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COVID-19 and Income Inequality: Evidence from Monthly Population Registers

Authors: Nikolay Angelov; Daniel Waldenström;

COVID-19 and Income Inequality: Evidence from Monthly Population Registers

Abstract

We measure the distributional impact of the COVID-19 pandemic using newly released population register data in Sweden. Monthly earnings inequality increased during the pandemic, and the key driver is income losses among low-paid individuals while middle- and high-income earners were almost unaffected. In terms of employment, as measured by having positive monthly earnings, the pandemic had a larger negative impact on private-sector workers and on women. In terms of earnings conditional on being employed, the effect was still more negative for women, but less negative for private-sector workers compared to publicly employed. Using data on individual take-up of government COVID-19 support, we show that policy significantly dampened the inequality increase, but did not fully offset it. Annual total market income inequality, which also includes capital income and taxable transfers, shows similar patterns of increasing inequality during the pandemic.The online version contains supplementary material available at 10.1007/s10888-022-09560-8.

Keywords

Pandemic, Government policy, ddc:330, H12, pandemic, H24, J22, COVID-19, Article, government policy, Earnings, Income inequality, D31, earnings, income inequality

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%
Green
bronze