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Are stay-at-home orders more difficult to follow for low-income groups?

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  • Lou, Jiehong
  • Shen, Xingchi
  • Niemeier, Deb

Abstract

In response to the COVID-19 pandemic, a growing number of states, counties and cities in the United States issued mandatory stay-at-home orders as part of their efforts to slow down the spread of the virus. We argue that the consequences of this one-size-fits-all order will be differentially distributed among economic groups. In this paper, we examine social distance behavior changes for lower income populations. We conduct a comparative analysis of responses between lower-income and upper-income groups and assess their relative exposure to COVID-19 risks. Using a difference-in-difference-in-differences analysis of 3140 counties, we find social distance policy effect on the lower-income group is smaller than that of the upper-income group, by as much as 46% to 54%. Our explorations of the mechanisms behind the disparate effects suggest that for the work-related trips the stay-at-home orders do not significantly reduce low income work trips and this result is statistically significant. That is, the share of essential business defined by stay-at-home orders is significantly negatively correlated with income at county level. In the non-work-related trips, we find that both the lower-income and upper-income groups reduced visits to retail, recreation, grocery, and pharmacy visits after the stay-at-home order, with the upper-income group reducing trips more compared to lower-income group.

Suggested Citation

  • Lou, Jiehong & Shen, Xingchi & Niemeier, Deb, 2020. "Are stay-at-home orders more difficult to follow for low-income groups?," Journal of Transport Geography, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:jotrge:v:89:y:2020:i:c:s0966692320309716
    DOI: 10.1016/j.jtrangeo.2020.102894
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    5. Liu, Qiyang & Liu, Zhengying & Kang, Tingting & Zhu, Le & Zhao, Pengjun, 2022. "Transport inequities through the lens of environmental racism: Rural-urban migrants under Covid-19," Transport Policy, Elsevier, vol. 122(C), pages 26-38.
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    7. Sheng, Jaymee & Malani, Anup & Goel, Ashish & Botla, Purushotham, 2022. "JUE insights: Does mobility explain why slums were hit harder by COVID-19 in Mumbai, India?," Journal of Urban Economics, Elsevier, vol. 127(C).
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    9. Xingchi Shen & Yueming Lucy Qiu & Pengfei Liu & Anand Patwardhan, 2022. "The Effect of Rebate and Loan Incentives on Residential Heat Pump Adoption: Evidence from North Carolina," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(3), pages 741-789, July.
    10. Lili Li & Araz Taeihagh & Si Ying Tan, 2023. "A scoping review of the impacts of COVID-19 physical distancing measures on vulnerable population groups," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    11. Raphael Bruce & Alexsandros Cavgias & Luis Meloni, 2022. "Policy Enforcement in the Presence of Organized Crime: Evidence from Rio de Janeiro," Working Papers, Department of Economics 2022_22, University of São Paulo (FEA-USP).
    12. Cavgias, Alexsandros & Bruce, Raphael & Meloni, Luis, 2023. "Policy enforcement in the presence of organized crime: Evidence from Rio de Janeiro," Journal of Development Economics, Elsevier, vol. 162(C).

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