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COVID-19 Spread and Inter-County Travel: Daily Evidence from the U.S

Author

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  • Hakan Yilmazkuday

    (Department of Economics, Florida International University)

Abstract

Daily data at the U.S. county level suggest that coronavirus disease 2019 (COVID-19) cases and deaths are lower in counties where a higher share of people have stayed in the same county (or travelled less to other counties). This observation is tested formally by using a difference-in-difference design controlling for county-fixed effects and time-fixed effects, where weekly changes in COVID-19 cases or deaths are regressed on weekly changes in the share of people who have stayed in the same county during the previous 14 days. A counterfactual analysis based on the formal estimation results suggests that staying in the same county has the potential of reducing total weekly COVID-19 cases and deaths in the U.S. as much as by 139,503 and by 23,445, respectively.

Suggested Citation

  • Hakan Yilmazkuday, 2020. "COVID-19 Spread and Inter-County Travel: Daily Evidence from the U.S," Working Papers 2007, Florida International University, Department of Economics.
    • Handle: RePEc:fiu:wpaper:2007
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    File URL: https://economics.fiu.edu/research/pdfs/2020_working_papers/20071.pdf
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    References listed on IDEAS

    as
    1. Paolo Bajardi & Chiara Poletto & Jose J Ramasco & Michele Tizzoni & Vittoria Colizza & Alessandro Vespignani, 2011. "Human Mobility Networks, Travel Restrictions, and the Global Spread of 2009 H1N1 Pandemic," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
    2. Fang, Hanming & Wang, Long & Yang, Yang, 2020. "Human mobility restrictions and the spread of the Novel Coronavirus (2019-nCoV) in China," Journal of Public Economics, Elsevier, vol. 191(C).
    3. Victor Couture & Jonathan Dingel & Allison Green & Jessie Handbury & Kevin Williams, 2020. "Measuring Movement and Social Contact with Smartphone Data: A Real-Time Application to COVID-19," Opportunity and Inclusive Growth Institute Working Papers 35, Federal Reserve Bank of Minneapolis.
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    Cited by:

    1. Lu Lan & Gao Qisheng & Zhan Chenglin, 2023. "Influence Mechanism Analysis of the Spatial Evolution of Inter-Provincial Population Flow in China Based on Epidemic Prevention and Control," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(3), pages 1-22, June.
    2. Hakan Yilmazkuday, 2021. "Welfare costs of COVID‐19: Evidence from US counties," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 826-848, September.
    3. Sun, Fan & Jin, Minjie & Zhang, Tao & Huang, Wencheng, 2022. "Satisfaction differences in bus traveling among low-income individuals before and after COVID-19," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 311-332.
    4. 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).
    5. Deepti Muley & Md. Shahin & Charitha Dias & Muhammad Abdullah, 2020. "Role of Transport during Outbreak of Infectious Diseases: Evidence from the Past," Sustainability, MDPI, vol. 12(18), pages 1-22, September.

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    More about this item

    Keywords

    COVID-19; Coronavirus; Same-County Stayers; County-level Investigation; the U.S.;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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