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COVID-19 restrictions in the US: wage vulnerability by education, race and gender

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  • Borja Gambau
  • Juan C. Palomino
  • Juan G. Rodríguez
  • Raquel Sebastian
Abstract
We study economic vulnerability to the stay-at-home orders and social distancing measures imposed to prevent COVID-19 contagion in the US by education, race, gender, and state. Under 2 months of lockdown plus 10 months of partial functioning we find that, without compensating policies, wage inequality and poverty would increase in the US for all social groups and states. We estimate a national potential increase in inequality of 4.1 Gini points and of 9.7 percentage points for poverty, with uneven increases by race, gender, and education. The restrictions imposed to curb the pandemic produce a double process of divergence: both inequality within and between social groups increase, with education accounting for the largest part of the rise in inequality between groups. Education level differences also impact wage poverty risk more than differences by race or gender, making the low-educated the most vulnerable group, while workers with higher education of any race and gender are less exposed. When measuring the potential percentile rank change, most women with secondary education or higher move up, while most men without higher education suffer downward mobility. Our findings can inform public policy aiming to address the disparities in vulnerability to pandemic-related shocks across different socioeconomic groups.

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  • Borja Gambau & Juan C. Palomino & Juan G. Rodríguez & Raquel Sebastian, 2022. "COVID-19 restrictions in the US: wage vulnerability by education, race and gender," Applied Economics, Taylor & Francis Journals, vol. 54(25), pages 2900-2915, May.
    • Handle: RePEc:taf:applec:v:54:y:2022:i:25:p:2900-2915
    DOI: 10.1080/00036846.2021.1999899
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    Cited by:

    1. Schettino, Francesco & Scicchitano, Sergio & Suppa, Domenico, 2024. "COVID 19 and Wage Polarization: A task based approach," GLO Discussion Paper Series 1398, Global Labor Organization (GLO).
    2. Tong Li & Yanfen Wang & Lizhen Cui & Ranjay K. Singh & Hongdou Liu & Xiufang Song & Zhihong Xu & Xiaoyong Cui, 2023. "Exploring the evolving landscape of COVID-19 interfaced with livelihoods," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    3. Kai Yu & Lirong Wu & Lujie Zhou, 2022. "Research on the Mixed Education Mode for the Safety Engineering Major during the Coronavirus (COVID-19) Epidemic," IJERPH, MDPI, vol. 19(4), pages 1-14, February.
    4. Carmen Aina & Irene Brunetti & Chiara Mussida & Sergio Scicchitano, 2023. "Distributional effects of COVID-19," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 221-256, March.

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    More about this item

    JEL classification:

    • D33 - Microeconomics - - Distribution - - - Factor Income Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O51 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - U.S.; Canada

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