau of Economic Research, Inc.
    3. Mohammad Akbarpour & Cody Cook & Aude Marzuoli & Simon Mongey & Abhishek Nagaraj & Matteo Saccarola & Pietro Tebaldi & Shoshana Vasserman & Hanbin Yang, 2020. "Socioeconomic Network Heterogeneity and Pandemic Policy Response," NBER Working Papers 27374, National Bureau of Economic Research, Inc.
    4. Alexis Akira Toda, 2020. "Susceptible-Infected-Recovered (SIR) Dynamics of COVID-19 and Economic Impact," Papers 2003.11221, arXiv.org, revised Mar 2020.
    5. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
    6. 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.
    7. 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).
    8. Christian Gourieroux & Joann Jasiak, 2020. "Analysis of Virus Transmission: A Stochastic Transition Model Representation of Epidemiological Models," Annals of Economics and Statistics, GENES, issue 140, pages 1-26.
    9. Sean Elliott & Christian Gourieroux, 2020. "Uncertainty on the Reproduction Ratio in the SIR Model," Papers 2012.11542, arXiv.org.
    10. 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.
    11. Joël Mossong & Niel Hens & Mark Jit & Philippe Beutels & Kari Auranen & Rafael Mikolajczyk & Marco Massari & Stefania Salmaso & Gianpaolo Scalia Tomba & Jacco Wallinga & Janneke Heijne & Malgorzata Sa, 2008. "Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases," PLOS Medicine, Public Library of Science, vol. 5(3), pages 1-1, March.
    12. Sean ELLIOTT & Christian GOURIEROUX, 2020. "Uncertainty on the Reproduction Ratio in the SIR Model," Working Papers 2020-31, Center for Research in Economics and Statistics.
    13. Ji, Chunyan & Jiang, Daqing & Shi, Ningzhong, 2011. "Multigroup SIR epidemic model with stochastic perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(10), pages 1747-1762.
    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. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CESifo Working Paper Series 8977, CESifo.
    2. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2023. "Social Distancing, Vaccination and Evolution of COVID-19 Transmission Rates in Europe," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 474-508, June.
    3. Ida Johnsson & M. Hashem Pesaran & Cynthia Fan Yang, 2023. "Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 across U.S. States and Selected Countries," CESifo Working Paper Series 10659, CESifo.
    4. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
    5. Toru Kitagawa & Guanyi Wang, 2021. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP28/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. 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).
    7. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2021. "COVID-19 Time-Varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing," Globalization Institute Working Papers 407, Federal Reserve Bank of Dallas.
    8. Toru Kitagawa & Guanyi Wang, 2020. "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network," Papers 2012.04055, arXiv.org, revised Jul 2021.
    9. Jonas E. Arias & Jesús Fernández-Villaverde & Juan Rubio Ramírez & Minchul Shin, 2021. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," NBER Working Papers 28617, National Bureau of Economic Research, Inc.
    10. 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.
    11. Toru Kitagawa & Guanyi Wang, 2020. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP59/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Park, Dojoon & Kang, Yong Joo & Eom, Young Ho, 2024. "Asset pricing tests for pandemic risk," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1314-1334.

    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. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2023. "Social Distancing, Vaccination and Evolution of COVID-19 Transmission Rates in Europe," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 474-508, June.
    2. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2021. "COVID-19 Time-Varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing," Globalization Institute Working Papers 407, Federal Reserve Bank of Dallas.
    3. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
    4. 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.
    5. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CESifo Working Paper Series 8977, CESifo.
    6. Jonas E. Arias & Jesús Fernández-Villaverde & Juan Rubio Ramírez & Minchul Shin, 2021. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," NBER Working Papers 28617, National Bureau of Economic Research, Inc.
    7. 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.
    8. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    9. Yasushi Iwamoto, 2021. "Welfare economics of managing an epidemic: an exposition," The Japanese Economic Review, Springer, vol. 72(4), pages 537-579, October.
    10. Janiak, Alexandre & Machado, Caio & Turén, Javier, 2021. "Covid-19 contagion, economic activity and business reopening protocols," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 264-284.
    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. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michele, 2024. "Optimal Age-based Policies for Pandemics: An Economic Analysis of Covid-19 and Beyond," LIDAM Discussion Papers CORE 2024012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Hornstein Andreas, 2022. "Quarantine, Contact Tracing, and Testing: Implications of an Augmented SEIR Model," The B.E. Journal of Macroeconomics, De Gruyter, vol. 22(1), pages 53-88, January.
    14. Sewon Hur, 2023. "The Distributional Effects Of Covid‐19 And Optimal Mitigation Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(1), pages 261-294, February.
    15. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
    16. Leonardo Bursztyn & Aakaash Rao & Christopher Roth & David Yanagizawa-Drott, 2023. "Opinions as Facts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(4), pages 1832-1864.
    17. 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.
    18. Bursztyn, Leonardo & Rao, Akaash & Roth, Christopher & Yanagizawa-Drott, David, 2020. "Misinformation during a Pandemic," The Warwick Economics Research Paper Series (TWERPS) 1274, University of Warwick, Department of Economics.
    19. Jacek Rothert & Ryan Brady & Michael Insler, 2020. "The Fragmented United States of America: The impact of scattered lock-down policies on country-wide infections," Departmental Working Papers 65, United States Naval Academy Department of Economics.
    20. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.

    More about this item

    Keywords

    Covid-19; multigroup SIR model; basic and effective reproduction numbers; rolling window estimates of the transmission rate; method of moments; calibration and counterfactual analysis;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J18 - Labor and Demographic Economics - - Demographic Economics - - - Public Policy

    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:cam:camdae:20102. 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: Jake Dyer (email available below). General contact details of provider: https://www.econ.cam.ac.uk/ .

    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.