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The Effect of Control Measures on COVID-19 Transmission and Work Resumption: International Evidence

Author

Listed:
  • Meng, Lina
  • Zhou, Yinggang
  • Zhang, Ruige
  • Ye, Zhen
  • Xia, Senmao
  • Cerulli, Giovanni
  • Casady, Carter
  • Härdle, Wolfgang Karl

Abstract

Many countries have taken non-pharmaceutical interventions (NPIs) to contain the spread of the coronavirus (COVID-19) and push the recovery of national economies. This paper investigates the effect of these control measures by comparing five selected countries, China, Italy, Germany, the United Kingdom, and the United States. There is evidence that the degree of early intervention and efficacy of control measures are essential to contain the pandemic. China stands out because its early and strictly enforced interventions are effective to contain the virus spread. Furthermore, we quantify the causal effect of different control measures on COVID-19 transmission and work resumption in China. Surprisingly, digital contact tracing and delegating clear responsibility to the local community appear to be the two most effective policy measures for disease containment and work resumption. Public information campaigns and social distancing also help to flatten the peak significantly. Moreover, material logistics that prevent medical supply shortages provide an additional conditioning factor for disease containment and work resumption. Fiscal policy, however, is less effective at the early to middle stage of the pandemic.

Suggested Citation

  • Meng, Lina & Zhou, Yinggang & Zhang, Ruige & Ye, Zhen & Xia, Senmao & Cerulli, Giovanni & Casady, Carter & Härdle, Wolfgang Karl, 2020. "The Effect of Control Measures on COVID-19 Transmission and Work Resumption: International Evidence," IRTG 1792 Discussion Papers 2020-011, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    • Handle: RePEc:zbw:irtgdp:2020011
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    References listed on IDEAS

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    1. Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021. "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
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    Cited by:

    1. Cuicui Lu & Weining Wang & Jeffrey M. Wooldridge, 2018. "Using generalized estimating equations to estimate nonlinear models with spatial data," Papers 1810.05855, arXiv.org.
    2. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Wang, Weining & Wooldridge, Jeffrey M. & Xu, Mengshan, 2020. "Improved Estimation of Dynamic Models of Conditional Means and Variances," IRTG 1792 Discussion Papers 2020-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

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    More about this item

    Keywords

    COVID-19; coronavirus;

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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