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Covid-19 in Deutschland – Erklärung, Prognose und Einfluss gesundheitspolitischer Maßnahmen

Author

Listed:
  • Donsimoni Jean Roch

    (Johannes Gutenberg Universität, Lehrstuhl für VWL, insb. Makroökonomik, Jakob-Welder-Weg 4, 55118MainzGermany)

  • Glawion René

    (Universität Hamburg, Fakultät für Wirtschafts- und Sozialwissenschaften, Volkswirtschaftslehre, Von-Melle-Park 5, 20146HamburgGermany)

  • Hartl Tobias

    (Universität Regensburg, Lehrstuhl für Ökonometrie, 93053RegensburgGermany)

  • Plachter Bodo

    (Universitätsmedizin Mainz, Institut für Virologie, Obere Zahlbacher Str. 67, 55131MainzGermany)

  • Timmer Jens

    (Universität Freiburg, Physikalisches Institut, CIBSS – Centre for Integrative Biological Signaling Studies, Hermann-Herder Str. 3, 79104 FreiburgGermany)

  • Wälde Klaus

    (Johannes Gutenberg Universität, Lehrstuhl für VWL, insb. Makroökonomik, Visiting Research Fellow IZA, Jakob-Welder-Weg 4, 55118MainzGermany)

  • Weber Enzo

    (Institut für Arbeitsmarkt- und Berufsforschung (IAB) der Bundesagentur für Arbeit (BA), Regensburger Straße 104, 90478 NürnbergGermany)

  • Weiser Constantin

    (Johannes Gutenberg Universität, Fachbereich Rechts- & Wirtschaftswissenschaften, Quantitative Methodenlehre, Jakob-Welder-Weg 4, 55118MainzGermany)

Abstract

Die Autoren erklären den bisherigen Verlauf von Covid-19 in Deutschland durch Regressionsanalysen und epidemiologische Modelle. Sie beschreiben und quantifizieren den Effekt der gesundheitspolitischen Maßnahmen (GPM), die bis zum 19. April in Kraft waren. Sie berechnen den erwarteten Verlauf der Covid-19-Epidemie in Deutschland, wenn es diese Maßnahmen nicht gegeben hätte, und zeigen, dass die GPM einen erheblichen Beitrag zur Reduktion der Infektionszahlen geleistet haben. Die seit 20. April gelockerten GPM sind zwischen den Bundesländern relativ heterogen, was ein Glücksfall für die Wissenschaft ist. Mittels einer Analyse dieser Heterogenität kann aufgedeckt werden, welche Maßnahmen für eine Bekämpfung einer eventuellen zweiten Infektionswelle besonders hilfreich und besonders schädlich sind.

Suggested Citation

  • Donsimoni Jean Roch & Glawion René & Hartl Tobias & Plachter Bodo & Timmer Jens & Wälde Klaus & Weber Enzo & Weiser Constantin, 2020. "Covid-19 in Deutschland – Erklärung, Prognose und Einfluss gesundheitspolitischer Maßnahmen," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 21(3), pages 250-262, September.
    • Handle: RePEc:bpj:pewipo:v:21:y:2020:i:3:p:250-262:n:2
    DOI: 10.1515/pwp-2020-0019
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    Cited by:

    1. Reinhold Kosfeld & Timo Mitze & Johannes Rode & Klaus Wälde, 2021. "The Covid‐19 containment effects of public health measures: A spatial difference‐in‐differences approach," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 799-825, September.
    2. Krenz Astrid & Strulik Holger, 2021. "The benefits of remoteness – digital mobility data, regional road infrastructure, and COVID-19 infections," German Economic Review, De Gruyter, vol. 22(3), pages 257-287, August.

    More about this item

    Keywords

    I18; E17; C63; C22; Covid-19; SARS-CoV-2; Corona-Epidemie Deutschland; Prognose; Strukturbruchanalyse; epidemiologische Modelle;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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