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A Synthetic Control Method Analysis of Schools Opening and Covid-19 Outbreak in Italy

Author

Listed:
  • Vincenzo Alfano
  • Salvatore Ercolano
  • Lorenzo Cicatiello

Abstract

Schools have been very central in the debate about COVID-19. On one hand, there have been many supporters of the argument to keep them open, for their importance for the youngsters, and for the effort many countries played in establishing protocols to keep them safe. On the other hand, a counter-argument supported by several other stakeholders, has been that being a major occasion of aggregation between teenager and adults accompanying their children, and being a major occasion of congestion per the public transportation, keeping the schools open favours the spread of the virus. In this article, by the means of a quantitative analysis that exploits the quasi experimental setting offered by the scattered opening that schools have had in Italy, we aim to shed some light on the subject. More precisely, a synthetic control method approach suggests that Bolzano, the first province in Italy to have opened the schools after the summer break, has way more cases than its synthetic counterfactual, built from a donor pool constituted by the other Italian provinces. Results seem to confirm that that opening the schools causes and increase in the infections, and this has to be taken into account by the policymakers.

Suggested Citation

  • Vincenzo Alfano & Salvatore Ercolano & Lorenzo Cicatiello, 2020. "A Synthetic Control Method Analysis of Schools Opening and Covid-19 Outbreak in Italy," CESifo Working Paper Series 8784, CESifo.
    • Handle: RePEc:ces:ceswps:_8784
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    References listed on IDEAS

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    1. Sebastian Galiani & Brian Quistorff, 2017. "The synth runner package: Utilities to automate synthetic control estimation using synth," Stata Journal, StataCorp LP, vol. 17(4), pages 834-849, December.
    2. Facundo Piguillem & Liyan Shi, 2022. "Optimal Covid-19 Quarantine and Testing Policies," The Economic Journal, Royal Economic Society, vol. 132(647), pages 2534-2562.
    3. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    4. Sardar, Tridip & Nadim, Sk Shahid & Rana, Sourav & Chattopadhyay, Joydev, 2020. "Assessment of lockdown effect in some states and overall India: A predictive mathematical study on COVID-19 outbreak," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    5. Benjamin Born & Alexander M Dietrich & Gernot J Müller, 2021. "The lockdown effect: A counterfactual for Sweden," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-13, April.
    6. Vincenzo Alfano & Salvatore Ercolano, 2020. "The Efficacy of Lockdown Against COVID-19: A Cross-Country Panel Analysis," Applied Health Economics and Health Policy, Springer, vol. 18(4), pages 509-517, August.
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    Cited by:

    1. Marc Diederichs & Reyn van Ewijk & Ingo E. Isphording & Nico Pestel, 2022. "Schools under mandatory testing can mitigate the spread of SARS-CoV-2," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(26), pages 2201724119-, June.

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    More about this item

    Keywords

    Covid-19; synthetic control method; schools opening; Italy; coronavirus;
    All these keywords.

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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