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Polarized Politics of Pandemic Response and the Covid-19 Connectedness Across the U.S. States

Author

Listed:
  • Umut Akovali

    (Koc University)

  • Kamil Yilmaz

    (Koc University)

Abstract

This paper investigates the state-level differences in government and community responses to the Covid-19 pandemic, leading to different growth trajectories of Covid-19 cases and their connectedness across the U.S. states. Our regression analysis shows that higher growth trajectories are observed in the states that implemented the lax government and community response to the pandemic. Moving to the analysis of spillovers/connectedness of Covid-19 cases across the states, we apply the Diebold-Yilmaz connectedness methodology to the growth rates of Covid-19 cases. Using the total directional connectedness measures, we find that the states with lax government and community response generated connectedness of Covid-19 cases to others. These findings are also supported by the secondary regression analysis of pairwise connectedness measures over time. Finally, the travel intensity between the pairs of states, indirectly measured by the data on smartphone location exposure, contributes significantly to the pairwise directional connectedness of Covid-19 across the states.

Suggested Citation

  • Umut Akovali & Kamil Yilmaz, 2020. "Polarized Politics of Pandemic Response and the Covid-19 Connectedness Across the U.S. States," Koç University-TUSIAD Economic Research Forum Working Papers 2019, Koc University-TUSIAD Economic Research Forum.
    • Handle: RePEc:koc:wpaper:2019
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    References listed on IDEAS

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    Cited by:

    1. Victor Couture & Jonathan I. Dingel & Allison E. Green & Jessie Handbury & Kevin R. Williams, 2020. "Measuring Movement and Social Contact with Smartphone Data: A Real-Time Application to COVID-19," NBER Working Papers 27560, National Bureau of Economic Research, Inc.
    2. Cheng, Tingting & Liu, Junli & Yao, Wenying & Zhao, Albert Bo, 2022. "The impact of COVID-19 pandemic on the volatility connectedness network of global stock market," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    3. Couture, Victor & Dingel, Jonathan I. & Green, Allison & Handbury, Jessie & Williams, Kevin R., 2022. "JUE Insight: Measuring movement and social contact with smartphone data: a real-time application to COVID-19," Journal of Urban Economics, Elsevier, vol. 127(C).

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    More about this item

    Keywords

    Covid-19; Coronavirus; Spillovers; Connectedness; Government policy stringency; Community mobility; Travel Intensity.;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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