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Effects of the COVID-19 Pandemic on Population Mobility under Mild Policies: Causal Evidence from Sweden

Author

Listed:
  • Matz Dahlberg
  • Per-Anders Edin
  • Erik Gronqvist
  • Johan Lyhagen
  • John Osth
  • Alexey Siretskiy
  • Marina Toger

Abstract

Sweden has adopted far less restrictive social distancing policies than most countries following the COVID-19 pandemic. This paper uses data on all mobile phone users, from one major Swedish mobile phone network, to examine the impact of the Coronavirus outbreak under the Swedish mild recommendations and restrictions regime on individual mobility and if changes in geographical mobility vary over different socio-economic strata. Having access to data for January-March in both 2019 and 2020 enables the estimation of causal effects of the COVID-19 outbreak by adopting a Difference-in-Differences research design. The paper reaches four main conclusions: (i) The daytime population in residential areas increased significantly (64 percent average increase); (ii) The daytime presence in industrial and commercial areas decreased significantly (33 percent average decrease); (iii) The distance individuals move from their homes during a day was substantially reduced (38 percent decrease in the maximum distance moved and 36 percent increase in share of individuals who move less than one kilometer from home); (iv) Similar reductions in mobility were found for residents in areas with different socioeconomic and demographic characteristics. These results show that mild government policies can compel people to adopt social distancing behavior.

Suggested Citation

  • Matz Dahlberg & Per-Anders Edin & Erik Gronqvist & Johan Lyhagen & John Osth & Alexey Siretskiy & Marina Toger, 2020. "Effects of the COVID-19 Pandemic on Population Mobility under Mild Policies: Causal Evidence from Sweden," Papers 2004.09087, arXiv.org.
    • Handle: RePEc:arx:papers:2004.09087
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    Citations

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    Cited by:

    1. Tharcisio Leone, 2020. "COVID-19 sends the bill: Socially disadvantaged workers suffer the severest losses in earnings," Documentos de Trabajo 18291, The Latin American and Caribbean Economic Association (LACEA).
    2. J. Daniel Aromí & M. Paula Bonel & Julián Cristiá & Martín Llada, 2020. "Socio-economic status and mobility during the COVID-19 pandemic: An analysis of large Latin American urban areas," Asociación Argentina de Economía Política: Working Papers 4307, Asociación Argentina de Economía Política.
    3. Ali Cheshmehzangi & Maycon Sedrez & Junhang Ren & Dezhou Kong & Yifan Shen & Sinan Bao & Junhao Xu & Zhaohui Su & Ayotunde Dawodu, 2021. "The Effect of Mobility on the Spread of COVID-19 in Light of Regional Differences in the European Union," Sustainability, MDPI, vol. 13(10), pages 1-24, May.
    4. Oluwayemi-Oniya Aderibigbe & Trynos Gumbo, 2022. "Variations in Mode Choice of Residents Prior and during COVID-19: An Empirical Evidence from Johannesburg, South Africa," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    5. Stephen J. Davis & Dingqian Liu & Xuguang Simon Sheng, 2020. "Stock Prices, Lockdowns, and Economic Activity in the Time of Coronavirus," Working Papers 2020-156, Becker Friedman Institute for Research In Economics.
    6. Steven J. Davis & Dingqian Liu & Xuguang Simon Sheng, 2022. "Stock Prices and Economic Activity in the Time of Coronavirus," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(1), pages 32-67, March.
    7. Situngkir, Hokky & Lumbantobing, Andika Bernad, 2020. "The Pandemics in Artificial Society: Agent-Based Model to Reflect Strategies on COVID-19," MPRA Paper 102075, University Library of Munich, Germany.
    8. Andruetto, Claudia & Bin, Elisa & Susilo, Yusak & Pernestål, Anna, 2023. "Transition from physical to online shopping alternatives due to the COVID-19 pandemic - A case study of Italy and Sweden," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    9. Avital Angel & Achituv Cohen & Sagi Dalyot & Pnina Plaut, 2023. "Impact of COVID-19 policies on pedestrian traffic and walking patterns," Environment and Planning B, , vol. 50(5), pages 1178-1193, June.
    10. Zhang, Yunchang & Fricker, Jon D., 2021. "Quantifying the impact of COVID-19 on non-motorized transportation: A Bayesian structural time series model," Transport Policy, Elsevier, vol. 103(C), pages 11-20.
    11. Sarbast Moslem & Tiziana Campisi & Agnieszka Szmelter-Jarosz & Szabolcs Duleba & Kh Md Nahiduzzaman & Giovanni Tesoriere, 2020. "Best–Worst Method for Modelling Mobility Choice after COVID-19: Evidence from Italy," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    12. Adam Przybylowski & Sandra Stelmak & Michal Suchanek, 2021. "Mobility Behaviour in View of the Impact of the COVID-19 Pandemic—Public Transport Users in Gdansk Case Study," Sustainability, MDPI, vol. 13(1), pages 1-12, January.
    13. Lina Hedman & Kati Kadarik & Roger Andersson & John Östh, 2021. "Daily Mobility Patterns: Reducing or Reproducing Inequalities and Segregation?," Social Inclusion, Cogitatio Press, vol. 9(2), pages 208-221.
    14. Marina Toger & Karima Kourtit & Peter Nijkamp & John Östh, 2021. "Mobility during the COVID-19 Pandemic: A Data-Driven Time-Geographic Analysis of Health-Induced Mobility Changes," Sustainability, MDPI, vol. 13(7), pages 1-21, April.
    15. Michał Suchanek & Agnieszka Szmelter-Jarosz, 2023. "Car enthusiasm during the second and fourth waves of COVID-19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.

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