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True Covid-19 mortality rates from administrative data

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  • Depalo, Domenico

Abstract

In this paper I use administrative data to estimate the number of deaths, the number of infections, and mortality rates from Covid-19 in Lombardia, the hot spot of the disease in Italy and Europe. The information is relevant for the policy maker, to make decisions, and for the public, to adopt appropriate behaviours. As the available data suffer from sample selection bias I use partial identification to derive these quantities. Partial identification combines as- sumptions with the data to deliver a set of admissible values, or bounds. Stronger assumptions yield stronger conclusions, but decrease the credibility of the inference. Therefore, I start with assumptions that are always satisfied, then I impose increasingly more restrictive assumptions. Using my preferred bounds, during March 2020 in Lombardia there were between 10,000 and 18,500 more deaths than before 2020. The narrowest bounds of mortality rates from Covid-19 are between 0.1% and 7.5%, much smaller than the 17.5% discussed for long time. This finding suggests that the case of Lombardia may not be as special as some argue.

Suggested Citation

  • Depalo, Domenico, 2020. "True Covid-19 mortality rates from administrative data," GLO Discussion Paper Series 630, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:630
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Chris Sampson’s journal round-up for 23rd November 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-11-23 12:00:14

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    2. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    3. YAMAMURA, Eiji & Tsutsui, Yoshiro, 2020. "Impact of closing schools on mental health during the COVID-19 pandemic: Evidence using panel data from Japan," MPRA Paper 105023, University Library of Munich, Germany.
    4. Guccio, Calogero, 2021. "Measuring resilience and fatality rate during the first wave of COVID-19 pandemic in Northern Italy: a note," EconStor Preprints 231374, ZBW - Leibniz Information Centre for Economics.
    5. Luca Bonacini & Giovanni Gallo & Sergio Scicchitano, 2021. "Working from home and income inequality: risks of a ‘new normal’ with COVID-19," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 303-360, January.

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    More about this item

    Keywords

    Covid-19; Mortality; Bounds;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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