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COVID-19 Severity: A New Approach to Quantifying Global Cases and Deaths

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  • Millimet, Daniel L.

    (Southern Methodist University)

  • Parmeter, Christopher F.

    (University of Miami)

Abstract

Accurate counts of cases and deaths are critical for devising an optimal pandemic response. Yet, 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 roughly 60 countries from January 1 through November 3, 2020. Specifically, we estimate a 'structural' model based on the workhorse SIR epidemiological model extended to incorporate measurement error. The results indicate significant under-reporting 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 under-reporting in the assessment of the extent of the pandemic. Thus, we view our approach as a complement to existing methods.

Suggested Citation

  • Millimet, Daniel L. & Parmeter, Christopher F., 2021. "COVID-19 Severity: A New Approach to Quantifying Global Cases and Deaths," IZA Discussion Papers 14116, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp14116
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    Cited by:

    1. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    2. Boto-García, David, 2023. "Investigating the two-way relationship between mobility flows and COVID-19 cases," Economic Modelling, Elsevier, vol. 118(C).
    3. 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.
    4. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
    5. 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.
    6. Danelon, André F. & Kumbhakar, Subal C., 2023. "Estimating COVID-19 under-reporting through stochastic frontier analysis and official statistics: A case study of São Paulo State, Brazil," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).

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    More about this item

    Keywords

    stochastic frontier analysis; nonclassical measurement error; COVID-19;
    All these keywords.

    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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