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COVID‐19 severity: A new approach to quantifying global cases and deaths

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  • Daniel L. Millimet
  • Christopher F. Parmeter

Abstract

As the COVID‐19 pandemic has progressed, so too has the recognition that cases and deaths have been underreported, perhaps vastly so. Here, we present an econometric strategy to estimate the true number of COVID‐19 cases and deaths for 61 and 56 countries, respectively, from 1 January 2020 to 3 November 2020. Specifically, we estimate a ‘structural’ model based on the SIR epidemiological model extended to incorporate underreporting. The results indicate significant underreporting by magnitudes that align with existing research and conjectures by public health experts. While our approach requires some strong assumptions, these assumptions are very different from the equally strong assumptions required by other approaches addressing underreporting in the assessment of the extent of the pandemic. Thus, we view our approach as a complement to existing methods.

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  • Daniel L. Millimet & Christopher F. Parmeter, 2022. "COVID‐19 severity: A new approach to quantifying global cases and deaths," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
  • Handle: RePEc:bla:jorssa:v:185:y:2022:i:3:p:1178-1215
    DOI: 10.1111/rssa.12826
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    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. Manski, Charles F. & Molinari, Francesca, 2021. "Estimating the COVID-19 infection rate: Anatomy of an inference problem," Journal of Econometrics, Elsevier, vol. 220(1), pages 181-192.
    3. Papadopoulos, Alecos & Parmeter, Christopher F., 2021. "Type II failure and specification testing in the Stochastic Frontier Model," European Journal of Operational Research, Elsevier, vol. 293(3), pages 990-1001.
    4. Hai-Anh H. Dang & Trong-Anh Trinh, 2022. "The Beneficial Impacts of COVID-19 Lockdowns on Air Pollution: Evidence from Vietnam," Journal of Development Studies, Taylor & Francis Journals, vol. 58(10), pages 1917-1933, October.
    5. Oguzoglu, Umut, 2020. "COVID-19 Lockdowns and Decline in Traffic Related Deaths and Injuries," IZA Discussion Papers 13278, Institute of Labor Economics (IZA).
    6. Rebucci, Alessandro & Chudik, Alexander & Pesaran, M. Hashem, 2020. "Voluntary and Mandatory Social Distancing: Evidence on COVID-19 Exposure Rates from Chinese Provinces and Selected Countries," CEPR Discussion Papers 14646, C.E.P.R. Discussion Papers.
    7. Oleg Badunenko & Daniel J. Henderson & Subal C. Kumbhakar, 2012. "When, where and how to perform efficiency estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(4), pages 863-892, October.
    8. Hortaçsu, Ali & Liu, Jiarui & Schwieg, Timothy, 2021. "Estimating the fraction of unreported infections in epidemics with a known epicenter: An application to COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 106-129.
    9. Francisco Arroyo-Marioli & Francisco Bullano & Simas Kucinskas & Carlos Rondón-Moreno, 2021. "Tracking R of COVID-19: A new real-time estimation using the Kalman filter," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-16, January.
    10. Andreas Backhaus, 2020. "Common Pitfalls in the Interpretation of COVID-19 Data and Statistics," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 55(3), pages 162-166, May.
    11. Fetzer, Thiemo & Graeber, Thomas, 2020. "Does Contact Tracing Work? Quasi-Experimental Evidence from an Excel Error in England," CEPR Discussion Papers 15494, C.E.P.R. Discussion Papers.
    12. Marc F. Bellemare & Casey J. Wichman, 2020. "Elasticities and the Inverse Hyperbolic Sine Transformation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(1), pages 50-61, February.
    13. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    14. Andrew Atkeson, 2020. "How Deadly is COVID-19? Understanding the Difficulties with Estimation of its Fatality Rate," Staff Report 598, Federal Reserve Bank of Minneapolis.
    15. Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2021. "Local mortality estimates during the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1189-1217, October.
    16. Subal Kumbhakar & Roar Amundsveen & Hilde Kvile & Gudbrand Lien, 2015. "Scale economies, technical change and efficiency in Norwegian electricity distribution, 1998–2010," Journal of Productivity Analysis, Springer, vol. 43(3), pages 295-305, June.
    17. Ryan P. Badman & Yunxin Wu & Keigo Inukai & Rei Akaishi, 2021. "Blessing or Curse of Democracy?: Current Evidence from the Covid-19 Pandemic," Papers 2105.10865, arXiv.org.
    18. Goolsbee, Austan & Syverson, Chad, 2021. "Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020," Journal of Public Economics, Elsevier, vol. 193(C).
    19. Thiemo Fetzer & Thomas Graeber, 2021. "Measuring the scientific effectiveness of contact tracing: Evidence from a natural experiment," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(33), pages 2100814118-, August.
    20. Domenico Depalo, 2021. "True COVID-19 mortality rates from administrative data," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 253-274, January.
    21. Stephen R. Barnes & Louis‐Philippe Beland & Jason Huh & Dongwoo Kim, 2022. "COVID‐19 lockdown and traffic accidents: Lessons from the pandemic," Contemporary Economic Policy, Western Economic Association International, vol. 40(2), pages 349-368, April.
    22. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    23. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
    24. Sa, Filipa, 2020. "Socioeconomic Determinants of COVID-19 Infections and Mortality: Evidence from England and Wales," IZA Policy Papers 159, Institute of Labor Economics (IZA).
    25. 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.
    26. Christopher Avery & William Bossert & Adam Clark & Glenn Ellison & Sara Fisher Ellison, 2020. "An Economist's Guide to Epidemiology Models of Infectious Disease," Journal of Economic Perspectives, American Economic Association, vol. 34(4), pages 79-104, Fall.
    27. Robin C. Sickles & William C. Horrace (ed.), 2014. "Festschrift in Honor of Peter Schmidt," Springer Books, Springer, edition 127, number 978-1-4899-8008-3, December.
    28. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    29. Ali Hortaçsu & Jiarui Liu & Timothy Schwieg, 2020. "Estimating the Fraction of Unreported Infections in Epidemics with a Known Epicenter: An Application to COVID-19," Working Papers 2020-37, Becker Friedman Institute for Research In Economics.
    30. Parmeter, Christopher F. & Kumbhakar, Subal C., 2014. "Efficiency Analysis: A Primer on Recent Advances," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(3-4), pages 191-385, December.
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    1. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
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    3. Gearhart, Richard & Michieka, Nyakundi & Anders, Anne, 2023. "The effectiveness of COVID deaths to COVID policies: A robust conditional approach," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 376-394.
    4. Richard Gearhart & Lyudmyla Sonchak-Ardan & Nyakundi Michieka, 2022. "The efficiency of COVID cases to COVID policies: a robust conditional approach," Empirical Economics, Springer, vol. 63(6), pages 2903-2948, December.

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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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